From 83b382fc4b6eddf2ae22942a901d9835d03cb8c2 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Wed, 4 Sep 2019 22:06:47 -0400
Subject: [PATCH 1/9] Created using Colaboratory

---
 .../LS_DSPT3_111_A_First_Look_at_Data.ipynb   | 483 ++++++++++++++++++
 1 file changed, 483 insertions(+)
 create mode 100644 module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb

diff --git a/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb b/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb
new file mode 100644
index 00000000..110330e2
--- /dev/null
+++ b/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb
@@ -0,0 +1,483 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "LS_DSPT3_111_A_First_Look_at_Data.ipynb",
+      "version": "0.3.2",
+      "provenance": [],
+      "collapsed_sections": [],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/b-whitman/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Okfr_uhwhS1X",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Lambda School Data Science - A First Look at Data\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9dtJETFRhnOG",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Lecture - let's explore Python DS libraries and examples!\n",
+        "\n",
+        "The Python Data Science ecosystem is huge. You've seen some of the big pieces - pandas, scikit-learn, matplotlib. What parts do you want to see more of?"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "WiBkgmPJhmhE",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import pandas as pd"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "P9Gx2pik9wbC",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "86fa207a-2d55-492d-b8a5-0bfcc1650663"
+      },
+      "source": [
+        "np.random.randint"
+      ],
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<function RandomState.randint>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 4
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "jxmjmUoq_e3E",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "x = [1,2,3,4]\n",
+        "y = [2,4,6,10]"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "cYf23Xz-_9w-",
+        "colab_type": "code",
+        "outputId": "747614f3-e65a-4a15-f29b-21b11c130266",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 171
+        }
+      },
+      "source": [
+        "df = pd.DataFrame({'first_col': x, 'second_col': y})\n",
+        "df['third_col'] = df['first_col'] + 2*df['second_col']\n",
+        "df['fourth_col'] = df['third_col'] > 10\n",
+        "df"
+      ],
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>first_col</th>\n",
+              "      <th>second_col</th>\n",
+              "      <th>third_col</th>\n",
+              "      <th>fourth_col</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
+              "      <td>5</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>10</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>3</td>\n",
+              "      <td>6</td>\n",
+              "      <td>15</td>\n",
+              "      <td>True</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>4</td>\n",
+              "      <td>10</td>\n",
+              "      <td>24</td>\n",
+              "      <td>True</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   first_col  second_col  third_col  fourth_col\n",
+              "0          1           2          5       False\n",
+              "1          2           4         10       False\n",
+              "2          3           6         15        True\n",
+              "3          4          10         24        True"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 6
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "DJIKkngQENf_",
+        "colab_type": "code",
+        "outputId": "30d339bb-098e-491a-9f9e-e4cc54778d16",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 79
+        }
+      },
+      "source": [
+        "df[df['second_col'] == 10]"
+      ],
+      "execution_count": 7,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>first_col</th>\n",
+              "      <th>second_col</th>\n",
+              "      <th>third_col</th>\n",
+              "      <th>fourth_col</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>4</td>\n",
+              "      <td>10</td>\n",
+              "      <td>24</td>\n",
+              "      <td>True</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   first_col  second_col  third_col  fourth_col\n",
+              "3          4          10         24        True"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 7
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lOqaPds9huME",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Assignment - now it's your turn\n",
+        "\n",
+        "Pick at least one Python DS library, and using documentation/examples reproduce in this notebook something cool. It's OK if you don't fully understand it or get it 100% working, but do put in effort and look things up."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "TGUS79cOhPWj",
+        "colab_type": "code",
+        "outputId": "79e8f3be-5588-4945-c6b9-112be394d995",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        }
+      },
+      "source": [
+        "arr_1 = np.random.randint(low=0, high=100, size=1000)\n",
+        "arr_2 = np.random.randint(low=0, high=100, size=1000)\n",
+        "plt.scatter(arr_1, arr_2)\n",
+        "\n",
+        "# Plotting 1000 random x's and y's"
+      ],
+      "execution_count": 20,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.PathCollection at 0x7f6da7f79710>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 20
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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YJyF/uNRPmsJG4WRFij3XoDRLg2q/yV1rn8HkLvJAeH6kxquUzoa16bMPYeOtD4n7WHru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\nDiOObqHv0KFDhxFHt9B36NChw4jj/wPUznKWMg86KgAAAABJRU5ErkJggg==\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "PA8bb4rRX1GZ",
+        "colab_type": "code",
+        "outputId": "f18ed091-9a7c-4adb-f6c0-a3066193c912",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 307
+        }
+      },
+      "source": [
+        "fib = [1]\n",
+        "for i in range(50):\n",
+        "  fib.append(fib[i-1]+fib[i])\n",
+        "# Fibonacci sequence in honor of the new Tool LP\n",
+        "\n",
+        "plt.scatter(fib, fib)"
+      ],
+      "execution_count": 21,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.PathCollection at 0x7f6da7f4c400>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 21
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "JvkQaJTHDhij",
+        "colab_type": "code",
+        "colab": {
+          "resources": {
+            "http://localhost:8080/nbextensions/google.colab/files.js": {
+              "data": "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",
+              "ok": true,
+              "headers": [
+                [
+                  "content-type",
+                  "application/javascript"
+                ]
+              ],
+              "status": 200,
+              "status_text": ""
+            }
+          },
+          "base_uri": "https://localhost:8080/",
+          "height": 75
+        },
+        "outputId": "da1f5368-0e8c-48cf-ee66-6e0a34e7c53a"
+      },
+      "source": [
+        "from google.colab import files\n",
+        "uploaded = files.upload()"
+      ],
+      "execution_count": 22,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/html": [
+              "\n",
+              "     <input type=\"file\" id=\"files-0f6dc5f6-da34-47ab-9be4-4862d06695bd\" name=\"files[]\" multiple disabled />\n",
+              "     <output id=\"result-0f6dc5f6-da34-47ab-9be4-4862d06695bd\">\n",
+              "      Upload widget is only available when the cell has been executed in the\n",
+              "      current browser session. Please rerun this cell to enable.\n",
+              "      </output>\n",
+              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
+            ],
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "Saving adult.csv to adult.csv\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "BT9gdS7viJZa",
+        "colab_type": "text"
+      },
+      "source": [
+        "### Assignment questions\n",
+        "\n",
+        "After you've worked on some code, answer the following questions in this text block:\n",
+        "\n",
+        "1.  Describe in a paragraph of text what you did and why, as if you were writing an email to somebody interested but nontechnical.\n",
+        "\n",
+        "2.  What was the most challenging part of what you did?\n",
+        "\n",
+        "3.  What was the most interesting thing you learned?\n",
+        "\n",
+        "4.  What area would you like to explore with more time?\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_XXg2crAipwP",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Stretch goals and resources\n",
+        "\n",
+        "Following are *optional* things for you to take a look at. Focus on the above assignment first, and make sure to commit and push your changes to GitHub (and since this is the first assignment of the sprint, open a PR as well).\n",
+        "\n",
+        "- [pandas documentation](https://pandas.pydata.org/pandas-docs/stable/)\n",
+        "- [scikit-learn documentation](http://scikit-learn.org/stable/documentation.html)\n",
+        "- [matplotlib documentation](https://matplotlib.org/contents.html)\n",
+        "- [Awesome Data Science](https://github.com/bulutyazilim/awesome-datascience) - a list of many types of DS resources\n",
+        "\n",
+        "Stretch goals:\n",
+        "\n",
+        "- Find and read blogs, walkthroughs, and other examples of people working through cool things with data science - and share with your classmates!\n",
+        "- Write a blog post (Medium is a popular place to publish) introducing yourself as somebody learning data science, and talking about what you've learned already and what you're excited to learn more about."
+      ]
+    }
+  ]
+}
\ No newline at end of file

From dc27b1960ea7fad7b96bac6fdd7dd77bea07b036 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Wed, 4 Sep 2019 23:27:54 -0400
Subject: [PATCH 2/9] Created using Colaboratory

---
 .../LS_DSPT3_111_A_First_Look_at_Data.ipynb   | 1380 ++++++++++++++++-
 1 file changed, 1353 insertions(+), 27 deletions(-)

diff --git a/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb b/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb
index 110330e2..8b5eecc5 100644
--- a/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb
+++ b/module1-afirstlookatdata/LS_DSPT3_111_A_First_Look_at_Data.ipynb
@@ -68,16 +68,16 @@
       "metadata": {
         "id": "P9Gx2pik9wbC",
         "colab_type": "code",
+        "outputId": "5ba62774-1610-438b-9e4f-aa5a6cc43eb2",
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 35
-        },
-        "outputId": "86fa207a-2d55-492d-b8a5-0bfcc1650663"
+        }
       },
       "source": [
         "np.random.randint"
       ],
-      "execution_count": 4,
+      "execution_count": 0,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -89,7 +89,7 @@
           "metadata": {
             "tags": []
           },
-          "execution_count": 4
+          "execution_count": 25
         }
       ]
     },
@@ -112,7 +112,7 @@
       "metadata": {
         "id": "cYf23Xz-_9w-",
         "colab_type": "code",
-        "outputId": "747614f3-e65a-4a15-f29b-21b11c130266",
+        "outputId": "e7d72879-5121-4a69-c351-1e2c1c352f9d",
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 171
@@ -124,7 +124,7 @@
         "df['fourth_col'] = df['third_col'] > 10\n",
         "df"
       ],
-      "execution_count": 6,
+      "execution_count": 0,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -198,7 +198,7 @@
           "metadata": {
             "tags": []
           },
-          "execution_count": 6
+          "execution_count": 27
         }
       ]
     },
@@ -207,7 +207,7 @@
       "metadata": {
         "id": "DJIKkngQENf_",
         "colab_type": "code",
-        "outputId": "30d339bb-098e-491a-9f9e-e4cc54778d16",
+        "outputId": "9235c5d8-1e55-4659-f79e-60762ed3ef35",
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 79
@@ -216,7 +216,7 @@
       "source": [
         "df[df['second_col'] == 10]"
       ],
-      "execution_count": 7,
+      "execution_count": 0,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -266,7 +266,7 @@
           "metadata": {
             "tags": []
           },
-          "execution_count": 7
+          "execution_count": 28
         }
       ]
     },
@@ -287,7 +287,7 @@
       "metadata": {
         "id": "TGUS79cOhPWj",
         "colab_type": "code",
-        "outputId": "79e8f3be-5588-4945-c6b9-112be394d995",
+        "outputId": "6de440d4-4d62-44a1-93d7-e80ce6a846ed",
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 287
@@ -300,24 +300,24 @@
         "\n",
         "# Plotting 1000 random x's and y's"
       ],
-      "execution_count": 20,
+      "execution_count": 59,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.collections.PathCollection at 0x7f6da7f79710>"
+              "<matplotlib.collections.PathCollection at 0x7f6da7732da0>"
             ]
           },
           "metadata": {
             "tags": []
           },
-          "execution_count": 20
+          "execution_count": 59
         },
         {
           "output_type": "display_data",
           "data": {
-            "image/png": 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YJyF/uNRPmsJG4WRFij3XoDRLg2q/yV1rn8HkLvJAeH6kxquUzoa16bMPYeOtD4n7WHru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\nDiOObqHv0KFDhxFHt9B36NChw4jj/wPUznKWMg86KgAAAABJRU5ErkJggg==\n",
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W1IMx9txUcOZibW12ExEXc2MCSd9R6e6yFFL6suldQF8u9OMR9gvIT+RjDL0E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\nrcmcom550zNLIytSfWP7GHA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uK2W3VsovBZDFiOqlGDh9b6OnfvndqHO2fc2HkHqliQww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\n",
             "text/plain": [
               "<Figure size 432x288 with 1 Axes>"
             ]
@@ -333,7 +333,7 @@
       "metadata": {
         "id": "PA8bb4rRX1GZ",
         "colab_type": "code",
-        "outputId": "f18ed091-9a7c-4adb-f6c0-a3066193c912",
+        "outputId": "9d13fc3b-f864-430d-8060-9923c6da13f4",
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 307
@@ -344,22 +344,23 @@
         "for i in range(50):\n",
         "  fib.append(fib[i-1]+fib[i])\n",
         "# Fibonacci sequence in honor of the new Tool LP\n",
+        "# Sort of -- a real Fibo would start with [0, 1, ...]. This is a rude approximation.\n",
         "\n",
         "plt.scatter(fib, fib)"
       ],
-      "execution_count": 21,
+      "execution_count": 0,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.collections.PathCollection at 0x7f6da7f4c400>"
+              "<matplotlib.collections.PathCollection at 0x7f6da7d227f0>"
             ]
           },
           "metadata": {
             "tags": []
           },
-          "execution_count": 21
+          "execution_count": 30
         },
         {
           "output_type": "display_data",
@@ -380,6 +381,7 @@
       "metadata": {
         "id": "JvkQaJTHDhij",
         "colab_type": "code",
+        "outputId": "a57aefd5-cfa9-473e-b946-ba0b50db8eaf",
         "colab": {
           "resources": {
             "http://localhost:8080/nbextensions/google.colab/files.js": {
@@ -397,22 +399,22 @@
           },
           "base_uri": "https://localhost:8080/",
           "height": 75
-        },
-        "outputId": "da1f5368-0e8c-48cf-ee66-6e0a34e7c53a"
+        }
       },
       "source": [
         "from google.colab import files\n",
-        "uploaded = files.upload()"
+        "uploaded = files.upload()\n",
+        "# Imported census income dataset from UCI ML repository"
       ],
-      "execution_count": 22,
+      "execution_count": 35,
       "outputs": [
         {
           "output_type": "display_data",
           "data": {
             "text/html": [
               "\n",
-              "     <input type=\"file\" id=\"files-0f6dc5f6-da34-47ab-9be4-4862d06695bd\" name=\"files[]\" multiple disabled />\n",
-              "     <output id=\"result-0f6dc5f6-da34-47ab-9be4-4862d06695bd\">\n",
+              "     <input type=\"file\" id=\"files-be9b87b0-e33e-4fc6-bf28-358aca9a28b2\" name=\"files[]\" multiple disabled />\n",
+              "     <output id=\"result-be9b87b0-e33e-4fc6-bf28-358aca9a28b2\">\n",
               "      Upload widget is only available when the cell has been executed in the\n",
               "      current browser session. Please rerun this cell to enable.\n",
               "      </output>\n",
@@ -429,12 +431,1330 @@
         {
           "output_type": "stream",
           "text": [
-            "Saving adult.csv to adult.csv\n"
+            "Saving adult.csv to adult (1).csv\n"
           ],
           "name": "stdout"
         }
       ]
     },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "WEXiuj-SMLi0",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import io\n",
+        "df = pd.read_csv(io.BytesIO(uploaded['adult.csv']))\n",
+        "\n",
+        "# Used uploaded file to create Pandas dataframe"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "5zhUXs3OPueL",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "columns = ['age', 'workclass', 'fnlwgt', 'education', 'education_num', 'marital_status', 'occupation', 'relationship', 'race', 'sex', 'capital_gain', 'capital_loss', 'hours_per_wk', 'native_country', 'income']\n",
+        "df.columns = columns\n",
+        "\n",
+        "# Give columns titles per the UCI ML Repo page for the dataset\n",
+        "# This seems to have actually replaced the original first row with the column headers. That's not exactly what I wanted... workaround?"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "-LwupQdyOJHN",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "d56fce20-948b-45de-ae7f-c4819fa8d2ad"
+      },
+      "source": [
+        "df.head(20)"
+      ],
+      "execution_count": 67,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>age</th>\n",
+              "      <th>workclass</th>\n",
+              "      <th>fnlwgt</th>\n",
+              "      <th>education</th>\n",
+              "      <th>education_num</th>\n",
+              "      <th>marital_status</th>\n",
+              "      <th>occupation</th>\n",
+              "      <th>relationship</th>\n",
+              "      <th>race</th>\n",
+              "      <th>sex</th>\n",
+              "      <th>capital_gain</th>\n",
+              "      <th>capital_loss</th>\n",
+              "      <th>hours_per_wk</th>\n",
+              "      <th>native_country</th>\n",
+              "      <th>income</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>50</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>83311</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>13</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>38</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>215646</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Divorced</td>\n",
+              "      <td>Handlers-cleaners</td>\n",
+              "      <td>Not-in-family</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>53</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>234721</td>\n",
+              "      <td>11th</td>\n",
+              "      <td>7</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Handlers-cleaners</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>Black</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>28</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>338409</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Wife</td>\n",
+              "      <td>Black</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>Cuba</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>37</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>284582</td>\n",
+              "      <td>Masters</td>\n",
+              "      <td>14</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Wife</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>49</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>160187</td>\n",
+              "      <td>9th</td>\n",
+              "      <td>5</td>\n",
+              "      <td>Married-spouse-absent</td>\n",
+              "      <td>Other-service</td>\n",
+              "      <td>Not-in-family</td>\n",
+              "      <td>Black</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>16</td>\n",
+              "      <td>Jamaica</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>52</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>209642</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>45</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>31</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>45781</td>\n",
+              "      <td>Masters</td>\n",
+              "      <td>14</td>\n",
+              "      <td>Never-married</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Not-in-family</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>14084</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>42</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>159449</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>5178</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>37</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>280464</td>\n",
+              "      <td>Some-college</td>\n",
+              "      <td>10</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>Black</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>80</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>30</td>\n",
+              "      <td>State-gov</td>\n",
+              "      <td>141297</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>Asian-Pac-Islander</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>India</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>23</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>122272</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Never-married</td>\n",
+              "      <td>Adm-clerical</td>\n",
+              "      <td>Own-child</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>30</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>32</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>205019</td>\n",
+              "      <td>Assoc-acdm</td>\n",
+              "      <td>12</td>\n",
+              "      <td>Never-married</td>\n",
+              "      <td>Sales</td>\n",
+              "      <td>Not-in-family</td>\n",
+              "      <td>Black</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>40</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>121772</td>\n",
+              "      <td>Assoc-voc</td>\n",
+              "      <td>11</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Craft-repair</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>Asian-Pac-Islander</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>?</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>34</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>245487</td>\n",
+              "      <td>7th-8th</td>\n",
+              "      <td>4</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Transport-moving</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>Amer-Indian-Eskimo</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>45</td>\n",
+              "      <td>Mexico</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>25</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>176756</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Never-married</td>\n",
+              "      <td>Farming-fishing</td>\n",
+              "      <td>Own-child</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>35</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>32</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>186824</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Never-married</td>\n",
+              "      <td>Machine-op-inspct</td>\n",
+              "      <td>Unmarried</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>38</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>28887</td>\n",
+              "      <td>11th</td>\n",
+              "      <td>7</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Sales</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&lt;=50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>43</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>292175</td>\n",
+              "      <td>Masters</td>\n",
+              "      <td>14</td>\n",
+              "      <td>Divorced</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Unmarried</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>45</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>40</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>193524</td>\n",
+              "      <td>Doctorate</td>\n",
+              "      <td>16</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "    age          workclass  fnlwgt  ... hours_per_wk  native_country  income\n",
+              "0    50   Self-emp-not-inc   83311  ...           13   United-States   <=50K\n",
+              "1    38            Private  215646  ...           40   United-States   <=50K\n",
+              "2    53            Private  234721  ...           40   United-States   <=50K\n",
+              "3    28            Private  338409  ...           40            Cuba   <=50K\n",
+              "4    37            Private  284582  ...           40   United-States   <=50K\n",
+              "5    49            Private  160187  ...           16         Jamaica   <=50K\n",
+              "6    52   Self-emp-not-inc  209642  ...           45   United-States    >50K\n",
+              "7    31            Private   45781  ...           50   United-States    >50K\n",
+              "8    42            Private  159449  ...           40   United-States    >50K\n",
+              "9    37            Private  280464  ...           80   United-States    >50K\n",
+              "10   30          State-gov  141297  ...           40           India    >50K\n",
+              "11   23            Private  122272  ...           30   United-States   <=50K\n",
+              "12   32            Private  205019  ...           50   United-States   <=50K\n",
+              "13   40            Private  121772  ...           40               ?    >50K\n",
+              "14   34            Private  245487  ...           45          Mexico   <=50K\n",
+              "15   25   Self-emp-not-inc  176756  ...           35   United-States   <=50K\n",
+              "16   32            Private  186824  ...           40   United-States   <=50K\n",
+              "17   38            Private   28887  ...           50   United-States   <=50K\n",
+              "18   43   Self-emp-not-inc  292175  ...           45   United-States    >50K\n",
+              "19   40            Private  193524  ...           60   United-States    >50K\n",
+              "\n",
+              "[20 rows x 15 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 67
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "znTd1LUrPKKi",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 295
+        },
+        "outputId": "a8af7bfa-9c5d-473d-f893-1b25a94af4a8"
+      },
+      "source": [
+        "df.dtypes"
+      ],
+      "execution_count": 44,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "age                int64\n",
+              "workclass         object\n",
+              "fnlwgt             int64\n",
+              "education         object\n",
+              "education_num      int64\n",
+              "marital_status    object\n",
+              "occupation        object\n",
+              "relationship      object\n",
+              "race              object\n",
+              "sex               object\n",
+              "capital_gain       int64\n",
+              "capital_loss       int64\n",
+              "hours_per_wk       int64\n",
+              "native_country    object\n",
+              "income            object\n",
+              "dtype: object"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 44
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "09iXlStgZZJF",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "067ff3d0-9c3e-4f2d-8150-2587e07b1dbe"
+      },
+      "source": [
+        "df['education_num'].median()\n",
+        "# Median level of education: some college"
+      ],
+      "execution_count": 66,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "10.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 66
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "3hez2x2laGrx",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "344e62b8-a922-4caf-ee09-59eddafedc19"
+      },
+      "source": [
+        "plt.scatter(df['education_num'], df['capital_gain'])\n",
+        "\n",
+        "# Scatter plot comparing level of education and capital gains\n",
+        "# What's going on at the top there...?"
+      ],
+      "execution_count": 68,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.PathCollection at 0x7f6da7710ba8>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 68
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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EJqmBCsdgVapXo7ms8ieL90ShITJJNZmNqV6N5rLKnyzeE4WGSA6kMffUNYtmj6lezeql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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "EFasvr90a9bI",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "4d48adbe-4ca4-46a4-e318-90eda30b9c82"
+      },
+      "source": [
+        "gains_100000 = df['capital_gain']>=90000\n",
+        "gains_100000.head()\n",
+        "is_gains = df[gains_100000]\n",
+        "is_gains.shape\n",
+        "\n",
+        "# Looks like the dataframe capital gains column maxes out at 99999. Interesting to know!\n",
+        "# Here I take the shape of the subset dataframe with only people who max out the capital gains column."
+      ],
+      "execution_count": 75,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(159, 15)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 75
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "eYGtwUd9dJ3p",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "324b9a77-e5f3-42e8-ff24-c5016c9c9884"
+      },
+      "source": [
+        "is_gains.head(30)\n",
+        "# ...and here I take a peek at the data."
+      ],
+      "execution_count": 77,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>age</th>\n",
+              "      <th>workclass</th>\n",
+              "      <th>fnlwgt</th>\n",
+              "      <th>education</th>\n",
+              "      <th>education_num</th>\n",
+              "      <th>marital_status</th>\n",
+              "      <th>occupation</th>\n",
+              "      <th>relationship</th>\n",
+              "      <th>race</th>\n",
+              "      <th>sex</th>\n",
+              "      <th>capital_gain</th>\n",
+              "      <th>capital_loss</th>\n",
+              "      <th>hours_per_wk</th>\n",
+              "      <th>native_country</th>\n",
+              "      <th>income</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1245</th>\n",
+              "      <td>54</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>166459</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1367</th>\n",
+              "      <td>52</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>152234</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>Asian-Pac-Islander</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>Japan</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1481</th>\n",
+              "      <td>53</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>263925</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Sales</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1527</th>\n",
+              "      <td>52</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>118025</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1615</th>\n",
+              "      <td>46</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>370119</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1681</th>\n",
+              "      <td>43</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>176270</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1764</th>\n",
+              "      <td>49</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>159816</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Wife</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>20</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1770</th>\n",
+              "      <td>50</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>171338</td>\n",
+              "      <td>Some-college</td>\n",
+              "      <td>10</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1825</th>\n",
+              "      <td>22</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>202920</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Never-married</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Unmarried</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>Dominican-Republic</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2102</th>\n",
+              "      <td>43</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>172826</td>\n",
+              "      <td>Some-college</td>\n",
+              "      <td>10</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Sales</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>55</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2318</th>\n",
+              "      <td>65</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>139272</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Sales</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2360</th>\n",
+              "      <td>26</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>256000</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2706</th>\n",
+              "      <td>52</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>64045</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>45</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3104</th>\n",
+              "      <td>46</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>176814</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3174</th>\n",
+              "      <td>36</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>208358</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Divorced</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Not-in-family</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>45</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3367</th>\n",
+              "      <td>40</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>223881</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>70</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3835</th>\n",
+              "      <td>52</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>90363</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>35</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4388</th>\n",
+              "      <td>32</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>46807</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Craft-repair</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4420</th>\n",
+              "      <td>53</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>88842</td>\n",
+              "      <td>HS-grad</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4624</th>\n",
+              "      <td>47</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>345493</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>Asian-Pac-Islander</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>55</td>\n",
+              "      <td>Taiwan</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4655</th>\n",
+              "      <td>37</td>\n",
+              "      <td>Local-gov</td>\n",
+              "      <td>287306</td>\n",
+              "      <td>Assoc-acdm</td>\n",
+              "      <td>12</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Wife</td>\n",
+              "      <td>Black</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>?</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4897</th>\n",
+              "      <td>37</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>362062</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5097</th>\n",
+              "      <td>39</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>114844</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>65</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5183</th>\n",
+              "      <td>38</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>146091</td>\n",
+              "      <td>Doctorate</td>\n",
+              "      <td>16</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Wife</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5472</th>\n",
+              "      <td>44</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>332401</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>65</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5587</th>\n",
+              "      <td>57</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>159028</td>\n",
+              "      <td>Prof-school</td>\n",
+              "      <td>15</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Husband</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6001</th>\n",
+              "      <td>51</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>44000</td>\n",
+              "      <td>Masters</td>\n",
+              "      <td>14</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Wife</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>50</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6034</th>\n",
+              "      <td>78</td>\n",
+              "      <td>Self-emp-not-inc</td>\n",
+              "      <td>316261</td>\n",
+              "      <td>Bachelors</td>\n",
+              "      <td>13</td>\n",
+              "      <td>Never-married</td>\n",
+              "      <td>Exec-managerial</td>\n",
+              "      <td>Not-in-family</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>20</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6224</th>\n",
+              "      <td>36</td>\n",
+              "      <td>Private</td>\n",
+              "      <td>383518</td>\n",
+              "      <td>Some-college</td>\n",
+              "      <td>10</td>\n",
+              "      <td>Married-civ-spouse</td>\n",
+              "      <td>Adm-clerical</td>\n",
+              "      <td>Wife</td>\n",
+              "      <td>Black</td>\n",
+              "      <td>Female</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>40</td>\n",
+              "      <td>United-States</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6523</th>\n",
+              "      <td>49</td>\n",
+              "      <td>Self-emp-inc</td>\n",
+              "      <td>362795</td>\n",
+              "      <td>Masters</td>\n",
+              "      <td>14</td>\n",
+              "      <td>Divorced</td>\n",
+              "      <td>Prof-specialty</td>\n",
+              "      <td>Unmarried</td>\n",
+              "      <td>White</td>\n",
+              "      <td>Male</td>\n",
+              "      <td>99999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>80</td>\n",
+              "      <td>Mexico</td>\n",
+              "      <td>&gt;50K</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "      age          workclass  fnlwgt  ... hours_per_wk       native_country income\n",
+              "1245   54       Self-emp-inc  166459  ...           60        United-States   >50K\n",
+              "1367   52            Private  152234  ...           40                Japan   >50K\n",
+              "1481   53       Self-emp-inc  263925  ...           40        United-States   >50K\n",
+              "1527   52            Private  118025  ...           50        United-States   >50K\n",
+              "1615   46            Private  370119  ...           60        United-States   >50K\n",
+              "1681   43            Private  176270  ...           60        United-States   >50K\n",
+              "1764   49            Private  159816  ...           20        United-States   >50K\n",
+              "1770   50            Private  171338  ...           50        United-States   >50K\n",
+              "1825   22   Self-emp-not-inc  202920  ...           40   Dominican-Republic   >50K\n",
+              "2102   43       Self-emp-inc  172826  ...           55        United-States   >50K\n",
+              "2318   65       Self-emp-inc  139272  ...           60        United-States   >50K\n",
+              "2360   26            Private  256000  ...           60        United-States   >50K\n",
+              "2706   52   Self-emp-not-inc   64045  ...           45        United-States   >50K\n",
+              "3104   46            Private  176814  ...           50        United-States   >50K\n",
+              "3174   36            Private  208358  ...           45        United-States   >50K\n",
+              "3367   40   Self-emp-not-inc  223881  ...           70        United-States   >50K\n",
+              "3835   52       Self-emp-inc   90363  ...           35        United-States   >50K\n",
+              "4388   32       Self-emp-inc   46807  ...           40        United-States   >50K\n",
+              "4420   53            Private   88842  ...           40        United-States   >50K\n",
+              "4624   47            Private  345493  ...           55               Taiwan   >50K\n",
+              "4655   37          Local-gov  287306  ...           40                    ?   >50K\n",
+              "4897   37   Self-emp-not-inc  362062  ...           50        United-States   >50K\n",
+              "5097   39       Self-emp-inc  114844  ...           65        United-States   >50K\n",
+              "5183   38            Private  146091  ...           36        United-States   >50K\n",
+              "5472   44            Private  332401  ...           65        United-States   >50K\n",
+              "5587   57       Self-emp-inc  159028  ...           60        United-States   >50K\n",
+              "6001   51            Private   44000  ...           50        United-States   >50K\n",
+              "6034   78   Self-emp-not-inc  316261  ...           20        United-States   >50K\n",
+              "6224   36            Private  383518  ...           40        United-States   >50K\n",
+              "6523   49       Self-emp-inc  362795  ...           80               Mexico   >50K\n",
+              "\n",
+              "[30 rows x 15 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 77
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "WoHGaay6daIH",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "372db664-209b-45fb-dba1-26eb78959283"
+      },
+      "source": [
+        "# ...and peek at the median education level.\n",
+        "is_gains['education_num'].median()"
+      ],
+      "execution_count": 79,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "13.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 79
+        }
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -448,13 +1768,19 @@
         "\n",
         "1.  Describe in a paragraph of text what you did and why, as if you were writing an email to somebody interested but nontechnical.\n",
         "\n",
+        "I did a few things, treating the basic tools as a sort of visualization toy. First I generated 1000 random x and y values and plotted them. Then I generated a Fibonacci sequence (i.e. 0,1,1,2,3,5,8,13,21,etc.) and plotted it. Then I imported a set of data pertaining to people's occupations and income, gathered some basic info about it, and started to clean it up.\n",
+        "\n",
         "2.  What was the most challenging part of what you did?\n",
         "\n",
+        "Uploading and importing the data was a brand new experience, but went fairly smoothly. I'm still very much learning the ins and outs of Pandas. For instance, I wasn't able to figure out how to add column headers instead of having my chosen headers replace the first existing row of data.\n",
+        "\n",
         "3.  What was the most interesting thing you learned?\n",
         "\n",
+        "That Google Colab seemingly has a robust and user-friendly interface for uploading and importing data!\n",
+        "\n",
         "4.  What area would you like to explore with more time?\n",
         "\n",
-        "\n"
+        "I'd like to spend more time poking at the data, and maybe play with it with scikit-learn."
       ]
     },
     {

From 435277b6d86f635a570a59e85727fed4e82fc8d7 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Fri, 6 Sep 2019 21:54:16 -0400
Subject: [PATCH 3/9] Created using Colaboratory

---
 .../LS_DS_112_Loading_Data_Assignment.ipynb   | 1052 ++++++++++++++++-
 1 file changed, 1044 insertions(+), 8 deletions(-)

diff --git a/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb b/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb
index 93f2cc5a..15d010a7 100644
--- a/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb
+++ b/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb
@@ -22,7 +22,7 @@
         "colab_type": "text"
       },
       "source": [
-        "<a href=\"https://colab.research.google.com/github/LambdaSchool/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+        "<a href=\"https://colab.research.google.com/github/b-whitman/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
@@ -53,6 +53,20 @@
         "<https://github.com/ryanleeallred/datasets>"
       ]
     },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "XwdDnjOKQXD8",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import pandas as pd\n",
+        "import matplotlib.pyplot as plt"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
     {
       "cell_type": "code",
       "metadata": {
@@ -61,13 +75,742 @@
         "colab": {}
       },
       "source": [
-        "# TODO your work here!\n",
-        "# And note you should write comments, descriptions, and add new\n",
-        "# code and text blocks as needed"
+        "# Load housing dataset from URL\n",
+        "dataset_url = 'https://raw.githubusercontent.com/ryanleeallred/datasets/master/Ames%20Housing%20Data/train.csv'\n",
+        "\n",
+        "df = pd.read_csv(dataset_url)"
       ],
       "execution_count": 0,
       "outputs": []
     },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "jZlaoBS2Qo6j",
+        "colab_type": "code",
+        "outputId": "ce2de272-1bef-446a-d3ce-0e5c4a7ff9fd",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 251
+        }
+      },
+      "source": [
+        "# Get eyeballs on the data\n",
+        "df.head()"
+      ],
+      "execution_count": 0,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Id</th>\n",
+              "      <th>MSSubClass</th>\n",
+              "      <th>MSZoning</th>\n",
+              "      <th>LotFrontage</th>\n",
+              "      <th>LotArea</th>\n",
+              "      <th>Street</th>\n",
+              "      <th>Alley</th>\n",
+              "      <th>LotShape</th>\n",
+              "      <th>LandContour</th>\n",
+              "      <th>Utilities</th>\n",
+              "      <th>LotConfig</th>\n",
+              "      <th>LandSlope</th>\n",
+              "      <th>Neighborhood</th>\n",
+              "      <th>Condition1</th>\n",
+              "      <th>Condition2</th>\n",
+              "      <th>BldgType</th>\n",
+              "      <th>HouseStyle</th>\n",
+              "      <th>OverallQual</th>\n",
+              "      <th>OverallCond</th>\n",
+              "      <th>YearBuilt</th>\n",
+              "      <th>YearRemodAdd</th>\n",
+              "      <th>RoofStyle</th>\n",
+              "      <th>RoofMatl</th>\n",
+              "      <th>Exterior1st</th>\n",
+              "      <th>Exterior2nd</th>\n",
+              "      <th>MasVnrType</th>\n",
+              "      <th>MasVnrArea</th>\n",
+              "      <th>ExterQual</th>\n",
+              "      <th>ExterCond</th>\n",
+              "      <th>Foundation</th>\n",
+              "      <th>BsmtQual</th>\n",
+              "      <th>BsmtCond</th>\n",
+              "      <th>BsmtExposure</th>\n",
+              "      <th>BsmtFinType1</th>\n",
+              "      <th>BsmtFinSF1</th>\n",
+              "      <th>BsmtFinType2</th>\n",
+              "      <th>BsmtFinSF2</th>\n",
+              "      <th>BsmtUnfSF</th>\n",
+              "      <th>TotalBsmtSF</th>\n",
+              "      <th>Heating</th>\n",
+              "      <th>...</th>\n",
+              "      <th>CentralAir</th>\n",
+              "      <th>Electrical</th>\n",
+              "      <th>1stFlrSF</th>\n",
+              "      <th>2ndFlrSF</th>\n",
+              "      <th>LowQualFinSF</th>\n",
+              "      <th>GrLivArea</th>\n",
+              "      <th>BsmtFullBath</th>\n",
+              "      <th>BsmtHalfBath</th>\n",
+              "      <th>FullBath</th>\n",
+              "      <th>HalfBath</th>\n",
+              "      <th>BedroomAbvGr</th>\n",
+              "      <th>KitchenAbvGr</th>\n",
+              "      <th>KitchenQual</th>\n",
+              "      <th>TotRmsAbvGrd</th>\n",
+              "      <th>Functional</th>\n",
+              "      <th>Fireplaces</th>\n",
+              "      <th>FireplaceQu</th>\n",
+              "      <th>GarageType</th>\n",
+              "      <th>GarageYrBlt</th>\n",
+              "      <th>GarageFinish</th>\n",
+              "      <th>GarageCars</th>\n",
+              "      <th>GarageArea</th>\n",
+              "      <th>GarageQual</th>\n",
+              "      <th>GarageCond</th>\n",
+              "      <th>PavedDrive</th>\n",
+              "      <th>WoodDeckSF</th>\n",
+              "      <th>OpenPorchSF</th>\n",
+              "      <th>EnclosedPorch</th>\n",
+              "      <th>3SsnPorch</th>\n",
+              "      <th>ScreenPorch</th>\n",
+              "      <th>PoolArea</th>\n",
+              "      <th>PoolQC</th>\n",
+              "      <th>Fence</th>\n",
+              "      <th>MiscFeature</th>\n",
+              "      <th>MiscVal</th>\n",
+              "      <th>MoSold</th>\n",
+              "      <th>YrSold</th>\n",
+              "      <th>SaleType</th>\n",
+              "      <th>SaleCondition</th>\n",
+              "      <th>SalePrice</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1</td>\n",
+              "      <td>60</td>\n",
+              "      <td>RL</td>\n",
+              "      <td>65.0</td>\n",
+              "      <td>8450</td>\n",
+              "      <td>Pave</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Reg</td>\n",
+              "      <td>Lvl</td>\n",
+              "      <td>AllPub</td>\n",
+              "      <td>Inside</td>\n",
+              "      <td>Gtl</td>\n",
+              "      <td>CollgCr</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>1Fam</td>\n",
+              "      <td>2Story</td>\n",
+              "      <td>7</td>\n",
+              "      <td>5</td>\n",
+              "      <td>2003</td>\n",
+              "      <td>2003</td>\n",
+              "      <td>Gable</td>\n",
+              "      <td>CompShg</td>\n",
+              "      <td>VinylSd</td>\n",
+              "      <td>VinylSd</td>\n",
+              "      <td>BrkFace</td>\n",
+              "      <td>196.0</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>PConc</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>No</td>\n",
+              "      <td>GLQ</td>\n",
+              "      <td>706</td>\n",
+              "      <td>Unf</td>\n",
+              "      <td>0</td>\n",
+              "      <td>150</td>\n",
+              "      <td>856</td>\n",
+              "      <td>GasA</td>\n",
+              "      <td>...</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>SBrkr</td>\n",
+              "      <td>856</td>\n",
+              "      <td>854</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1710</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>8</td>\n",
+              "      <td>Typ</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Attchd</td>\n",
+              "      <td>2003.0</td>\n",
+              "      <td>RFn</td>\n",
+              "      <td>2</td>\n",
+              "      <td>548</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>0</td>\n",
+              "      <td>61</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2008</td>\n",
+              "      <td>WD</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>208500</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2</td>\n",
+              "      <td>20</td>\n",
+              "      <td>RL</td>\n",
+              "      <td>80.0</td>\n",
+              "      <td>9600</td>\n",
+              "      <td>Pave</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>Reg</td>\n",
+              "      <td>Lvl</td>\n",
+              "      <td>AllPub</td>\n",
+              "      <td>FR2</td>\n",
+              "      <td>Gtl</td>\n",
+              "      <td>Veenker</td>\n",
+              "      <td>Feedr</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>1Fam</td>\n",
+              "      <td>1Story</td>\n",
+              "      <td>6</td>\n",
+              "      <td>8</td>\n",
+              "      <td>1976</td>\n",
+              "      <td>1976</td>\n",
+              "      <td>Gable</td>\n",
+              "      <td>CompShg</td>\n",
+              "      <td>MetalSd</td>\n",
+              "      <td>MetalSd</td>\n",
+              "      <td>None</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>CBlock</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>ALQ</td>\n",
+              "      <td>978</td>\n",
+              "      <td>Unf</td>\n",
+              "      <td>0</td>\n",
+              "      <td>284</td>\n",
+              "      <td>1262</td>\n",
+              "      <td>GasA</td>\n",
+              "      <td>...</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>SBrkr</td>\n",
+              "      <td>1262</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1262</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>6</td>\n",
+              "      <td>Typ</td>\n",
+              "      <td>1</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Attchd</td>\n",
+              "      <td>1976.0</td>\n",
+              "      <td>RFn</td>\n",
+              "      <td>2</td>\n",
+              "      <td>460</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>298</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0</td>\n",
+              "      <td>5</td>\n",
+              "      <td>2007</td>\n",
+              "      <td>WD</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>181500</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>3</td>\n",
+              "      <td>60</td>\n",
+              "      <td>RL</td>\n",
+              "      <td>68.0</td>\n",
+              "      <td>11250</td>\n",
+              "      <td>Pave</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>IR1</td>\n",
+              "      <td>Lvl</td>\n",
+              "      <td>AllPub</td>\n",
+              "      <td>Inside</td>\n",
+              "      <td>Gtl</td>\n",
+              "      <td>CollgCr</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>1Fam</td>\n",
+              "      <td>2Story</td>\n",
+              "      <td>7</td>\n",
+              "      <td>5</td>\n",
+              "      <td>2001</td>\n",
+              "      <td>2002</td>\n",
+              "      <td>Gable</td>\n",
+              "      <td>CompShg</td>\n",
+              "      <td>VinylSd</td>\n",
+              "      <td>VinylSd</td>\n",
+              "      <td>BrkFace</td>\n",
+              "      <td>162.0</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>PConc</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Mn</td>\n",
+              "      <td>GLQ</td>\n",
+              "      <td>486</td>\n",
+              "      <td>Unf</td>\n",
+              "      <td>0</td>\n",
+              "      <td>434</td>\n",
+              "      <td>920</td>\n",
+              "      <td>GasA</td>\n",
+              "      <td>...</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>SBrkr</td>\n",
+              "      <td>920</td>\n",
+              "      <td>866</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1786</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>6</td>\n",
+              "      <td>Typ</td>\n",
+              "      <td>1</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Attchd</td>\n",
+              "      <td>2001.0</td>\n",
+              "      <td>RFn</td>\n",
+              "      <td>2</td>\n",
+              "      <td>608</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>0</td>\n",
+              "      <td>42</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0</td>\n",
+              "      <td>9</td>\n",
+              "      <td>2008</td>\n",
+              "      <td>WD</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>223500</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>4</td>\n",
+              "      <td>70</td>\n",
+              "      <td>RL</td>\n",
+              "      <td>60.0</td>\n",
+              "      <td>9550</td>\n",
+              "      <td>Pave</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>IR1</td>\n",
+              "      <td>Lvl</td>\n",
+              "      <td>AllPub</td>\n",
+              "      <td>Corner</td>\n",
+              "      <td>Gtl</td>\n",
+              "      <td>Crawfor</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>1Fam</td>\n",
+              "      <td>2Story</td>\n",
+              "      <td>7</td>\n",
+              "      <td>5</td>\n",
+              "      <td>1915</td>\n",
+              "      <td>1970</td>\n",
+              "      <td>Gable</td>\n",
+              "      <td>CompShg</td>\n",
+              "      <td>Wd Sdng</td>\n",
+              "      <td>Wd Shng</td>\n",
+              "      <td>None</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>BrkTil</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>No</td>\n",
+              "      <td>ALQ</td>\n",
+              "      <td>216</td>\n",
+              "      <td>Unf</td>\n",
+              "      <td>0</td>\n",
+              "      <td>540</td>\n",
+              "      <td>756</td>\n",
+              "      <td>GasA</td>\n",
+              "      <td>...</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>SBrkr</td>\n",
+              "      <td>961</td>\n",
+              "      <td>756</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1717</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>7</td>\n",
+              "      <td>Typ</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>Detchd</td>\n",
+              "      <td>1998.0</td>\n",
+              "      <td>Unf</td>\n",
+              "      <td>3</td>\n",
+              "      <td>642</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>0</td>\n",
+              "      <td>35</td>\n",
+              "      <td>272</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2006</td>\n",
+              "      <td>WD</td>\n",
+              "      <td>Abnorml</td>\n",
+              "      <td>140000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>5</td>\n",
+              "      <td>60</td>\n",
+              "      <td>RL</td>\n",
+              "      <td>84.0</td>\n",
+              "      <td>14260</td>\n",
+              "      <td>Pave</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>IR1</td>\n",
+              "      <td>Lvl</td>\n",
+              "      <td>AllPub</td>\n",
+              "      <td>FR2</td>\n",
+              "      <td>Gtl</td>\n",
+              "      <td>NoRidge</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>Norm</td>\n",
+              "      <td>1Fam</td>\n",
+              "      <td>2Story</td>\n",
+              "      <td>8</td>\n",
+              "      <td>5</td>\n",
+              "      <td>2000</td>\n",
+              "      <td>2000</td>\n",
+              "      <td>Gable</td>\n",
+              "      <td>CompShg</td>\n",
+              "      <td>VinylSd</td>\n",
+              "      <td>VinylSd</td>\n",
+              "      <td>BrkFace</td>\n",
+              "      <td>350.0</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>PConc</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Av</td>\n",
+              "      <td>GLQ</td>\n",
+              "      <td>655</td>\n",
+              "      <td>Unf</td>\n",
+              "      <td>0</td>\n",
+              "      <td>490</td>\n",
+              "      <td>1145</td>\n",
+              "      <td>GasA</td>\n",
+              "      <td>...</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>SBrkr</td>\n",
+              "      <td>1145</td>\n",
+              "      <td>1053</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2198</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Gd</td>\n",
+              "      <td>9</td>\n",
+              "      <td>Typ</td>\n",
+              "      <td>1</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Attchd</td>\n",
+              "      <td>2000.0</td>\n",
+              "      <td>RFn</td>\n",
+              "      <td>3</td>\n",
+              "      <td>836</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>TA</td>\n",
+              "      <td>Y</td>\n",
+              "      <td>192</td>\n",
+              "      <td>84</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>0</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2008</td>\n",
+              "      <td>WD</td>\n",
+              "      <td>Normal</td>\n",
+              "      <td>250000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 81 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   Id  MSSubClass MSZoning  ...  SaleType  SaleCondition SalePrice\n",
+              "0   1          60       RL  ...        WD         Normal    208500\n",
+              "1   2          20       RL  ...        WD         Normal    181500\n",
+              "2   3          60       RL  ...        WD         Normal    223500\n",
+              "3   4          70       RL  ...        WD        Abnorml    140000\n",
+              "4   5          60       RL  ...        WD         Normal    250000\n",
+              "\n",
+              "[5 rows x 81 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 29
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "N_6-vERtRxKK",
+        "colab_type": "code",
+        "outputId": "1ca9ec49-f966-4804-9a8e-e9e2e4e31e92",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        }
+      },
+      "source": [
+        "df.shape"
+      ],
+      "execution_count": 0,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(1460, 81)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 30
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "XBxXZcY8Q-3h",
+        "colab_type": "code",
+        "outputId": "e16a9a98-20bf-4ee1-bec1-ee93b01c8fe0",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        }
+      },
+      "source": [
+        "df.isna().sum()\n",
+        "# Looks like NaN stands in for \"0\" or \"Not Applicable\""
+      ],
+      "execution_count": 0,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Id                  0\n",
+              "MSSubClass          0\n",
+              "MSZoning            0\n",
+              "LotFrontage       259\n",
+              "LotArea             0\n",
+              "Street              0\n",
+              "Alley            1369\n",
+              "LotShape            0\n",
+              "LandContour         0\n",
+              "Utilities           0\n",
+              "LotConfig           0\n",
+              "LandSlope           0\n",
+              "Neighborhood        0\n",
+              "Condition1          0\n",
+              "Condition2          0\n",
+              "BldgType            0\n",
+              "HouseStyle          0\n",
+              "OverallQual         0\n",
+              "OverallCond         0\n",
+              "YearBuilt           0\n",
+              "YearRemodAdd        0\n",
+              "RoofStyle           0\n",
+              "RoofMatl            0\n",
+              "Exterior1st         0\n",
+              "Exterior2nd         0\n",
+              "MasVnrType          8\n",
+              "MasVnrArea          8\n",
+              "ExterQual           0\n",
+              "ExterCond           0\n",
+              "Foundation          0\n",
+              "                 ... \n",
+              "BedroomAbvGr        0\n",
+              "KitchenAbvGr        0\n",
+              "KitchenQual         0\n",
+              "TotRmsAbvGrd        0\n",
+              "Functional          0\n",
+              "Fireplaces          0\n",
+              "FireplaceQu       690\n",
+              "GarageType         81\n",
+              "GarageYrBlt        81\n",
+              "GarageFinish       81\n",
+              "GarageCars          0\n",
+              "GarageArea          0\n",
+              "GarageQual         81\n",
+              "GarageCond         81\n",
+              "PavedDrive          0\n",
+              "WoodDeckSF          0\n",
+              "OpenPorchSF         0\n",
+              "EnclosedPorch       0\n",
+              "3SsnPorch           0\n",
+              "ScreenPorch         0\n",
+              "PoolArea            0\n",
+              "PoolQC           1453\n",
+              "Fence            1179\n",
+              "MiscFeature      1406\n",
+              "MiscVal             0\n",
+              "MoSold              0\n",
+              "YrSold              0\n",
+              "SaleType            0\n",
+              "SaleCondition       0\n",
+              "SalePrice           0\n",
+              "Length: 81, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 31
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "tF7Gz5z4Tq9o",
+        "colab_type": "code",
+        "outputId": "6cd560f4-bb29-4076-abd9-f4fb9c165fcc",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 173
+        }
+      },
+      "source": [
+        "# Testing hypothesis about the NaN values- looks like LotFrontage mins out at 21.\n",
+        "# Can I assume that \"NaN\" just means \"0\" in this case? Other cases?\n",
+        "df['LotFrontage'].describe()"
+      ],
+      "execution_count": 0,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "count    1201.000000\n",
+              "mean       70.049958\n",
+              "std        24.284752\n",
+              "min        21.000000\n",
+              "25%        59.000000\n",
+              "50%        69.000000\n",
+              "75%        80.000000\n",
+              "max       313.000000\n",
+              "Name: LotFrontage, dtype: float64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 32
+        }
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -85,6 +828,20 @@
         "- Make sure that your file has correct headers, and the same number of rows and columns as is specified on the UCI page. If your dataset doesn't have headers use the parameters of the `read_csv` function to add them. Likewise make sure that missing values are encoded as `NaN`."
       ]
     },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "DoqBcmxrWsFH",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# name the columns, per description on UCI ML Repo\n",
+        "columns_car = ['buying', 'maint', 'doors', 'persons', 'lug_boot', 'safety', 'acceptability']"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
     {
       "cell_type": "code",
       "metadata": {
@@ -93,13 +850,292 @@
         "colab": {}
       },
       "source": [
-        "# TODO your work here!\n",
-        "# And note you should write comments, descriptions, and add new\n",
-        "# code and text blocks as needed"
+        "# read car.csv and name columns appropriately\n",
+        "df2 = pd.read_csv('car.csv', names=columns_car)"
       ],
       "execution_count": 0,
       "outputs": []
     },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "kQ2TCqfQX7YF",
+        "colab_type": "code",
+        "outputId": "b1883c8c-0e7b-4301-ba87-95f3b6e71577",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 355
+        }
+      },
+      "source": [
+        "# take a quick look\n",
+        "df2.sample(10)"
+      ],
+      "execution_count": 0,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>buying</th>\n",
+              "      <th>maint</th>\n",
+              "      <th>doors</th>\n",
+              "      <th>persons</th>\n",
+              "      <th>lug_boot</th>\n",
+              "      <th>safety</th>\n",
+              "      <th>acceptability</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1671</th>\n",
+              "      <td>low</td>\n",
+              "      <td>low</td>\n",
+              "      <td>3</td>\n",
+              "      <td>more</td>\n",
+              "      <td>big</td>\n",
+              "      <td>low</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>258</th>\n",
+              "      <td>vhigh</td>\n",
+              "      <td>med</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>big</td>\n",
+              "      <td>low</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>227</th>\n",
+              "      <td>vhigh</td>\n",
+              "      <td>med</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>small</td>\n",
+              "      <td>high</td>\n",
+              "      <td>acc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>160</th>\n",
+              "      <td>vhigh</td>\n",
+              "      <td>high</td>\n",
+              "      <td>3</td>\n",
+              "      <td>more</td>\n",
+              "      <td>big</td>\n",
+              "      <td>med</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1665</th>\n",
+              "      <td>low</td>\n",
+              "      <td>low</td>\n",
+              "      <td>3</td>\n",
+              "      <td>more</td>\n",
+              "      <td>small</td>\n",
+              "      <td>low</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1341</th>\n",
+              "      <td>low</td>\n",
+              "      <td>vhigh</td>\n",
+              "      <td>3</td>\n",
+              "      <td>more</td>\n",
+              "      <td>small</td>\n",
+              "      <td>low</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>447</th>\n",
+              "      <td>high</td>\n",
+              "      <td>vhigh</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>big</td>\n",
+              "      <td>low</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1203</th>\n",
+              "      <td>med</td>\n",
+              "      <td>low</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>big</td>\n",
+              "      <td>low</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>364</th>\n",
+              "      <td>vhigh</td>\n",
+              "      <td>low</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>med</td>\n",
+              "      <td>med</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1725</th>\n",
+              "      <td>low</td>\n",
+              "      <td>low</td>\n",
+              "      <td>5more</td>\n",
+              "      <td>more</td>\n",
+              "      <td>big</td>\n",
+              "      <td>low</td>\n",
+              "      <td>unacc</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "     buying  maint  doors persons lug_boot safety acceptability\n",
+              "1671    low    low      3    more      big    low         unacc\n",
+              "258   vhigh    med      3       4      big    low         unacc\n",
+              "227   vhigh    med      2       4    small   high           acc\n",
+              "160   vhigh   high      3    more      big    med         unacc\n",
+              "1665    low    low      3    more    small    low         unacc\n",
+              "1341    low  vhigh      3    more    small    low         unacc\n",
+              "447    high  vhigh      2       4      big    low         unacc\n",
+              "1203    med    low      2       4      big    low         unacc\n",
+              "364   vhigh    low      3       4      med    med         unacc\n",
+              "1725    low    low  5more    more      big    low         unacc"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 37
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "zkas1-pZYXFf",
+        "colab_type": "code",
+        "outputId": "9b6e7dc8-29a7-43f3-f276-b57391089f00",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        }
+      },
+      "source": [
+        "# shape matches description on UCI ML Repo\n",
+        "df2.shape"
+      ],
+      "execution_count": 0,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(1728, 7)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 38
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "8P38ndnuY1xc",
+        "colab_type": "code",
+        "outputId": "dae4e7d5-61a2-452d-ee92-afcf3a6eaf40",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 156
+        }
+      },
+      "source": [
+        "# dataset contains no null values, which also matches description\n",
+        "df2.isna().sum()"
+      ],
+      "execution_count": 0,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "buying           0\n",
+              "maint            0\n",
+              "doors            0\n",
+              "persons          0\n",
+              "lug_boot         0\n",
+              "safety           0\n",
+              "acceptability    0\n",
+              "dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 39
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "xfofM-9fY_8M",
+        "colab_type": "code",
+        "outputId": "26637964-c492-4035-cf7b-2f6ed551ebe3",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 87
+        }
+      },
+      "source": [
+        "# Checked each column for any values that look unusual.\n",
+        "# Interestingly, it looks like most column's values are evenly distributed.\n",
+        "# i.e., for size of trunk, there's the same number (576) of S, M, and L trunks\n",
+        "# \"acceptability\" works a little differently\n",
+        "df2['lug_boot'].value_counts()"
+      ],
+      "execution_count": 66,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "med      576\n",
+              "small    576\n",
+              "big      576\n",
+              "Name: lug_boot, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 66
+        }
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -160,4 +1196,4 @@
       "outputs": []
     }
   ]
-}
+}
\ No newline at end of file

From 4cb450249b51076f80ac7129baf943ed112f57f0 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Fri, 6 Sep 2019 22:27:12 -0400
Subject: [PATCH 4/9] Created using Colaboratory

---
 .../LS_DS_112_Loading_Data_Assignment.ipynb   | 369 ++++++++++++++++++
 1 file changed, 369 insertions(+)

diff --git a/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb b/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb
index 15d010a7..9768fa6b 100644
--- a/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb
+++ b/module2-loadingdata/LS_DS_112_Loading_Data_Assignment.ipynb
@@ -7,6 +7,7 @@
       "version": "0.3.2",
       "provenance": [],
       "collapsed_sections": [],
+      "toc_visible": true,
       "include_colab_link": true
     },
     "kernelspec": {
@@ -1158,6 +1159,374 @@
         " - Density Plot\n"
       ]
     },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "vWt3E9p6cn7x",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 228
+        },
+        "outputId": "c1b90490-7b18-4360-ad62-569daa4c7c20"
+      },
+      "source": [
+        "# get the file\n",
+        "!wget 'https://archive.ics.uci.edu/ml/machine-learning-databases/poker/poker-hand-training-true.data'"
+      ],
+      "execution_count": 69,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "--2019-09-07 02:06:42--  https://archive.ics.uci.edu/ml/machine-learning-databases/poker/poker-hand-training-true.data\n",
+            "Resolving archive.ics.uci.edu (archive.ics.uci.edu)... 128.195.10.252\n",
+            "Connecting to archive.ics.uci.edu (archive.ics.uci.edu)|128.195.10.252|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 613694 (599K) [application/x-httpd-php]\n",
+            "Saving to: ‘poker-hand-training-true.data’\n",
+            "\n",
+            "poker-hand-training 100%[===================>] 599.31K  1.63MB/s    in 0.4s    \n",
+            "\n",
+            "2019-09-07 02:06:42 (1.63 MB/s) - ‘poker-hand-training-true.data’ saved [613694/613694]\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "zJDW-UAzeJSW",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# label the columns\n",
+        "columns_cards = ['card_1_suit','card_1_rank','card_2_suit','card_2_rank','card_3_suit','card_3_rank',\n",
+        "                'card_4_suit','card_4_rank','card_5_suit','card_5_rank','poker_hand']"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "KpNjZzkHe-yb",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 222
+        },
+        "outputId": "736161d4-59a0-4ac4-8718-e13b101b2d8b"
+      },
+      "source": [
+        "# read in the file - no missing values.\n",
+        "df3 = pd.read_csv('poker-hand-training-true.data', names=columns_cards)\n",
+        "df3.head()"
+      ],
+      "execution_count": 77,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>card_1_suit</th>\n",
+              "      <th>card_1_rank</th>\n",
+              "      <th>card_2_suit</th>\n",
+              "      <th>card_2_rank</th>\n",
+              "      <th>card_3_suit</th>\n",
+              "      <th>card_3_rank</th>\n",
+              "      <th>card_4_suit</th>\n",
+              "      <th>card_4_rank</th>\n",
+              "      <th>card_5_suit</th>\n",
+              "      <th>card_5_rank</th>\n",
+              "      <th>poker_hand</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1</td>\n",
+              "      <td>10</td>\n",
+              "      <td>1</td>\n",
+              "      <td>11</td>\n",
+              "      <td>1</td>\n",
+              "      <td>13</td>\n",
+              "      <td>1</td>\n",
+              "      <td>12</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>9</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2</td>\n",
+              "      <td>11</td>\n",
+              "      <td>2</td>\n",
+              "      <td>13</td>\n",
+              "      <td>2</td>\n",
+              "      <td>10</td>\n",
+              "      <td>2</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>9</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>3</td>\n",
+              "      <td>12</td>\n",
+              "      <td>3</td>\n",
+              "      <td>11</td>\n",
+              "      <td>3</td>\n",
+              "      <td>13</td>\n",
+              "      <td>3</td>\n",
+              "      <td>10</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>9</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>4</td>\n",
+              "      <td>10</td>\n",
+              "      <td>4</td>\n",
+              "      <td>11</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>13</td>\n",
+              "      <td>4</td>\n",
+              "      <td>12</td>\n",
+              "      <td>9</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>13</td>\n",
+              "      <td>4</td>\n",
+              "      <td>12</td>\n",
+              "      <td>4</td>\n",
+              "      <td>11</td>\n",
+              "      <td>4</td>\n",
+              "      <td>10</td>\n",
+              "      <td>9</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   card_1_suit  card_1_rank  card_2_suit  ...  card_5_suit  card_5_rank  poker_hand\n",
+              "0            1           10            1  ...            1            1           9\n",
+              "1            2           11            2  ...            2            1           9\n",
+              "2            3           12            3  ...            3            1           9\n",
+              "3            4           10            4  ...            4           12           9\n",
+              "4            4            1            4  ...            4           10           9\n",
+              "\n",
+              "[5 rows x 11 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 77
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "bFXTaT4IhGTP",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 302
+        },
+        "outputId": "8d0c7b05-e930-4974-9175-a1f11cd2bbad"
+      },
+      "source": [
+        "df3.plot.scatter('card_1_rank','poker_hand')"
+      ],
+      "execution_count": 79,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7fba4ab55e48>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 79
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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/v/7hQDfwOXd/tXBflsvJ3wL53cCP3P26415rLPlfNl9391UDFhepgAJfGo6Z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\nvrgAAAAASUVORK5CYII=\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "4DRac2oyiBEr",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "392ed770-1fff-489d-e167-95a65451cb96"
+      },
+      "source": [
+        "# interesting case where number of bins makes a huge difference\n",
+        "df3['card_2_rank'].hist(bins=13)"
+      ],
+      "execution_count": 81,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7fba497b47f0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 81
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYEAAAD8CAYAAACRkhiPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "KubbY8giidWi",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "b0c5c72f-1ecb-4559-fcef-751fb07fe21c"
+      },
+      "source": [
+        "# with the default 10 bins, the histogram is deceptive.\n",
+        "# Matching number of bins to number of possible ranks makes things more clear.\n",
+        "df3['card_2_rank'].hist()"
+      ],
+      "execution_count": 82,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7fba51b1c940>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 82
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "zImd4awbiz9g",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "8614650c-6615-4b49-be81-00e214e5d6e0"
+      },
+      "source": [
+        "df3['poker_hand'].plot.density()"
+      ],
+      "execution_count": 83,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7fba49785ac8>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 83
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {

From adcf4db5cdc3ba980cc7adb83141b82f5d019fa1 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Tue, 10 Sep 2019 23:23:14 -0400
Subject: [PATCH 5/9] Created using Colaboratory

---
 ...ng_Data_backed_Assertions_Assignment.ipynb | 1080 +++++++++++++++++
 1 file changed, 1080 insertions(+)
 create mode 100644 module3-databackedassertions/Benjamin_Whitman_LS_DS_113_Making_Data_backed_Assertions_Assignment.ipynb

diff --git a/module3-databackedassertions/Benjamin_Whitman_LS_DS_113_Making_Data_backed_Assertions_Assignment.ipynb b/module3-databackedassertions/Benjamin_Whitman_LS_DS_113_Making_Data_backed_Assertions_Assignment.ipynb
new file mode 100644
index 00000000..5de9dfc1
--- /dev/null
+++ b/module3-databackedassertions/Benjamin_Whitman_LS_DS_113_Making_Data_backed_Assertions_Assignment.ipynb
@@ -0,0 +1,1080 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Benjamin Whitman - LS_DS_113_Making_Data_backed_Assertions_Assignment.ipynb",
+      "version": "0.3.2",
+      "provenance": [],
+      "collapsed_sections": [],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/b-whitman/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module3-databackedassertions/Benjamin_Whitman_LS_DS_113_Making_Data_backed_Assertions_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Okfr_uhwhS1X",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Lambda School Data Science - Making Data-backed Assertions\n",
+        "\n",
+        "This is, for many, the main point of data science - to create and support reasoned arguments based on evidence. It's not a topic to master in a day, but it is worth some focused time thinking about and structuring your approach to it."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lOqaPds9huME",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Assignment - what's going on here?\n",
+        "\n",
+        "Consider the data in `persons.csv` (already prepared for you, in the repo for the week). It has four columns - a unique id, followed by age (in years), weight (in lbs), and exercise time (in minutes/week) of 1200 (hypothetical) people.\n",
+        "\n",
+        "Try to figure out which variables are possibly related to each other, and which may be confounding relationships.\n",
+        "\n",
+        "Try and isolate the main relationships and then communicate them using crosstabs and graphs. Share any cool graphs that you make with the rest of the class in Slack!"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "TGUS79cOhPWj",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import pandas as pd\n",
+        "import matplotlib.pyplot as plt"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "csiVUIjb4VBj",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "pd.read_csv?"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "DBsW8j013jK9",
+        "colab_type": "code",
+        "outputId": "1d7989bc-4166-424c-bd9c-b8e66b9c5791",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 202
+        }
+      },
+      "source": [
+        "# Read persons.csv, and fix headers\n",
+        "df = pd.read_csv('https://raw.githubusercontent.com/LambdaSchool/DS-Unit-1-Sprint-1-Dealing-With-Data/master/module3-databackedassertions/persons.csv', index_col=0)\n",
+        "df.head()"
+      ],
+      "execution_count": 34,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>age</th>\n",
+              "      <th>weight</th>\n",
+              "      <th>exercise_time</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>44</td>\n",
+              "      <td>118</td>\n",
+              "      <td>192</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>41</td>\n",
+              "      <td>161</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>46</td>\n",
+              "      <td>128</td>\n",
+              "      <td>220</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>39</td>\n",
+              "      <td>216</td>\n",
+              "      <td>57</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>28</td>\n",
+              "      <td>116</td>\n",
+              "      <td>182</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   age  weight  exercise_time\n",
+              "0   44     118            192\n",
+              "1   41     161             35\n",
+              "2   46     128            220\n",
+              "3   39     216             57\n",
+              "4   28     116            182"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 34
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "1NJiguDxQwNh",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "plt.scatter?"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "HS6J2nk7PXfK",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "91acac2b-ec33-4f19-8598-ad2a1439959a"
+      },
+      "source": [
+        "time_weight_plot = plt.scatter(df['exercise_time'], df['weight'])\n",
+        "# This seems like a pretty clear relationship right off the bat!\n",
+        "# The more a person exercises, the less he or she weighs.\n",
+        "# TODO: Add axis labels"
+      ],
+      "execution_count": 86,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.PathCollection at 0x7f5736505b00>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 86
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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6fjt0Rx/ytL1IhHmlnJPJyO8+H1VrdniohFNnZp0G3IxjhK69TOBz9mEwK+D/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\nEOYAAAAASUVORK5CYII=\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "3t-p766DQS9b",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "cf5ac205-c5c0-4820-e1bd-5a1463c953dc"
+      },
+      "source": [
+        "plt.scatter(df['age'], df['exercise_time'])\n",
+        "# This also tells us about how the data is structured.\n",
+        "# People start exercising less around age 60, tapering off until nobody at age 80 exercises more than ~100 mins."
+      ],
+      "execution_count": 80,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.PathCollection at 0x7f5736728278>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 80
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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6iRaKlqiOgbKIyg25ht4Y8waAN5r//VMi+gGApQA+DOADzdO+CuBv0TD0Hwbw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\n/wPwcpXQ5++hQgAAAABJRU5ErkJggg==\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Np5FwPKnRL_B",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "bbf0c66c-303e-4d9b-ceea-0bbe71060ef7"
+      },
+      "source": [
+        "plt.scatter(df['age'], df['weight'])\n",
+        "# Curiously, there's a less distinct relationship between age and weight.\n",
+        "# There's a slight increase starting around 60, but nothing as stark as previous 2 graphs."
+      ],
+      "execution_count": 82,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.PathCollection at 0x7f5736701978>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 82
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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OTJOS4JI5ZHsXWsMp6Z3YmFV4SD6GuZ1SEVmhXYc2XK6Tz1oPw2U3o6UpuHxz\nblxaGtDuH2CPuSL0HXChXu2Xq4YuTCr6yhqgzgNdaejXr13Btr6zPQ6Wj1duIzsFg8LDaucluxo5\nTZGLhpP1gfah9slp1vyeL42UpnqqpTMkZK289lnrGifHl9+2rx1Hl0rgjHh4zNrYhrYWQksXFhGg\nzgNdmUcPQNWyRuL8zjxjXse1+pKw+bqVMV38WoWw+bporrZrkDiLFgmX5+yiZW9D09Up75zmPBs+\ncL+1fvso1j84Gjl2766DqnWo1UHn0I617sNvc9dux54x3Hj5kOqaSHrzAbRaMtpaCG3tjrYZSavr\nY7rSo9/6xIusmJRdKu6zjXRBkRkg0jYaiHrlnDdUqzS2r2nPolaLJBhPWlVptUIq+kbT19MlpxmI\nB4Xt++DL74fvNUcPcIZP7EtqrUOfDBuXEv281qsPvy3dh0dHD2PB/FNm6ZqLz2GTIuzMHk0PBGnu\nW2+6JDMlYx/XJoq0uj6mKw29tlRcgrY1meaBcMkAyfqApRnXsDdkN1UAdDrzGi0SaWz2OeysGwlp\nXhmgD55r74MPv2+fw7ehuCaLRboPdtrsQF8Vx6filIet1yMVQ4XPnwfSgsfaYPSOPWO4bHghdr1y\ndG6ulw0vZOew+/UjkfV/1YVLYn/nvnfZ8EL8ePwEDIAfj5/A7tcbiQPh+9A3r4KTM3FJ4oG+aNWu\nS+1CK+tjutLQuwRtOGhak2kNh9ZD9EkJtF8QE1Mz7Dmf/sFbqU0glm98XGyOnbVRN+c5rVs1NJfZ\n4+OpagPv2vvgU2znEvBOAxdTAnTc+J0790fqSGaNwfGp2dhOitPruXfXwcxqkPY6XCC8XDRaPy4F\nef/08pG5Mc8aE/l7+HPhazJ2bDL2d2nuXAqy/V0JE9b8tetr594x7NgzFqmP2bFnTF0f4wpNc/Cv\nEtGbRPTPoWOXEtGuZv/Y3UR0RfM4EdGXiOglInqBiC7LfcTg9TlcoKlu1XJyPvKtGs0SjsuUUi5V\nGTGCF+rrnSZBy5dy0OrWuxT5ZNXBV2eEMDGVmG65x+W+/9lD7PF63aTq9UinTdvRcOtwaqYen6tS\n68flGVaE4zL9Th6wf1O7vvLW60qDxqP/awBfBvC10LE/A3CXMeZvm43C/wzArwH4AIB3N/+7EsBf\nNP+fK7gtrouHr8kA0GaiaN/gWSkDFy9SE9yUUiQX5SzJy9FUWdLVtFtcrYyuTwFSVUjZs/GO+fMi\n8QMulW66bjKn0kljMIAqs4ND2o4mb/0X7hnmrlOnIy3N05fzzwua5uDfJqJl9mEAv9D880IAP2r+\n+XoAX2s2CN9FRINEdI4xhm9qHduAAAAgAElEQVSX7gF7i7vqs0+qFklSBoCmmk0j38qdIytl4HLj\nNUbIt7mJNm6R1mJPS2Vpt7haGV2fAiTtrseOH+SdSie9cGyjI/H2NmoVwsTUDM7f8JizYcqq/wLo\nAvudjluvXBo7pqHfsspTZEXW9MqPA9hKRIcA/HcAG5vHhwCE95VvNI8VDilN6sOrh1Mpg6RqtjA4\nA66lJbJSBi7pVprgJjdejSQvoE9N1LTY025dtZ/j5sXJ6PpsjzXXFzi1iwgkaaXgf9ZUOs64AMDq\nCxZFzptk5IPrNNhfA6iRyJB0T6Wx5tnmkruHAzXeRC3oq0Y+p+nop+z6J6JWOfUyrVLDtmTt25tV\nniIrsgZj/xOAPzbG7CCi3wbwFQC/4fIDRHQ7gNsBYHh4OOMwTsFHm0RbzSb9nuYNnnV8kqcablIO\nuKVm2ePVepzagKemxZ526+qyxc06Ly00BWPcLiLvIr3AuNhaQs8fHFc3zwl2NGu2PKXqYNaqNpfa\nezgxNYsDnz21K7MD1AH6axWcmK7jXYP9GOir4IdvHo995hff0YefvD0duZbPvXY0VpC59aZLcguU\nZpWnyIqshv4jAD7W/PN2AH/V/PMYgLC7cW7zWAzGmHsA3AMAIyMjxUUCGWhLxe1qNl9kkVTQpC/6\npmb5xhnGjk1GePAkBPSAtrrVhXvX8vaaGI0ULwDiVa/hFD6Wj1dqvbjgc+suiniTnMaMhDDF45IO\nCLS+zaX2HnIvP1updfnGx9lz/OTtabx89wcjx4pWR/XJ/sqCrIb+RwB+FcA/ALgawA+bxx8G8EdE\n9A00grDjRfDzHFw4326XRdj9+pFcU7O0ss/S4iRERc2SENADnDQ0d82lHc3PT0a95vUPRmMA0ne1\nMRouL5tbDyPnLY4YE8kD9SnS89FY4RCmfnwMjrRzyzOg6CJJbr/8bCRlnHFOQ5HV8h1XMEVE96OR\nUXM2Eb0BYBOAPwTwRSKaB+AEmhQMgMcBfBDASwAmAPx+AWNmoaUVpFLxvD0uDlm8BC6wyS18H09K\nquZ77IXDiQUngKzbnwZtxgbnSR6bmIrxz5x0s5Yuk9ZOOO96LqAcosw4Z8JnB8LBV2NloFbByRkj\nernr167AJ7btQ7gUqNI8njYOl54NWT1kH0lyGxWCWCUedlRa0f3Jh2rOAk3Wza3CP13OfNYA+Kjv\noLJAuwWVPM6jHh6XBlkLprR6IkD+rRTtSmOu+jbJgw/iG9LotRkbtnclySVzVJDGM0uK0YTB3Qf7\nBeuS/ROMLwlaB0byEP/PlHqF3a8fgV3vWW8eT3OQtNIZPsWCeaYhzp9XweR0vLrVRqu6PxW9awij\ne0XNLGhFgqRcc00Oug+yFkhopGwDZOX3tN8LV9++uuUaPLPhajETJYhvvLrlGvEzRfGRrvAdx9ix\nSecm2trsHxcO/cbLhyJZIVLcJtyomtsdAvGirLSEBdestqDJSlrGTp7iXycURj5AJ0teZ0HPGHpt\n+qJvZSjXzV3T4b3oAomw0JNrqptLlaI9Xo1an081KgdJMbO/Vslt/q6v/XBqIoDIy1CqxNbce62h\nk+oN7GsQUIFjCTut4PuacWjkDpJ0bdJSdfNcOy4vBy6fXfOcdyq6UuuGg7aCUqoM1eRI+/S0dNHA\nCPN28wUxpfnzKjj7zPmpgk1SQDGtXZ22KbWGQ82bj9x83coYrwwAM3WTiWuVsmm2PXcoQtdUAFSt\nALINrh1g1gYggD5op6V4tFSgvcOV0ivHLXpv/fbR2JrzabKSp/iXFNjlYPt9rWhfWSR6xtD7VFBq\nPQSfnpaa83KLSUJ/rRpJ/eTS69iAovBiytqU2oVayPOBqFYJdaaXbhguXCtXpbntu1H6olol3PK+\npXNGTJQfthQYfRuAAOkvSWmt2Me1VKBdlMWN48jxk/F+xnUTEwTzabKSp/iXSwDXzmdvVfvKotC1\nhl6r6Ghr1PtonbjQLJo8ZPu8Lro29kJUBxSVLyatgWl1PnAwpiSvOgzuumgyQLhzTM+aiF66Vvum\nFVldWlkEze/YmTkBtEFxG9z8JV0brSop10Q9a2CXQ15aVZ2CrjT0Lp6vnTnio3Wi3YIC2XrQ+ixE\nX+lmTaUpB2mnomkMkedYJXDUmCZnXmxaE/LWXRQ/tXn0ae31JMpAG3uSWudVqEFX/KuFZ2DkvMXq\neWmRtcmKVrdeoik19CkHbQ2Jj0NTdFFWGF0ZjPXRBQ+8/CxBFa1zlHewSKO5s37tirgUbg7nTgOn\nT3Lj5UPYsWcsNdCW91g11ykpZz48XhdUiUK6QXxQWxPcu3Pn/piWENeGkMvYScp+CuOai89hP1c3\ncL5XmkBsAFsTB4hnJ3EZOy4ZYV+37uH67aOReUiJAxy4jlCcllbWhII8W1pq0JWG3ne7dHQiPdrP\nIUnHPo++nNJC/JXli1N/f/frR9hiENv4B3xpGL4VeetWDUWyTJ7+wVuFam1LmRi3KQTstBSXC+rG\nzM29VuUfKSm4l2bUtfrx2uwUDU+tvVeckGCFwBrEt0/MxJ45IJqdxD0zPr0nbCE9F46eXSd5CeOj\nM/XoOw7SNsqutJQyR2xogyrSefPSxJEW4ms/nUzVcv/RuGDAzCn+tkqNYOLIeYsL3TImaeKEpXCB\nbJk4Plk8vhQXhwrR3Lyk9aYJ7rnYDdvT1V4TrZOkjW1w/Vbtcfho4nDzOjw+mdoHOYBGSI8DFyvg\nFFk3PvQC7nhgVKw8ltBxevSdCIkX3nzdykRdmyRoHn4X3Y0s/Jv25rvEKAzAZizkKdZmI8mYhrfV\naXICSciaxcOtHamU3z7OqYYCp66viyyAzwPt04ZQ+6LTxjakeFeeKqJZg8A2krSa0qp7pbGGK22D\nNoQAUo29FO/T9rN2RVdSNxwvzG3Tuc9JNLYmO0Gru5GVf9MWx/jGKIraHgbQbLen6yZXrXgtuDVx\n2+phFRW09eZLsPWmS+aOcWtGcjS54B4H+xdrVYo/pB6Ugebe5N36Ls/qVkDfFwCIxhF8KD+XsUqt\nHsOQzE1RBfpd6dEDvPciedEab0CTQaH1uLPm3Gpz/H23d0WnhNnbbRe71Ip0NW7tuNBZwXGXVn1c\ncI+717aWEEd7BNxzXrSXLbXs2/ouLXMomGvWuJCkJzRTN5G1ViFE+tf6UH6aXgQBOFtiXxOpG56m\nn3UWdK2ht6FNmxsUtkyDOeqba3Xb7XNICxFA5HuSlntflTAV8pLtv0vjLQJhY7pmy1NqXlw7Ni01\npv1cFirIhe+3P6c1OpJjwqUXhn83CXnOVUPxcGJ43Lr2eVktO6sfz7x8JPK5uomLs2Wl/FxiBUTR\neV114RJs++6hCE0poahns2cMvVZqtlalmFxphcDqm9svCa1nksQFupboB9rzEf18Rsu9ViXMWEad\nM/KAW5pZHuC8oQoQkzAAdGPT9KQNPldk2bqLl8fRPBqjoy3K8qnS1LwMfaUYAjG88DldegBwzk8Y\n33nlSOwY0KBRsrb7s2HfL6mrlf2ca2UXitSj70qOnoNLZaj9Fq4bYNaOqM+aWF5u4Jlk6Q/LBels\njlObcjddN1jQNy8yjnkVYg0nhyxa3j7gePGFQg62ZmyanrRA8Sls3LwkuBRXZf1eFtpLG0/SxsV8\n6U27nmH99lGsf3A0euzB0Ygw29gxOQsn63XX4HPrLsKHVw9HFEMHahV1RhCQT1q2Bj3j0ReRNmeD\n80w4cEJM0oILPwAuKXe2lrtLJkI7yrZtb8gnE0PTkzbpt8aOTWL5xsdTU+K07QXDxySayiWAGIbW\noweybftd4kk+WT1aelPTA0ArfwFklx/XUn52VyuXuA2AQrPfwugZj75VdITGEHFCTNJyCz8APnm+\nLnDhwYuSZc07E8P1t8L35uu7DuLOnfsj/541c0oj2+wCrZHPuu3PO59bW7jVql4EffPIWVLcp2rV\nSQq5oFRKDl3r0XOiZhxsyiRr67sAmhvp4pmHDYAUZLXBPThE8epL6bsaHZqde8ew/sHRSACJ68ua\nFevXroj8PtCIM2jGJum12CX5Lhy6zeVmzZzybX1nr+ukueYhkpa3hos2yOwiGaxFrQLUTWMHVGk+\n6EGee0AD1XGKpg3W9PbdB7HrlaNzO7z58yjWiUobA5HknGdnTYRarVUIm69bGf+BgqDpGftVAB8C\n8KYx5pdDx/8LGm0DZwE8Zoz5ZPP4RgB/0Dz+X40xT+Q9aNeCoaClnRRQrVUaiyMSoEVce1zrNbl4\nQ2EDcFIwSH1VwpJ3nJH44CQZ+aT5SwHKux45wKo32n1ZvWCNeXbWxLITuLFtunYl+5IIp9KFvxM2\nOtJasT3nrJ6uj4fMNq4XmqhvunZlbi/cvJtUaygelzhRUq/XMM48ozYnnMZRaBINFM7WmTUGE9Pp\nNKuEpMy5VgmYcdB49H8N4MsAvhYcIKKrAFwP4BJjzEkiemfz+HsB/A6AlQDeBeDviOg9xphs1T0C\nXAqGJHmCMH9+yxW8LEBwriLL7MOLZ0JodTY1a1K5vKSGKhrdettbkXYWmh2HBlxJeR2Iacz7SCi7\nIszbn1Hj+4umebo+HjLb70DZRD0rirqWaXBxhvprVZyYrqfGu8I56EXEobS7HKnGp53QNAf/NhEt\nsw7/JwBbjDEnm595s3n8egDfaB5/lYheAnAFgO/kNmLobyJHUwQerVYWQFuUFYZLmX1eXOX6tSsi\nKYdAY6eStVFI0XAJnHOf1XiNLjs/IMrbTwpeXRrX7uMhS/dA20Q9q+xt1txy6ZxAukerpSkB4PjU\nqWuZFLNYGKqF0VKZWvjscjqhO1VWjv49AP5XIvo8gBMA/psx5rsAhgDsCn3ujeaxXCF5TbUKEHbC\nzl10RoymCOfVB9A2MtDeMKn6MC0HP0lzRQX7g8wXtR6n9KDkVaLtkk2SNXPCRypCQhrloC16y7uJ\ni0teusa4aAw4RwNyGkZcVzOOkvKJn9UqhONTp2phfI08EfCuhf257HI6oTtVVkM/D8BiAKsBvA/A\nA0R0gcsPENHtAG4HgOHhYaeTSwU49k77h28ej31Xuv+aSkPfVLS0MntpbJo1K3VEytLSEJAflLy8\nJJf85qy50EXsUrQ8bZbCrbzbXHIFgxpPUtsbmXOatOmQHCXFOUNJCMeepI5VWXHblcO5FVp1wi46\nq6F/A8BDxhgD4DkiqgM4G8AYgHCzyXObx2IwxtwD4B4AGBkZcXqSpXJkr3QaC5wB971haVtkn8bl\n2rFpPU4p24MbS9GdcrJ69JKHbBsYF9nbInPVufoLbSNsbV66xpPU9kb2fdwkSkpTfwJEc9Bd89fD\nGKhVcHLGOEsNa5F3ZlMWZDX0OwFcBeBpInoPgD4APwHwMID7iOgLaARj3w3guTwGakMrVuYD++Fx\nkRbNYvyklLNlZ/XHtv2AjvPkFpPG45SyPWzvshX8o0YkyqVs35azTiplj8gUK9M/bbjIT2sbYd+5\nc3/EIErBY5fxaP89L3A6Ofb8JfTXKpH7oGnzyclM99equCGkw5NHK8WiRd2yQJNeeT+AXwNwNhG9\nAWATgK8C+CoR/TOAKQAfaXr3B4joAQDfAzAD4KN5Z9y0EhxvzWF6th4L+N737ME5L3Hs2CQ+8cA+\nAMnGT+J//+nlI5Htt5bzlBaTprG6NtujFfyjvYvwiZVwcwi8t7DhXH3BIjz36tEIFaFN/7Sh9ei0\n19J+MQXBY0k/yIbtmNjrwSVQ6gM7sO0SU5mpm4ieTNA5LZKMUCUs6JuH8clppziDj6PiIurWUemV\nxphbhX/6sPD5zwP4vM+g8kaYy9Nme3BGUlr8x6dmcXwqWcSoboBPP/RC4s110euxoTXMLpkommyP\nrHTWmuWLY2qDHFy10bOU7QPxUvY1W57KnP5pw1d+2j4u6p0TMBQKIB6bmIpkrMx9LOSwaHdztSpF\nnIvm6bzoG9uxcdlJcPEobRGZLVmRp6OiFXVrNbq2MtaGxOe5NMwOvxA43to3ZYvLkw97UxWHTBQO\nGsPs4jUFDZ2LyBS59w/fj9v+8jsRY79m+WLcPDKcuR1enpSDy2+lfVa7s9BeS2mN1I2Otz46MT13\nX7k1N1036K9VUK8jsQWlr7aULdutoV+ScGxieq5gSou811InBF459Iyhv/XKpXxJtYlKhkror0Vl\nfzh54Lxhe1PcA+ziNXHG1d6Wu8xjfHJ6bhcjbWmXncX/5rKz0gNNN48M47WfTs6N7eaR4VyFs3zg\ncq0059XMS3sttamvGrls6aVht8jjak1WffZJL4rHlvPl6BcXZLn/ea8ll98rOokhjJ4RNeMkQ/tr\nFbV078mZeqo8cN6QvOsq0Zx06a8s1weGbM6TE2dyyV+xnzdO4nfXK0fZ70rHk8amFY7SCmf5gDtH\nQGkUdV7tteyfxz+29nGtXLYG3L0/oXw+AgOeNo7pWYMzz4jKb88X5sohi3Bc3mtJK2rns/6zoGc8\neqCRpx6Onrt4r7ZRK07F+hSk7VzdGLy65RoADepIC5vzlMTVfLhVe8ySR5hGQbnw7Jznc/cNFxXq\nDa1bNYTtuw9GqKUrzl+kopayIulahikOSSrDzrpx0frRwL73SVk+HA2qGYdNv7ikTT46etg54OmS\n0qrxwLWidq0uouoZQ88FlXyDRS4IL2yuz2fwmTA02zwfrlh6mOxrYlcUJ8HegkqxkbTcd5eUQ66b\n1NabLyk0uHXnzv2xYPEzLx/B+UvOLOy8SXnjYYrDRU5Dq5cfHsP8ecS+THyoMe047HO4PL9Z2itq\nU1q1mV7add1qLr9rDb39dj1+Mp4iyHmvRRh/WzjMXhQAvx2UmhxPTM3g/A2POQeoYumg0M11uh5v\n7SflHNtzkGIjt165NHbMHqvmQU/qJpWnPov9W1JmS9bWdJpzinEmCxrJawlp0s2zxjTWg6UYWavG\ndZMGahVxd5HWMlOSqc4qv81hcnoWH9+2Dx/ftk8shJI8a1sShUtB5jxw7bpudRFVV3L0HL8lGcNA\npjjg/G5bPRznXhkOUQvO+K1bpWu7Zn9usL8GUCMrIpjX8amZ2Ni0XLHT80HR67T15kuw9aZLUufA\nxUY+vDq9fFzLjWq7SWmh5UazUlI+5xw5b7HXA6mR/rXXHLfz4tptcotpvnX/JIjtGxXnmJeTtpLU\nYEbyoI9NTkfulxR0tr+vXdetiDOF0ZUeva9MsUaSWNLO4HLVAV6wylU5cM2Wp2IGTMoPtsfryxXb\nqXnh8YXBeaZ2DjqHdvDsHLTcaFZKyuecW594UZ08wIEzWtJOIjivlgOfrsd1k44Jxk8zNk6mmjuH\nllLUwt6R+cYtuBRkzbputTx0Vxp6LY+V1E0prZBCol/s8nmXTkxp23fRuxDyg9MWhaRXw0Gzocmq\nkCh97+4bLkrlu7XdpLTQcqOrL1jEFnStvmBR5O8aSsaXt9WCkxRI45VdDJ09Pp8U1Hblm9svb5cu\nZDZqVcL4RDQF2SV+5CMP7YquNPQSbz1Qq2DRgvm5lDdr37hSJ6bPfHO/qtQ6bCSlgqmwzrbLm/+a\ni89Rt2vTpLFJnmn4HMFiT5vX5PQs7nokXRpa6iZ1zcXnZLomWm70tZ/yBid8XPvik9arlrflYMdf\nslYQ+/ROkLSZbH5f6hnLCs5ZHrJLTC2829Z+h3vOjx4/ycYe+msVLA7ZlyPHT8affSF+1MqceQ5d\naeil3fP8WjVTNyUJmjeuVhZB0sEPH5f435+dcM8mANzatZ1Q7JG1Rmi6bmJaLByOTqQXZHEPos8L\nXDJOdiBT43FqpYG5QiCX4DwXFNdop2jmoLm+0nil9fULZ6RLcUi9Vd8+MRNZE1rYu20XkUP7OV/1\n2SdZQ3+GZV+kc9gv9W5uPNJWSNygfdxle1j0G9dHa14qXErzGlweFE2036VZSBZoX8KPjh7O/ALX\n5jn7pL5yhUAaHRZpF8kdy3P3YiNQb0zLLZfmr5Hi4OYqpSVzSLuePpLfWvuiRTc3Hmkr8k5hknK1\ngfQ3blKKWZHg8s196gg0qXlFGvkA9v1yEWHT8Lval79GiMxF5ZGLs6QFSsPQGAT79yRJhfC9Tmoy\nkpZbLj1fWqrRnqs2MKxpju7TxEU7rwV9VVY0bkFfNfI5ac22Uv+mK9MrXVKYuNRE+3NJudpp6Jun\nSzHLG4NWMFKqgtVCQ/NovCENkjJX7H9zybDS7EqkzwQP8fkbHpurRk5LkXV570nORTiFb/32Udy5\nc39kHDv3jmHn3rHYMRvc70nqoI+9cHjuz1KTEft5CHLLw+O46sIlrEzE8amZTKX90r1ZNFBLTfO1\noU1x5iDJX9jzmpqpo2rZl2qFMGXJqUirvaiceQ5d6dE7pSYp+qj65Gprt5p5F2rZRsbXO9B8X+KQ\n6wBmQ4ahWqFma0f3XHT731wyrDTemjSHcL9RbVaQ9t5zY5Oci1hgm+k9wPG73O9JCO9CXNaNXXnK\n6axzaclamkLywtO8dwlZs1o4+8LNi5MG5+gnrnCz4xqPdCo0N1HbRzUJyzc+nthiTOKtCY03dlaN\nkeD70vfGrcXkmw+sVWAEdBxy+JiL/LJWJkKrPa6Zg49xSppH0ti0Lwmu9wA3tqwFZD7rhtNZl+gX\nzQul1bnlaWPR0Ep2PEL6XFC4WWbdFAAtH5uUbx7mKQNvK2zsJQNmgFgGUJYHalCZmueTDwzolf9c\nOGTXohxuHHl7ecG4NA+xzy6p6CYTefG7UvaL3WREOw4pbmFTjYBbjKLd8I0LZq37yAtdydEDUPGW\nkpdqH9907cqYpIAEWwNF4q0HLc6X4zOTEPB7Pz8Zl0DQyi64LK5HRw+nfygjXLhIexw+XKvv+Gze\n3l5jUqxBUz3r++DbY876e+tWDeHGy4ciEha3vG8ptt4clb9Y0MevXduASxu3k9OzkWt55879aple\nzbPOIev3OPhIGwRpo62SJOaQauiJ6KtE9GazP6z9b3cQkSGis5t/JyL6EhG9REQvENFlRQxaqx2i\n1YZet2oopusiwfbgpXP8/GT0xgZ8ZvgcNcVrdrZu0DevojJ061YN4ZkNV+PVLdfgmQ1XY9O1K9Uv\nF5/OPmlw0QnnxmHPK2+PTxt8s9eYJNyWJugG8M6FVJ1sH+cMjIuzEoak3gggcs1rVX6x2obdphQD\nTEyn93vgNHGy6rbnrfeeVb+q8ZKcxwa3Wf2fgqChbv4awJcBfC18kIiWAvhNAOHqkw8AeHfzvysB\n/EXz/7nCRXGOgybDxK7uC2B7a9JvzTI3Vstn2jg+NYsDn3WnAjjOs4hOWWlwKdzygbYWQqO7o+Ht\nuabit17ZaLmXll7okkc+f14FUzMmMac9673W5nhLBvzY5HRkrlq1VYkU4jRxsuSg++aua2klzeeK\noAZdoWkO/m0iWsb8058D+CSAvwkdux7A14wxBsAuIhokonOMMbnyAmLTAisrQIImB11ytm1vzUcv\nvhWGl6v6y1M7Bmhot9vGLhzHcJlj1nFo5Qikqlo7w0aqerTnYgu6ueoBhe+NdE67rd+25w7FctqB\nbPdaG8eS1mre7QBtCQRp7XDHw0ZXOrtmLe7cO4ZPPLBvztEbOzaJTzywT72WgGjMqtWSxBwycfRE\ndD2AMWPMqPVPQwDCJPYbzWMdhWAxBdzdXY8ciL3962hoW6TJ77rcLJvP5PL82e/1x43fnTv3Y/nG\nx7Fsw2NYvvHxmPxqAJunvObic2Jb/FqVsOnalep52OP4+q6DsaB1eDxaxcewho0rr5okR5CFMpBG\nnDYT7Tg4GkF7nbQ1HhydY99rLkjKHde2JeTaAXLrN/i+PbZxSx5Ygn2tbKpG+z0On37ohdhuvm6A\nr2dcS62WJObgnHVDRAMAPo0GbZMZRHQ7gNsBYHh42OennOCip3Fiuj7X0k+CS7YLG6hKWXe1CmHz\ndVEjHBjXAFJGEOdd7tgzhlvet9S55ZqE+57lRdPue/bg3FiSUivDKWc+GjZaOQItZZBVskI7Do5G\ncKk81tAjmnRF6ZT2cRdq6KhVBSwpwdo5+EcZkTAJ9rXSFtZprrG20l27ljohbTRLeuVyAOcDGKXG\n2/FcAM8T0RUAxgCEuY1zm8diMMbcA+AeABgZGSmstl5T0CAha265Nvedy/MPo0qEW65Yit2vH8Ed\nD4zOUSPSYrW1tiXv8rEXDmOgL5/MWmmHXjenNPqlMdue3mMv8Bo2nMolEL3mLnIEHGzKICt8ZH8l\nfRYfpKUrSty7dDwMqQjQ9pq1hs5FiMw+h5ZCzau6Ownc+ml32qjz026M2Q/gncHfieg1ACPGmJ8Q\n0cMA/oiIvoFGEHY8b37eBYE3nEVPA8ieW37pXU+yL5MzahUV/xhg1hjct+tgpBlFHlWlGtXIPBDM\nTxrzz0/OqGIq9njXbx+NKDqOHZuc67ql9QhtjE9Oq3Z5UpphAEkdk4NPLcT8eZXUYj4JYS5bKmZj\nJRusvgsSuN/jDJ0d23GBfQ7N81QEXcJVvEo9MGy0UrpYk155P4DvAFhBRG8Q0R8kfPxxAK8AeAnA\nXwL4z7mM0oJ6UTAfWyjwhRyyZotIw5u0Usw0cJFLs6+L1jP1SfXq1+SICrAzk7SYrhtWB3xBX5Qb\nHnAYm3YoUpphAGnN2EtCWwvx4dXDbBrmyZl6YlxEgs1lc0aZGxvXd0GCJqDOxXZcYHvmklO2oK9a\nWP1Ff62K21YPR+7XjZcPYceesdR4TN7pn2nQZN3cmvLvy0J/NgA+6j+sZGibKHNyBy6OQ9b0p6xy\npr6wM4LWr10RUeVMQta53n3DxfjEtn1eLfDywrHJaSyYf2pJF6EqmkZpJHH0mhJ4zvO1W19K59A0\nLk/jsqX0TRdaTGOzpebrNirUGFOalr/0gh0c6MuUmiwh7R5KPTDs1O/jJ3XNxvNCV0ogjJy3GPc/\nd0jlEdoPhYsRdvH+w2hF2iQBc9tuKX/7qguXpKeJNMH1vsyqHeMzdzumcuT4yUh6YRrCqX55C8kB\n6RK80vy53sVaaNMwZ5cA5McAAB/7SURBVI1JvYdpL3RJktgF3MvQpim0AXqtHr9L74k0JGnZp91D\n6XxZU7/zQlca+q1PvKje9nu1a8vYgX792hWx9nd545feuQCvvDUx9/dX33o7lrHCdbUC4rwil4nk\nwttzBSJZZs715F312SedDH0YnGqgi46LjQrAqlwCp66TtoOVD5IC8uEXHXcPNUFrzgN1Acfva3sK\nANma1GvbNWpQhJa9FkXl1nel1o2PdC2X0yrBi4KxnsMKEONaNe+RivC5H755PMJvPvPyEbUefUAj\nFFWirTWhC/qqqSXlvjSYPdetN10S03HRoo64mqR9nbQdrHygkVgA+HuopcKPKfPZbWh710rQPBMc\nv318SqcJpUHeWvZaFJlb35UevfTWtLf9vqXnWd+uW594MWY46wB+oW9eZHyaB6gI7tveguZdoq1N\nE5xQSDv4ekjSdju8LrIqiwYIXydfCoHLxAB4Gehwxork4dvn1aRNumBBXxUnpuuZWg5y0LyHpGYp\nWaWrORStZQ9kl9rOgq409NLWyt72S7Bvol2AFIDbbmsexKQ8+rB2ta+B0UCT/pUkLZuFt9emCWp+\n30d+WUp1A9KbYbsgXEXqUu5uryWuYExqPHL3DVHpBWkt2ec9o1bJTIXZqFUb3ZSythzkoMmoS0ob\nzlIfkneao21fpIIxH6ltV5BpQR/QNIyMjJjdu3c7fSfPmyNpgizoq2JwoC/RIHCcrxQEtL1LW1Mj\nb3DVh+wcKhTJSwf4efXXquotbPj+LOyv4fjUTObft++1tAOzd3Ta+8VdJ8kL4zDYX5t7gUsPtT0v\n7nMuwWNuLWnOe8HGxzKvt4FaBYsWzE+9D5qxSVizfDHu/cP3J35Gel5t1CqErTdfkrhetdfNF9qd\nmus5iWiPMWYk7XNd6dED+VaaSYvm+NQsjk+dCm5xwU0u4MoFATn+bffrRzI9dNUKscHoNcsX47Wf\nTjqnf2lbormkf3FeTZqxln5fqwbI7Zi4Lb4NTln0tr/8jthzlTtveKxA+gPs2+M3a5m9j1Mxv1bN\nRPm50Bmv/TTd89f6poEmUJEql1qkeflFFi4CXWzo2wGXZ0STN63NJeZiD9t3H4wYojXLF+P8JWdi\n1ytHYQD8ePwEdr9+RM2Xaluicd/Xeit5xQXEGI1S+VBz3l2vHFV/16ZHNE6Ibxpd1jL7JD4/rX2l\nHRh3oanylO51iTOkyZ24xFTy9Mpb9YIJ0POGXkPxSO36fMAFAV1yiQNwsYede8fw/MHxyOe+88qR\niOEPqiVffevtiJevTUOTPmfXFnCl8XdsH400B+e8FR/pVimFcdySSnChQuyXhLZSM2umhFa3Pc9z\nAnKx4UCIu5daa2okG/prVSw7qz9VnsHn/udZp6IdB+eBaxu3c8gz71+Drkyv1EJbZrz5upUquWAt\nuAeRG0sSktK6OG9A2pI/8/KRTGloUkzMPs6Vxs/WDZuueccDo3PywwN9/NJbdlb6gy61PbRDjJKp\n5uRx7VZvWpy76AxsfeLFVFllWy56etYtIBqWy+YyWyTY5x05bzE+vHp47veIGtWnE9P1ubmPC1Qm\n15nNbkN47qIz8MzLR1LlGaS6gmVn9afKVLukMKY91pxUeK1CqhTR6Vl+nWvSkqUXWplHnwFJ26Mw\n1q0aiuVWr1m+2OlcaTm3LrnEC/qqiW3zfLwZTi/cJX/dPu5SGj9rzJwx+eGbx9nPaCiTPHZfaXUE\nWvzwzeOZdE2OT7ll+NiZLRpNFMnRGTlvMV6++4N4bcs1eNfC/rj2uvB7di0A14ZQuq82TSnVFfyT\n5Zhw15PLc5eguq32y4B5Ofg0GOIgOTQaRycLupa60VAyLtsjm0Ncs+Up9VikxgqasXCYSDECSTyr\nBkcnpvGzyZkIl7/79SORvOz+WoXVirElAPIGNy/7XvvCAJlaOmrA8awuL/ms5+Cg4YF9DJjLvLTK\nqvbdl2SquedVki0Iw15LE1Y2GMBrZLnQRZpU2sPj/G+5xIZc0JWGXhux9uEBtQ9ArUL42YmojsX6\n7aPqsXBIG5+Pkbd/I9y0JPxvE9N+0sJZwXUO0srjZj1H3tpEY8cmMwWFpWwq6RxpPLimDZ/PunR5\nSdjX3CWfn5PV3r77IHa9cnRu/qsvWIQjx6cSZQtcpBjsuXHxCClVV6JtNefN49nm0JXUjZaSkXhA\nje6IJGjWX6tEtoy1KsW2h1yrN45XDDTUo7+fHmiTtqoDVuvDNcsXZy7HlpBVWliL1RcsivzdRR5X\nC07lM3Zvmr1PsyDooxrQD9Kv2K0q+6pu50vjwaXio/Dx9WtXsDLImnXpsrtafcGiCPfuU7Q1OT0b\niwM88/IRnLvojMj1vGx4YSR+wrUMlcBlUtl0ESen4Uvbuurya9GVHr2WkvHRHZma4W8MAaom0jaP\nLOU5c8fStuRS1skNl58b8+rsLWNRlbjhVNIfHUvu25mEAz/6eeTvPl2jgEaDjplZk+j5au+N5tpx\nmT6suFqFMFM3EWM1KeyitLBliiXvMHbc+muVSNVuUsq6uWx4Yczbfv7guFrULCvC8YHA+AdwPSfn\nDErpq3mm0mp1jFzRlYZeeuhs/li6uZoLL2mZ+2iccwslS6MBlxeYVuLWB3YqadI5UnO1c05znZpJ\n7/sL6B5in3nZdRUulbda2AY8SW43AKfLNF03sQIyDtoiLa5wTUJwHdOqb4tGniJ00rror1UwNZPs\nhOSFrjT0nAxwheISslIedZ5BRCnnWNNlJ2t1nIZ7DZ8jz0Amh4G+aFu7POFb46AJjGmLXJKC4EFg\ne0AIYtvrIW8jz4F7TmrVaOpgK/K5XX7rttXDEWMn6VAVjTznL+188pZZSEJXcvQAYha8buLl7cGW\nOQxtsYlkqO3jm65dGeMza1XCpmtXpp5DG2uwoeFeAffc/aywJZOTkDYO+/r61DiERc0CnvbOnfsz\nt3BL21Y3gthxI18hxPL0pRlxcRZ7fTmB45FC8Mnn1tapSL+1oK8ameuHLSMPNBrGtwNBAV1afYQG\nPrLHeUHTM/arRPQmEf1z6NhWIvoBEb1ARN8kosHQv20kopeI6EUiWlvEoLntpgRbj1x7gbUGfN2q\nIWy96ZJYkEZzDhfPPAwt96oNAklmpB1ewDUXnxP5O1fjwPVRrVUbhiKtf+e9uw5merkCwOfWXRQp\nNtKibuKNTjgnpFZptMwLvzSfPziOW963NJN+vkTLhOfqk7CgdVS4YHd/rYrP/7uL5vL5X777gyxt\nkefOh0t+4ILuXAGdbz/XdauG8MyGqxPrY4qEhrr5awBfBvC10LFvAdhojJkhoj8FsBHAp4jovQB+\nB8BKAO8C8HdE9B5jTH5JxHBP68rSwm3dqqFYbvkt71sq8rhZbpxEBaQZEg33CiRfp+DcATf46ltv\nx7Rzbh4ZVqlGJo3TNTD76OhhNghoX1+7j6qWG5bGYqdESnTO59adkgf2jXdoeHtOcE17Xg0tI3HR\nO/a8EVn7HH+spX20XH4RqBKhbkyqtn9WwT0Oecse5wFNc/BvE9Ey69iTob/uAnBT88/XA/iGMeYk\ngFeJ6CUAVwD4Ti6jbcJFJ0RTgMPdiJ17x7DtuUMR72rbc4e8emlqxhYcX7bhMfEB07arS7pO4Xnd\n9+xBVC2v5vmD47h5BJnlZsMvWBfdfbu3phSzkALbPhlG4TZ86x+M10LkjawNYNYsX8wqa9rV3Jo6\nEslYh9Mfw7UW4bXoI2qmhUuMhlOM5XbwaUF3H8E1ru6jFWspDXnszv8DgL9t/nkIQLjW+Y3msVzh\nsnO2q1bV+jcPH2C3vXZ+vA/StuFSfrQ260Z7nbj4hiQVYXONklREmM/2aa+mpVW4+ypNX3NZpmcN\n7nokv3utiRVp+fJ7//D9sevO6bhLlEn4vC4BelvGQPP7vuBiNBUCq9d0m0XdZeXBpRoa6XgYXN1H\n3mspC7yybojoMwBmANyb4bu3A7gdAIaHh52+69JH1DZ2WnlQyYvIM9VL2z3Jzo+WPAubfvDlNzVS\nEUAjMyJpm89t3X0khAG+lF1D09Sq8RxxaSx58cNcYxMpLz0tSybAzSPDEVXSm0fiz5CGMnHp4GXv\nQFtByeRZf6KFVtCPg7RmWpFllYTMhp6Ifg/AhwD8ujnVpmoMQDg14dzmsRiMMfcAuAdodJhyObeL\nobBfCnmkk9ml5xxfDKQvRHsRSxfBfsCS5h+mH3yh9fbCvLUErTaJZhwuJeUxmAa/Hx5vUbUFWYzQ\nrK0EylQFS/TA7tePqOIbYXCG9PD4JCsGxsWO8mwAlDTGLIVKWaEV9HNFlraceSGToSei3wLwSQC/\naoyZCP3TwwDuI6IvoBGMfTeA57xHaWH92hVYv31UlXlj64xL/VFtYyLlxwPx0vP7nzs0Jw3gqlO9\n+/Uj+PH4icSAJVF0kfj2ONVA8iS5+IYdtJZefuG5S3EGroJUIxmrRUC/hcfWL+iupInVJdVQZEkA\n2PzwgZhyZL15PHztJHogfD2DNScZ/zBsQyrlrhdVtdlp8NHISoophJ2wIrtJcdCkV96PRjB1BRG9\nQUR/gEYWzjsAfIuI9hHR/w0AxpgDAB4A8D0A/xPAR/POuDk1sOhfqxVdmtTbJ2ZUOh52ml8SbP0X\nrU518ECl5Z7b2ik79ozhxsuHMqXcqcEMiePBP/HAvsgcgpffHdtHE+MgUpwhdlpPyVgOxyanI2Ob\nqZvYg1CrEDZfl1wL4VNDIY1Lc1xLA0xOz+LeXQed0wTtNFIpx71X4RN70NZ9aGNPeaErm4NL2/5F\nAzUM9CX3PQX41nxAeopVHohowoxPJva/rBJh/jxii3BcZAd8xho+hwvdkvZ75294LHMjbGkcmr63\nEuy1o91a+6TSuWQJvRaScfC911z3sxJRtOK+EqCS50hCTzcHTwqe7f2T9L6nxyan8fMTp/TYt+8+\n2BLRpcAz15yDAPyrhWeo9XqI9E2TtbDP4etJh7/vEmfRSMZKLRe1gcZj1trRQhuctqksm35zWXMS\n1aRFUe3q2o0889d9Yg/aeFRRkiQcutLQV4jvHGPvmJKMiS1xWjRc+pcC6VIBdqrXbVcO564JYovE\nSfENLcIL2yXOwknGAu7B7iQxMe6hS8sm4mDz2wGVdd+zB+fWbFChq10PdqzgjFrVy9Bzwe2iC3zy\n9JClupc7to9GYmV3MH0h2jEHbq1zsaci0ZWGXrIN9nGX1DEt3v3OBXjlrYm5hz+JXw/TNHnvEuwE\niMAAhQ2TRPvYqFCDJrIXoi0S51t0ESurt+ZQoUasJRxolLhRrcdlf47z8rlzSAYbQKKxt3PNA9hr\nU2vkuViBT/aHphlH3oFCn3Nov/uZb+6Pxcpm6waf+eb+XObhfZ0U7QqLRFcaei1887c5TEzV8fLd\nH5z7e1ILszAPGqRk5gXuYbfTHLUt8uqmQQfUp+tzL4m+eZVYX9PsPmQD9z97CPfuOii2cKsb4Bf6\n5sXiJ63Iy7bPIRlsu6bBhu89rhBwzsLk1EzXdZyU6qmtKwGye7TSOaQWgZrv2uOTevDax/Oeg53B\nJc1B066wSHSloZdSmLh0ONuj8zW4dlHSVRcuwbbvHkotcsm7RRhXpWcvYheqJfxAzBrj3Lxag+Aa\nJBmp8clp7NvkzpW7QLMbUDftsODbz1ej1ee6U00KvGqF9SSPVpO+KcUEuBaBQNRD1hYHauDjlUvj\n0Eh2tEIKOg1daeg3X7eS5bzS0uGARkszjpN/9zsXYGKqnpqxYQdUt333ULyohXlYfXXVY+Owtn7c\nIg7U+vJuxWdDm+2kQZ768S6wzyHFgbiahrChk9aX9Hsc0vKtuV3JkeMn1bUA4blKsIujJI82HGuQ\nxqvdgXCeuvRdbWJDeBY+uxetvpbLHFoZjO1KPXpOunbrzTpp4Nd+yi+Kial6REb0Q5fwefT2szo9\na2KUhi0FC7jp82hge+rcIp6uGyzomxe5Tgv6sveQlXrcbrp2ZeTabb5uZWZtG5vH12oT+YDV7ReM\nsl3T8HUrT/35g+NYs3xxLAf9C799aeQ+9Nd0j56Ub23L3t59w8XxOhLG+bHnKsHelUgvBfs3tDLF\nErgMK/u7LokNvxLSBHLdvYTv689O6B0X+/daoQmUhq706IHs6U/areDE1IzX+Fx0Z8Ic6rKz+iP9\nNiUaoGJ5ltIitqkQLW8P6OoNgsrYOx4YjWSn3Hj50Fxg2AV2IZWLF5YV3DnqiLd60wS3J6dn8dpP\nJyNxnAAahUQOmi2+NvagrSq2i/B80mG5sYk1LlYl+/q1KyJryZUa2/XKUZy/4bHEXZpm96LdjXG/\n106Z5gBda+g5aLb4rdKJsbeWkhcSDtoGGiaabk11o/t9e3uYtBW2JV7tvPQASeXyQXaKC1URhj02\nX35TsyaSpHqDl3BSTYNmbPY4Bvqq6jiIdouvcX40143zNrm4gLTm7LRcTnOHy34KKtnDvP367aOo\nA6pngoMmLqTdvbieM4xWaAIloWcMvTZY1AqdGIDv4MYZ0/ADxWmYuJwv7fcBWWPml6y00RsvbyzK\nNCGm+57lc/ezGHkg7g358Jva4FsS/5rl5T/QV40I362+YFHmgjzfLb5dC9Av9LTlGnTY9/7uGy5K\nLPoC+LRcbZyB8/K1neR8YMcxXPpdcChEksQTPWPotcGiQCdGI1ObN+yOQrbh9JUyTft9QNaYeenN\n43PXadYYbPvuIWx77lCqMFvez6HtDUlVsBrjp6V98oyfVCsUy2ByLcjLqnxpg9ttTUyb2G7LbtAh\nvSDvvuGiWAaPXfErdcniqDbby3Whszi4FiXOfY+S/y6hVqWIeCHQeu5di54x9C7Boqyt2XzBaYxo\nMiCC72o0fGxodTe4ILONvLlxDnnym1rax1d+NuwN55Eyl5cOjVQLkOYQuMRFtMZac118na7wvCoO\nXL59/5PWg33dgPZy71r0jKF3WST255IkibOCo1GuunBJJrnhwf5aaks/bss8x2/W03lKLewgc60C\neFTjx5Anv6mlfVzWTlq7Ol+nYaBWyU23XDJ0xkRfJnfu3B8Jpkvf8zHWGqpNohW1sONd2piCdj1I\nYnCdaNhtdGV6JQeXFC7ba9x07cqYTg4Adcd4TVuzGy8fwo49Y5GUrXt3HVTFCuxUz3Wr4i39zjxj\nXrz6rm5iZeG+sNMLuX1uBYikGLpA2pWs2fIUzt/wGNZseUpMrbQ/d9WFS9i0tuCFm/Q5KZU0rV2d\ndsa1CsX69Faocc/ySiWVrn/4uC2VneQFa4y1TyqhRCtqUCFEzsE9I7etHlaNrRPSIfNGz3j0LnIH\n3GKuVgh1q7rVbjmn7SLPeWFrtjylanXHgXsA8uY3bXD8I+cRTc+aWMFUsFPJUiGqKQTjYgXc57h4\nDKcayX0u67ZcyqaZP6+Cs8+cn/j7Lvy2BrdeuTS1gYhE79jQGjofqs1nx1k3jSY+dsDXPm9aQxzf\nOXQqesbQA3p5UDsqLmlR2Fx++DyaY2H4cLet4DeBdP5R+n1b4pd7qYWRRA8cnZiO1TNo+GKJV350\n9DAWzD+1zB8dPcx+zuVeJ2FCSJk8ORPnt/LktwE+lRRAogKnVpTPxdBlpdp85SPue/agczctQE7B\n7WbDbqMrG48AeulSLmNDm3WjbQygGcuqzz6ZOQ6gaYrhor3OYUFfFQc++1uJn7n0rifZIHB/rYLF\nC+Y7XU/fJiZAvuqgWZtA2PdeK/9QqxK23nSJ2jFJC9BKa92mlmxI2k9VIrboq0jknRShmf/OvWOs\nnMotV8R3851o+LWNR7qSo9eWxXM8HceVS7yqS6522lh83qfjVus77Vw/vHo4Fj+oIK7bX60QPv/v\n0tvESZT75HTd+Xq6xFQkaM6pRRbdEe7eH5+aUbWSm541uOuRA5FjPtxwUqZMEqQ+sO3oDyvlny8a\nqEXWteLyAtDNf/PDB2K5+tN1E5O2yFt2o9VIpW6I6KsAPgTgTWPMLzePLQawDcAyAK8B+G1jzFEi\nIgBfBPBBABMAfs8Y83zeg/Ypi+e27tpiI4D34DQSrD4FGHY8NUniVcNJxpp5X7FU5a1o0xC5d5rd\naCFvCWnuHmrBZURpPDhWX4iJWUjzsnd4rUgltcH1MZAarEjUUF5ctlQzsenaaIW21LycQ9r8tc9l\nK1KLi0QqdUNE/wbA2wC+FjL0fwbgiDFmCxFtALDIGPMpIvoggP+ChqG/EsAXjTFXpg3ClbqR+o3a\n229XOiONk/ShRyQjFDYKPiSatE21H04upVOzxQVk6kaDaoXwjvnzMD45LV7fPLbu4XsodZOSgseu\n10S7DpPm9Zpnz9AAEu1j6/VoumRx4CiOCoBqNd4ohgtsaw2kVqnUrvjtm0esemca7eW65rLGLbJ0\nK9Mgt56xxphvE9Ey6/D1AH6t+ef/AeAfAHyqefxrpvH22EVEg0R0jjHmsH7o6dDm6moFnAAdD+ry\nezakXUPYW/ExpJzHwWWicC3stN6Kj2zEbN2klsX71jPY91DirW0PkQsea66JpPc/OBBNEXXpn5AV\nUg562Phpu2Rx4CiOOhDJVGucTyddLEEbBLWb7Gg7h9lY4KA5ZOtXaeeVtVtZnsjK0f9iyHj/GMAv\nNv88BCCcr/VG81iu0HKZ2mwFLQ/qW/UYVO6JOdieRLM9Pu7FJO0aNHPjMkeyguNPN127Mpa7Xq0w\ntQtCjrt9D7m4BeelZ6U9pM2wfXzzdStVEsI+cMlB16ZUhuHigGiki/OG9l7bqFV1JpDbkWvnldSt\nrFXwTq80xhgicmYdiOh2ALcDwPDwsNN3tVym5Plrslg4aH9PyrxI2zVoS6+l37d3NC4vJt8mCBrK\nxIZGztandiH4zbR7m7Wac1wwfvbxVuRlu9zrvLudaZCHNEQasqRESvcQ0GV1aeaVtVtZnshq6P8l\noGSI6BwAbzaPjwEIh+vPbR6LwRhzD4B7gAZH7zoAzU3VBne00P5e1m2ktvRa+/suksSaHY0UZyAg\ndXwcOEMq3dcstQtaZBVOc3lBFJ2X7RLMzlKxrKXVtDIDnQLtMyfFQDTzkuoDstyHrMhK3TwM4CPN\nP38EwN+Ejv97amA1gPG8+XkXZN3O+f5e1vNqKSnt70u/l1bGL+G21fzOyz5uj2/RQI2VieiUkvKi\n71crwI1FerizpE5ytFqt2uielUVmoFOgvYc+97oTUlg1WTf3oxF4PRvAvwDYBGAngAcADAN4HY30\nyiPN9MovA/gtNNIrf98Yk5pOk6VgqleRd3/UvH8va/ZAK/q+tgOdNC9uLLFUWo9sD+1cO+maaNCK\nebU766ZrK2NLlChR4nRHT1fGlihRokQJPUpDX6JEiRI9jtLQlyhRokSPozT0JUqUKNHjKA19iRIl\nSvQ4OiLrhojeQiNNs0icDeAnBZ+jaJRz6Bz0wjzKOXQGfOZwnjFmSdqHOsLQtwJEtFuThtTJKOfQ\nOeiFeZRz6Ay0Yg4ldVOiRIkSPY7S0JcoUaJEj+N0MvT3tHsAOaCcQ+egF+ZRzqEzUPgcThuOvkSJ\nEiVOV5xOHn2JEiVKnJboSUNPREuJ6Gki+h4RHSCijzWPLyaibxHRD5v/X9TusUogojOI6DkiGm3O\n4a7m8fOJ6FkieomIthFRX7vHmgYiqhLRXiJ6tPn3rpoDEb1GRPuJaB8R7W4e65q1BADNtp4PEtEP\niOj7RPT+bpoDEa1oXv/gv58R0ce7aQ4AQER/3Hye/5mI7m8+54U/Dz1p6AHMALjDGPNeAKsBfJSI\n3gtgA4C/N8a8G8DfN//eqTgJ4GpjzCUALgXwW02N/z8F8OfGmF8CcBTAH7RxjFp8DMD3Q3/vxjlc\nZYy5NJQG101rCQC+COB/GmMuBHAJGveja+ZgjHmxef0vBXA5GjLo30QXzYGIhgD8VwAjxphfBlAF\n8DtoxfNgjOn5/9BojPJvAbwI4JzmsXMAvNjusSnHPwDgeQBXolFYMa95/P0Anmj3+FLGfi4aD+DV\nAB5FowlRt83hNQBnW8e6Zi0BWAjgVTRjct04B2vcvwngmW6bA0711F6MRne/RwGsbcXz0Kse/RyI\naBmAVQCehdzUvCPRpDz2odGq8VsAXgZwzBgz0/xIIc3Xc8b/BeCTAILO4meh++ZgADxJRHuavY6B\n7lpL5wN4C8D/26TQ/oqIFqC75hDG7wC4v/nnrpmDMWYMwH8HcBDAYQDjAPagBc9DTxt6IjoTwA4A\nHzfG/Cz8b6bx+uzolCNjzKxpbFXPBXAFgAvbPCQnENGHALxpjNnT7rF44l8bYy4D8AE0aMB/E/7H\nLlhL8wBcBuAvjDGrAByHRXF0wRwAAE3++joA2+1/6/Q5NOMH16Px4n0XgAVodOMrHD1r6ImohoaR\nv9cY81Dz8L80m5nDamre0TDGHAPwNBrbukEiCpq6i83XOwRrAFxHRK8B+AYa9M0X0V1zCDwxGGPe\nRIMXvgLdtZbeAPCGMebZ5t8fRMPwd9McAnwAwPPGmH9p/r2b5vAbAF41xrxljJkG8BAaz0jhz0NP\nGvpm79qvAPi+MeYLoX+Smpp3HIhoCRENNv/cj0aM4ftoGPybmh/r6DkYYzYaY841xixDY7v9lDHm\nNnTRHIhoARG9I/gzGvzwP6OL1pIx5scADhFR0Mn61wF8D100hxBuxSnaBuiuORwEsJqIBpo2KrgP\nhT8PPVkwRUT/GsD/B2A/TnHDn0aDp481NW/LIFNARBcD+B9oROYrAB4wxnyWiC5AwzteDGAvgA8b\nY062b6Q6ENGvAfhvxpgPddMcmmP9ZvOv8wDcZ4z5PBGdhS5ZSwBARJcC+CsAfQBeAfD7aK4rdM8c\nFqBhLC8wxow3j3XbfbgLwC1oZAbuBfC/o8HJF/o89KShL1GiRIkSp9CT1E2JEiVKlDiF0tCXKFGi\nRI+jNPQlSpQo0eMoDX2JEiVK9DhKQ1+iRIkSPY7S0JcoUaJEj6M09CVKlCjR4ygNfYkSJUr0OP5/\n2wpE3LU2tdUAAAAASUVORK5CYII=\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "JueFNnm55HwO",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "pd.crosstab?"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Ix55K8bk6UD9",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "pd.cut?"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "lOtYpPvN7xQ4",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "#!pip install pandas==0.23.4"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "VUY5v2bZ6Fgc",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# Create bins for all features\n",
+        "age_bins = pd.cut(df['age'], 5, precision=0)\n",
+        "weight_bins = pd.cut(df['weight'], 5, precision=0)\n",
+        "exercise_bins = pd.cut(df['exercise_time'], 5, precision=0)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Uy0aD6cY5zZ1",
+        "colab_type": "code",
+        "outputId": "71a2903f-60f4-4f6a-f860-667e9181b3af",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 233
+        }
+      },
+      "source": [
+        "# People seem to get heavier as they get older\n",
+        "weight_age_ct = pd.crosstab(age_bins, weight_bins, normalize='columns')\n",
+        "weight_age_ct"
+      ],
+      "execution_count": 87,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th>weight</th>\n",
+              "      <th>(100.0, 129.0]</th>\n",
+              "      <th>(129.0, 158.0]</th>\n",
+              "      <th>(158.0, 188.0]</th>\n",
+              "      <th>(188.0, 217.0]</th>\n",
+              "      <th>(217.0, 246.0]</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>age</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>(18.0, 30.0]</th>\n",
+              "      <td>0.213333</td>\n",
+              "      <td>0.256716</td>\n",
+              "      <td>0.189922</td>\n",
+              "      <td>0.189944</td>\n",
+              "      <td>0.132075</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(30.0, 43.0]</th>\n",
+              "      <td>0.277333</td>\n",
+              "      <td>0.185075</td>\n",
+              "      <td>0.189922</td>\n",
+              "      <td>0.173184</td>\n",
+              "      <td>0.132075</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(43.0, 55.0]</th>\n",
+              "      <td>0.208000</td>\n",
+              "      <td>0.185075</td>\n",
+              "      <td>0.189922</td>\n",
+              "      <td>0.145251</td>\n",
+              "      <td>0.150943</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(55.0, 68.0]</th>\n",
+              "      <td>0.141333</td>\n",
+              "      <td>0.211940</td>\n",
+              "      <td>0.174419</td>\n",
+              "      <td>0.245810</td>\n",
+              "      <td>0.169811</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(68.0, 80.0]</th>\n",
+              "      <td>0.160000</td>\n",
+              "      <td>0.161194</td>\n",
+              "      <td>0.255814</td>\n",
+              "      <td>0.245810</td>\n",
+              "      <td>0.415094</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "weight        (100.0, 129.0]       ...        (217.0, 246.0]\n",
+              "age                                ...                      \n",
+              "(18.0, 30.0]        0.213333       ...              0.132075\n",
+              "(30.0, 43.0]        0.277333       ...              0.132075\n",
+              "(43.0, 55.0]        0.208000       ...              0.150943\n",
+              "(55.0, 68.0]        0.141333       ...              0.169811\n",
+              "(68.0, 80.0]        0.160000       ...              0.415094\n",
+              "\n",
+              "[5 rows x 5 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 87
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "qF81QhyWPL-m",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 291
+        },
+        "outputId": "a48b4c9d-4e77-43d4-b94c-3a3de9b68549"
+      },
+      "source": [
+        "weight_age_ct.plot()"
+      ],
+      "execution_count": 88,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5736505f60>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 88
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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rhgwZwnfffVeknpRWlkgejoy0bFUyVmdLatfTnWSswujfSL+MEXlF8CjSym+++Sa9evXC\n09MTgBkzZvDOO+/g7u5Ou3btaN++fYVLGm/YsAErKytSUlJ49tlnWbduHS+++CIbN25k4sSJTJs2\njZMnT/LCCy9w+fLlIhuxSCQSzQk4FqWTyViF0T+nrwU0lVa+z5w5c4iLi+Onn35Sn6tTpw6//vor\noJrGcXBwUE+d3Ce/NLORkdFjyxnfr2tubs7zzz+Pj48PL774IqtWrWLv3r2ASmY5PT2d27dvq+f8\n79eV0soSiWbcT8Zq5qR7yViFkUM7DdBUWhlg5cqV7Nu3j40bNxYYOScmJqojcVauXEmvXr2oU6dO\ngbqlSTNv3bqVmTNnamxzdnY2t2/fBlRTTf/88w8uLi6Aal/dQ4cOAXDlyhXS09Np1KhRgfqlyTxL\nJJKCBJ2PI/VOBu5PaHf/W02QTl9DBgwYwLFjx9THnp6ejBo1ikOHDmFtba0WRHv99de5desWHh4e\nuLu7M3fuXEDlXF1cXGjVqhV79uzhm2++Ubc1ZMgQoqKiAFi8eDFLlizB0dGR+Ph49d61QUFBRW4S\n97G3t+e9995jzZo1WFtbExAQQEZGBgMHDsTV1RV3d3esrKx49dVXAfj666/55ZdfcHNzY+zYsaxZ\nswZFUYiKilIvRBsZGbF8+XIGDhxImzZtGD16NM7Olb9rmUSi66iTsRrVwL5dQ22bUzaaSHFW5ktK\nKxfPuHHjRGxsrNb6L8yECRPEX3/9Vew1Xfh9SSSVRVRgolj+2iFx8XC4Vu1ASiuXL9qWVl6/fn2R\nKRhtMW7cOI4cOYKZmZm2TZFItI6uJ2MVRi7kPgRSWlnFhg0btG2CRKITJN9WJWO1H2Cns8lYhdFo\npK8oyiBFUa4pihKoKMqMYq6/rijKJUVR/BRFOaYoStu88/aKoqTlnfdTFOXH8v4AEolEoi0uekfo\nfDJWYcoc6SuKYgisAPoDEcAZRVF2CCEC8hX7XQjxY175YcASYFDetSAhhHv5mi2RSCTaJSMtm4Dj\nUTh20u1krMJoMtLvAgQKIYKFEJnAJmB4/gJCiOR8h7UAUX4mSiQSie5x5bgqGcutn+6HaeZHE6dv\nBYTnO47IO1cARVHeUhQlCPgCeDvfJQdFUc4rinJEURTPx7JWIpFIdIDcnFwueKuSsSztig+l1lXK\nLXpHCLFCCNECmA58nHc6GrAVQrQH3gN+VxSlyDekKMpkRVF8FUXxjYuLKy+TyhVNpZUnTpyIg4OD\nWs7Yz88PUAmbPfXUU7i5ueHs7KzOzi3M2bNnadeuHY6Ojrz99ttqvZySuHr1Kh4eHpiamhZR2ly6\ndCnOzs64uLgwduxYdXLZoUOH6NChA+7u7qWKtS1cuBBHR0datWqlzkNIS0vD3d0dExMTdfKXRFLd\nuJ+MpW+jfKDsOH3AA9iX73gmMLOU8gZAUgnX/gU6ldafrsbpL1++XCxbtkx9fPDgQbFjxw4xdOjQ\nAuVKil9fsGCB+PDDD4UQQsTGxop69eqJjIyMIuU6d+4sTp48KXJzc8WgQYPE7t27S7Xr1q1bwsfH\nR8yaNUt8+eWX6vMRERHC3t5e3Lt3TwghxKhRo8Svv/4qhBDCyclJ/Z2uWLFCTJgwoUi7/v7+wtXV\nVaSnp4vg4GDRvHlzkZ2drb5uZ2cn4uLiirVJF35fEklF8teiM2LdxydETk6utk1Rg4Zx+pqEbJ4B\nnBRFcQAigTHA8/kLKIriJIS4kXc4FLiRd74RcEcIkaMoSnPACQh+9FsULPZZzNU7Vx+niSK0rt+a\n6V2ml1pGU2nlklAUhZSUFIQQpKamUr9+fbWa5n2io6NJTk6mW7duALz44ots27aNwYMHl9iupaUl\nlpaW7Nq1q8i17Oxs0tLSMDY25t69e2oJZU2klbdv386YMWMwNTXFwcEBR0dHfHx88PDw0PgzSyRV\nkZjgJG6FJNNrTEsMdHBnrLIo0+kLIbIVRZkC7AMMgdVCCH9FUeaiurPsAKYoivIEkAUkABPyqvcC\n5iqKkgXkAq8LIe5UxAepSB5WWvmjjz5i7ty59OvXj0WLFmFqasqUKVMYNmwYzZo1IyUlhT/++KOI\nqmVkZCTW1g9Cvx5HztjKyor3338fW1tbatSowYABAxgwYACg0v4ZMmQINWrUoE6dOpw6dapI/cjI\nSPXN53FtkUiqEn56loxVGI2Ss4QQu4Hdhc59mu99sdtACSH+Bv5+HAMLU9aIvCJ4GGnlhQsX0qRJ\nEzIzM5k8eTKLFy/m008/Zd++fbi7u+Pt7U1QUBD9+/fH09OzRD2dxyUhIYHt27cTEhKChYUFo0aN\nYv369YwfP56lS5eye/duunbtypdffsl7772n3uFLIpGUTPLtNILPx9F+gK3eJGMVRsowaMDDSCs3\nbdoURVEwNTXlpZdewsfHB4Bff/2VZ555BkVRcHR0xMHBgatXC05TWVlZFdhY5XHkjA8ePIiDgwON\nGjXC2NiYZ555hhMnThAXF8eFCxfo2rUrAM899xwnTpwoUl9KK0skRbl4WP+SsQojnb4GPIy0cnR0\nNKBaIN+2bVuxcsa3bt3i2rVrRfT0mzZtqp5uEULw22+/qaWVly9fzvLlyzW22dbWllOnTnHv3j2E\nEBw6dIg2bdpQr149kpKSuH79OgAHDhygTZs2ReoPGzaMTZs2kZGRQUhICDdu3KBLly4a9y+RVDUK\nJmPpr+6U1N7RkPvSyk888QSgkla+evUqqampWFtbs2rVKgYOHMi4ceOIi4tDCIG7uzs//qhSnvjk\nk0+YOHEi7dq1QwjB4sWLadhQJcOaP7Tz+++/Z+LEiaSlpTF48GD1Iu7Vq1fp0aNHEbtiYmLo1KkT\nycnJGBgYsGzZMgICAujatSsjR46kQ4cOGBkZ0b59eyZPnoyRkRG//PILzz77LAYGBtSrV4/Vq1cD\nsGPHDnx9fZk7dy7Ozs6MHj2atm3bYmRkxIoVKyp8py+JRJe5cjyKrHT9S8YqjCLKiAOvbDp16iR8\nfX0LnLty5Uqxo9HK5Ny5cyxdupR169Zppf8nn3ySLVu2YGJiopX+C2Nvb4+vr6/6xpUfXfh9SSTl\nSW5OLus/OYV5AzNGTOugbXOKRVGUs0KITmWVk9M7GqJtaeV//vlHJxz+/eSsrKwsuaeupNoQ7Heb\nlDvpej/KBzm981BIaWXVovb9qSiJpLrgdzCMOo1qYO+qBztjlYEcqkkkEkkp3E/Gcutro5fJWIWR\nTl8ikUhKwe9geF4yVhNtm1IuSKcvkUgkJaBKxorF2bMZJmZVYzZcOn2JRCIpgaqQjFUY6fQ1RFNp\n5ZJki8PCwvDy8qJ9+/a4urqye/fuIn0A7N27l1atWuHo6MiiRYvKtGvJkiW0bdsWV1dX+vXrR2ho\nqPpaSTZ6enqqpZ+bNWvG008/XWzba9euxcnJCScnJ9auXas+7+XlRe3atSkcWiuRVCUy85KxWnTU\n72SsImgixVmZL32XVi5JtvjVV18V33//vRBCJVtsZ2dXpI/s7GzRvHlzERQUJDIyMoSrq6vw9/cv\n1S5vb29x9+5dIYQQ33//vRg9enSZNubnmWeeEWvXri1yPj4+Xjg4OIj4+Hhx584d4eDgIO7cuaO+\n3rt3b3HmzJli29SF35dE8ricPxAqlr92SNy6maRtUzSCcpRW1iliPv+cjCvlK61s2qY1TWbNKrWM\nptLKJckWayJn7OPjg6Ojo1qeYcyYMWzfvp22bduWaJeXl5f6fbdu3Vi/fn2ZNt4nOTkZb2/vYjd0\n2bdvH/3796d+/foA9O/fn7179zJ27NgS25NIqgq5Oblc9I6gqWNdvdsZqyz0zulrg4eRVi5Jtnj2\n7NkMGDCA7777jrt373Lw4MEidSMjI7GxeZD8YW1tzenTpzW2c9WqVaVq7xdm27Zt9OvXr1ilz+Js\nkdLKkurC/WSsnqOdtG1KuaN3Tr+sEXlF8DDSyiXJFm/cuJGJEycybdo0Tp48yQsvvMDly5fLLat1\n/fr1+Pr6cuTIEY3rbNy4kVdeeaVc+pdIqhIXDlWdZKzCyIVcDdBUWrk02eJVq1YxevRoADw8PEhP\nTy+yx+yjyhkfPHiQBQsWsGPHDkxNTTX6TLdv38bHx4ehQ4cWe11KK0uqKzHBScQEV51krMJIp68B\nmkorlyZbnF9a+cqVK6Snp9OoUaMC9Tt37syNGzcICQkhMzOTTZs2MWzYMABmzpzJ1q1bi/R5/vx5\nXnvtNXbs2IGlpaXGn2nz5s08+eSTmJkVH5UwcOBA9u/fT0JCAgkJCezfv5+BAwdq3L5Eoq9UtWSs\nImiy2luZL12N3nn55ZfFgQMH1Mc9e/YUDRs2FGZmZsLKykrs3btXCCHEli1bhIuLi3B1dRW9e/cW\nQUFBQghVxE737t2Fq6urcHNzE/v27RNCCBEZGSkGDx6sbnfXrl3CyclJNG/eXMyfP199fujQoeLE\niRNF7OrXr5+wtLQUbm5uws3NTTz11FNl2iiEKvpmz549Bdo6c+aMmDRpkvp41apVokWLFqJFixZi\n9erVBcrK6B1JVSQp7p5Y8fohcfzvG9o25aFBw+gdrTv5wi9ddfpnz54V48eP11r/AwYM0FrfxSGd\nvqQqcvSv6+L7N7xFyp00bZvy0Gjq9OX0joZoW1p53759Wum3OLy8vAgODsbY2Fjbpkgk5UZmWjYB\nx6pgMlYh9C56R5tIaWUVhw8f1rYJEkm5c+VENFnpObg/of+a+aUhR/oSiaTak5uTywXv8CqZjFUY\n6fQlEkm1J9jvNinx6bg/YattUyoc6fQlEkm158KhMOo0NKuSyViFkU5fIpFUa9TJWP2qZjJWYaTT\n15D80sp+fn54eHjg7OyMq6srf/zxh7rc8uXLcXR0RFGUAhm3X375pVrO2MXFBUNDQ+7cuVOkn5CQ\nELp27YqjoyPPPfccmZmZpdp14MABOnbsSLt27ejYsSPe3t5FygwbNgwXF5cC57777jtat26Ns7Mz\nH374YbFtlyTzPG7cOOrXr8/mzZtLtU0i0QcuHArHpIYRrT2aatuUykGTuE5gEHANCARmFHP9deAS\n4AccA9rmuzYzr941YGBZfelqnH5+aeVr166J69evCyFUyVVNmjQRCQkJQgghzp07J0JCQoSdnZ2I\ni4srtq0dO3YILy+vYq+NGjVKbNy4UQghxGuvvaaWYy6Jc+fOicjISCGEEJcuXRLNmjUrcP3vv/8W\nY8eOFc7Ozupz3t7eol+/fiI9PV0IIcStW7eKtFuWzPOECRPEX3/9VaxNuvD7kkg0Iel2XjLWZv1L\nxioM5SWtrCiKIbAC6A9EAGcURdkhhAjIV+x3IcSPeeWHAUuAQYqitAXGAM5AM+CgoigthRCPHOx+\n9M/r3A5PfdTqxdLQpjaeo1uWWia/tHLLlg/KNmvWDEtLS+Li4rCwsKB9+/Zl9rdx48ZiJYqFEHh7\ne6v7mTBhArNnz+aNN94osa38/Tk7O5OWlkZGRgampqakpqayZMkSfv75Z7XuD8APP/zAjBkz1Do9\nxck3PIrMs0Sib1w6HAGKQjuvqrMzVlloMr3TBQgUQgQLITKBTcDw/AWEEMn5DmsBIu/9cGCTECJD\nCBGCasTf5fHNrlxKk1b28fEhMzOTFi1aaNTWvXv32Lt3L88++2yRa/Hx8VhYWGBkpLoXP6yc8d9/\n/02HDh3UzvyTTz5h2rRp1KxZs0C569evc/ToUbp27Urv3r05c+ZMkbaktLKkqnM/GcuxoyXm9atu\nMlZhNEnOsgLC8x1HAF0LF1IU5S3gPcAE6Juv7qlCdR9LqrGsEXlFUJK0cnR0NC+88AJr167VWCJ5\n586d9OjRQ705SXnh7+/P9OnT2b9/PwB+fn4EBQWxdOlSbt68WaBsdnY2d+7c4dSpU5w5c4bRo0cT\nHByMolT9RSyJ5D5XTkSTmZ6DW7+qnYxVmHJbyBVCrBBCtACmAx8/TF1FUSYriuKrKIpvXFxceZlU\nbhQnrZycnMzQoUNZsGAB3bp107itTZs2lbj7VIMGDUhMTCQ7OxvQXM44IiKCESNG8Ntvv6mfOE6e\nPImvry/29vb07NmT69ev06dPH0A1an/mmWdQFIUuXbpgYGBQbjLPEok+kJsr1MlYje2rdjJWYTRx\n+pFA/luhdd65ktgE3N9pW6O6QoifhRCdhBCdCssN6wKFpZUzMzMZMWIEL774IiNHjtS4naSkJI4c\nOcLw4cOLva4oCl5eXuqomLWcDV1DAAAgAElEQVRr16rLbt26lZkzZxapk5iYyNChQ1m0aBE9evRQ\nn3/jjTeIiori5s2bHDt2jJYtW6q3Tnz66afVUgrXr18nMzOThg0LxieXJvMskeg7IX5xqmSsflU/\nGaswmjj9M4CToigOiqKYoFqY3ZG/gKIo+fcUGwrcyHu/AxijKIqpoigOgBPg8/hmVz4DBgzg2LFj\nAPz555/8999/rFmzRh2G6efnB8C3336LtbU1ERERuLq6FtiZauvWrQwYMIBatWoVaHvIkCFERUUB\nsHjxYpYsWYKjoyPx8fFMmjQJgKCgoGK3NVy+fDmBgYHMnTtXbUtsbGypn+Xll18mODgYFxcXxowZ\nw9q1a1EUhaioKIYMGQKAkZERy5cvZ+DAgbRp04bRo0fj7Oz8iN+eRKJb+B0MVyVjuVX9ZKwiaBLi\nAwwBrgNBwEd55+YCw/LefwP4owrZPAw456v7UV69a8DgsvrS1ZBNbUsrjxs3TsTGxmqt/8LIkE2J\nvhIdnCiWv3ZI+B0K07Yp5QrlFbKZd2PYDewudO7TfO/fKaXuAmCBJv3oMvmllQ0NDSu9//Xr11d6\nnyUxbtw4Tpw48VBTWxKJrnA/GatN92qSjFUIvZFWFkJoPbpESiur2LBhQ4nXVAMOiUQ3SY5PI+hc\nHO79bDAx0xv3V67ohQyDmZkZ8fHx0qHoOEII4uPjS9x3VyLRNpcORwBUq2SswujFre7+wqguhnNK\nCmJmZoa1dfX9h5LoLpnpeclYHRpVq2SswuiF0zc2NsbBwUHbZkgkEj3myvH7yVjVL0wzP3oxvSOR\nSCSPQ4FkLIfqlYxVGOn0JRJJled+MlZ1k1woDun0JRJJlefCIVUyloOb7mX8VzbS6UskkipNTEgS\n0UFJuPatHjtjlYV0+hKJpEpz4VA4JmaG1TYZqzDS6VdjAqKSSU7P0rYZEkmFkXInnaBzcbT1tKq2\nyViFkd9CNSQi4R4Ldl1hz+UYLM1NmTvcmUEuchQkqXpczEvGcq3GyViFkSP9akR6Vg7LDl6n39dH\n+PdaHG/2aUHD2qa8vv4ck3/zJSYpvexGJBI9ITM9m4CjkdU+GaswcqRfDRBCsM8/hnn/XCEyMY0n\nXZsya0gbmlnUYGr/lqw6FsLSA9fpv+QIHw5uzbgutnLBS6L3PNgZq3onYxVGOv0qzvVbKczZ6c/x\nwHhaNzFn0+RudGveQH3d2NCA13u3YLBLEz7aeplPtl1m2/lIFj3TDqfG5lq0XCJ5dHJzBRe9w2na\nQiZjFUY6/SpKUloW3xy8wdqTN6ltasTc4c4838UWI8PiZ/TsGtRi3aQubDkXybxdAQz59ihv9HHk\nLa8WmBpVvpS0RPI4hFyII/l2Ot2fddS2KTqHdPpVjNxcwV9nw/li7zXu3MtkbBdb3h/Qivq1TMqs\nqygKz3a0pk+rRsz7J4BvD91g18UoFj3rSmf78t3IXSKpSC4clMlYJSEXcqsQ58MSGPH9cab/fQmH\nhrXYOaUnn49op5HDz0+D2qYsG9OeNS91Jj0rl1E/nmTW1ksyvFOiF9wKSVYlY3nJZKzikCP9KkBs\nSjpf7L3G5rMRWJqbsuw5d4a7N3vsTWf6tLLkwHu9WLL/OquPh3Aw4JYM75ToPBcOhamSsXrIv9Pi\nkE5fj8nMzmXtiZt8c+gGGdk5vNGnBW95OVLbtPx+rTVNjPj4ybYMc2/GjL8v8fr6cwxo25i5w11o\nUleGwUl0i5Q76QSei8OtGu+MVRbyW9FT/rsex5yd/gTF3cWrVSM+fcoZh4a1Kqw/V2sLtk/pIcM7\nJTrNJZmMVSbS6esZYfH3mL8rgP0Bt7BvUJPVEzvRt3XjSuk7f3jnrK2X+GTbZbafj2ShDO+U6ACZ\n6dn4H4uihUzGKhXp9PWEtMwcfvg3kB//C8bIQGH6oNa83NNeK+GUdg1qsX5S1wLhnW/2ceRNGd4p\n0SJXTkSTmZaNu0zGKhXp9HUcIQS7LkXz+a4rRCWl87R7M2YMbqP1+fTC4Z3fHLrBPzK8U6Il7idj\nNWkuk7HKomqFbGaladuCcuVqTDJjfznFlN/PY1HThL9e92DZmPZad/j5keGdEl3g5oXbJN9Ox/0J\nuTNWWVQdp3/3NnzbAY58ATn67XCS7mXx2fbLDPnmKFdjUpj/tAs7/9dTp0fQ98M7X+npwCafMJ74\n+gh7L0dr2yxJNcHvUJgqGctdf5OxolKjuHz7coX3U3WcvmIAdh5weAH87AXRF7Rt0UOTkyv4/XQY\nfb46zLpToYzvZse/7/dhfDc7DPUgQuZ+eOe2t3pI9U5JpXHrZjLRgfqdjOUd5s3InSP56NhH5Irc\nCu1LI6evKMogRVGuKYoSqCjKjGKuv6coSoCiKBcVRTmkKIpdvms5iqL45b12lKfxBahZH0auhuc2\nwN1YleM/NA+yMyqsy/LkbOgdhq84xqytl3BqbM4///Nk7nAXLGo+XDatLnA/vHPG4NYcuR5H/yVH\nWHcqlNxcoW3TJFUQfd4ZKysni8U+i3nn8DtY17Zmed/lGCgVOxZXhCj9H1FRFEPgOtAfiADOAGOF\nEAH5yngBp4UQ9xRFeQPoI4R4Lu9aqhCitqYGderUSfj6+j78J8lPWgLsnQUXfodGrWH4CrDu9Hht\nVhC3ktNZtOcqW89H0qSOGbOGtuEp16aPnU2rK4TG32XW1kscD4ynk109Gd4pKVdS7qSz7uOTuPW1\npsdIJ22b81BEpETwwZEPuBx/medbP8+0TtMwMXz0QZ6iKGeFEGU6Ok1uKV2AQCFEsBAiE9gEDM9f\nQAhxWAhxL+/wFKDdzIga9WDEDzBuM2SkwKr+sP9jnVrozcjO4ccjQfT96l92XYxmipcj3u/3Zpjb\n48sn6BL3wzu/GuVGYFwqQ749ytID18nIztG2aZIqwP1krHZ6lox1MPQgo3eOJjQ5lKV9ljKz68zH\ncvgPgyYhm1ZAeL7jCKBrKeUnAXvyHZspiuILZAOLhBDbHtrKR8WpP7x5Cg58Cie+g6u7YfhysOte\naSYUx+FrsczdGUDI7bs80aYxnzzZBrsGFZdNq20URWFkXnjnfBneKSkn1MlY7RtRp0ENbZujEZk5\nmXzt+zW/X/0dlwYufNH7C2zMKzfiqFwnjxRFGQ90Ar7Md9ou75HjeWCZoigtiqk3WVEUX0VRfOPi\n4srTJDCrA08tgxe3Q24W/DoEdn8IGanl248G3Lx9l0lrzvDSr2dQgDUvdWblhE5V2uHnp6EM75SU\nI1dPqpKx3PQkTDM8OZwX9rzA71d/Z3yb8fw2+LdKd/ig2Zy+BzBbCDEw73gmgBBiYaFyTwDfAb2F\nELEltLUG+EcIsbmk/splTr8kMlLh0Fzw+Qks7GDYd9C8d8X0lY+7GdmsOBzIyqMhGBsqvPOEExO7\nO2BiVHWCpx6We5nZavXOhrXl5uxVkaxbt8gIDKyQtnNzBVu3Z1KjhsKQQbof7HD21ll+8/8NRVGY\n6DwBd8v2xZYzNDenhqvrI/Wh6Zy+Jk7fCNVCbj8gEtVC7vNCCP98ZdoDm4FBQogb+c7XA+4JITIU\nRWkInASG518ELkyFOv37hJ6A7VPgThB0nAj954JZ3XLvRgjBjgtRLNx9lZjkdJ7pYMWMQa2xrKM7\nyVXa5mJEIjP+vkRAdLJU76xC3PXxIeKNN8m9e7dC2o9r6MYll8m4+K/EMu58hfShDczcXHH4449H\nqltuTj+vsSHAMsAQWC2EWKAoylzAVwixQ1GUg0A74H42TpgQYpiiKN2Bn4BcVFNJy4QQq0rrq1Kc\nPqgWdQ8vgJMrwLwpPPWNag2gnPCPSmL2Dn/O3EygnVVdZg9zpqNdvXJrvyqRlZOrVu80MTSQ6p16\nToq3N5HvTsXYxoYmn3yMYlL+I/HdO1K4e1fw7HPmOvt3EnM3hhXnVxCaEspg+8GMajkKI8PSl1EN\natbErHXrR+qvXJ1+ZVJpTv8+Eb6w/S2Iuwpuz8Ogz1XRP49Iwt1Mvj5wjd9Ph2FR04QPB7ZiVCcb\nvUiu0jYyvFP/Sdy6jeiPP8bM2Rmbn37EqF75D3Ru3Uxm8yJfeo5ywq2fbs7n7w3Zy+yTszFUDFnQ\ncwF9bPpUeJ/S6T8M2Rkq+YZjS6FWQ3hyKbQe+lBN5OQKfvcJ4+v910hJz+aFbnZMfaIldWsaV5DR\nVRMhBH+fi2T+rgDuZmRL9U49Iv7XNcQuXkyt7t2x/u5bDGpVTIDC/lX+hF66zYSFPTCpoVuakenZ\n6Xxx5gv+uv4Xbo3c+LLXlzStXTlrVdLpPwrRF2DbW3DrErg8C4O/UN0EyuB0cDyzdwZwJToZj+YN\nmD3MmVZN5Aj1cbidmsG8fwLY7hdFi0a1ZHinDiOEIG7ZN8T/9BPmgwbR7IvFGFTAlA6okrHWf3yS\ndn2t6aljyVghSSG8f+R9ridc5yWXl/hf+/9hbFB5g77yTM6qPjR1g8mHwesjCNgBK7rC5S1Qwo0x\nOimNtzee57mfT5GclsX34zrw+6tdpcMvBxrWNuWbMe35VYZ36jQiJ4eYz2YT/9NPWIwejdXXX1WY\nwwe49G8EQgid2xlrV/Auxvwzhth7sazot4L3Or5XqQ7/YZAj/ZK4FQDb34So89D6SRi6BMxVO1Sl\nZ+Ww6lgIy70DyRGC13u34I3eLahhIqcgKgIZ3qmb5GZmEvXhdFL27qXBa6/R6N13KjSbPDM9m7Uz\nT2Dbtj4DX3WpsH4ehvTsdBb5LOLvG3/T3rI9X/T6gia1mmjFFjm9Ux7kZMPJ5XD4czCugRi0kEPG\nfZm3+wqh8fcY5NyEj4a2waZ+TW1bWi2Q4Z26Q+7du0T8723unjiB5fTpNHhpYoX3efFwBEf/uM6z\nH3akSfPyD7F+WIKTgpn27zQCEwN5pd0rvOX+FkYG2ltjkE6/PLl9g/TNr2MW44t3jjs/132bt4b3\nwtNJf7W79RUZ3ql9shMSCH/tddL9/Wk6bx4Wz4yo8D5zcwUbPjtFTXNjnv1Q++KJO4N2Mu/UPMwM\nzfjc83N6WvXUtklyTr+8SM3IZuGZbNzCp7JITKSX8VU2Zr2DZ/LuEuf6JRXH/c3Z90/thatNXT7Z\ndpnRP53kxq0UbZtWLciKiSF0/AtkXL2K9bffVIrDB7h58TbJcWm4aXn/27TsND45/gmzjs2ibYO2\n/PXUXzrh8B8G6fRLIDdXsOVcBF5f/ctPR4IZ5m7DpPe/wGjKSZSm7rDzbfhtOCSEatvUaolU76x8\nMkJCuPn882THxGCz8hfM+/WrtL79DoZh3sCM5u5lR9NVFEGJQYz9ZyzbA7cz2XUyKwespHGtxlqz\n51HRrSBXHeFSRBKf7bjMubBE3Gws+OXFTrjbWORdbQ4v7oCzv6rUO7/3gP5zoNMkMJD30Mokv3rn\n/c3Zd12KZuEz7WR4ZzmT5u9P+KuTAbD9bS01nJ0rre/YUNXOWD1GOmJgqJ3/sW2B2/j89OfUMKrB\nj/1/pHsz7Sr1Pg5yTj8f8akZfLX/GpvOhNOglgkfDmrNyA7WJc8XJ4arRvxB3mDbXSXb3KCIiKik\nkjh8LZaPt14mMjGNcV1tmT64NXXMdDNsTp+4e9qHiDffxKBuHWxXrcLUwaFS+9+/yp+bl24zUQvJ\nWPey7rHg9AJ2BO2gc5POLPZcTKOaurmWJxdyH4LsnFzWnwplyYHr3MvMYUJ3e955wkkzhyEE+G1Q\n7dSVkwF9P4Zub4KBDN/UBnczsll6QIZ3lhcphw4ROfU9jG1tsF25EuMmlRuOmJqQzrqPtJOMdSPh\nBtOOTONm0k1ed3ud11xfw1CH/6/lQq6GnAi6zdBvjzF7ZwCu1hbseceTT55sq/kIUVGg/Xh46zQ0\n91Lt0LVqAMRerVjDJcVSy1Ruzl5eJG7dRsTb72DaujV269ZVusOHfMlYfSovGUsIwZYbW3h+1/Mk\nZyTz84CfedP9TZ12+A9DtR3pRyam8fmuK+y6FI11vRp8PLQtA50bP15yiRBwaTPs+QAy70KfGdD9\nbTCUUwzaQIZ3PjqVpaNTGpnp2fw26wTWreszaHLlJGPdy7rH3FNz2RW8i65Nu7LIcxENa2hv8fhh\nkNM7JZCelcPP/wXz/b+BCAFv9nHktd7NMTMux7t4aizsfh8CtqukHYavgCbtyq99yUMh1Ts1RwhB\n3NJlxP/8c4Xr6JRFZSdjXbtzjfePvE9YShhvuL3Bq+1e1avRvXT6hRBCsD/gFvP+CSAiIY0h7Zow\na0gbrOtVYDat/zaV809LAM/3wXMaGOn+Lj9VEaneWTYiJ4eYOXNJ/PNPLEaPpslnn6IYauf7qcxk\nLCEEm29sZrHPYsxNzPmi1xd0btK5QvusCDR1+tUiZDMwNoU5OwM4euM2LRvX5vdXutLdsRIe2Zyf\nBodesGc6HFkEV3bC0yugWfFbpUkqDhneWTq5mZlEffAhKfv2VYqOTlncT8byeLpio+FSM1OZe3Iu\ne27uwaOpBws9F9KgRoMK7VPbVOmRfnJ6Ft8evMGaEzepaWLIe/1bMr6bHUbaiPW9tgf+maqa+unx\nNvSeAcZSN0ZbyPDOB2hDR6cstn59jpT4dMbP61ZhsflX4q/w/pH3iUiNYIr7FCa1m4SBor+xLdV6\npJ+bK/j7XASL914j/m4GYzrb8P6AVjSobao9o1oNBlsPVXTPsaVw5R/VXL9tV+3ZVI3xamXJ/qm9\nWHLgOr8eD+HglVvMGebCIBftKCRqiwI6OgsXYjHiaW2bRGxoMlE3EissGUsIwZ/X/uSLM19gYWrB\nqgGr6NRE+3o+lUWVG+n7hSfy2Q5/LoQn0t7WgjnDnHG1tii7YmUSeAh2vgNJEaqY/r4fg4lU6tQW\nF8ITmbHlEleqmXpnVkwMYZNeISs8HKtlSzHv21fbJgFwYLU/IRcrJhkrJTOFOSfnsO/mPnpY9eDz\nnp9T36xqTO9Vu4XchLuZLNxzhT99I2hkbsqMQa0Z0d5Kd8PzMlLgwGfguwrqOcCw78DBU9tWVVuq\nW3hnRkgIYZMmkZuUjPUP31OrSxdtmwTkS8bysqbnqPJNxgqID+D9I+8TlRrF/9r/j5dcXtLr6ZzC\nVLvkLAF4X43jtV7N8Z7Wm2c7liKfoAuYmsOTS2DCP4CAtU/Crmmqm4Gk0qlO6p1p/v6EjhuPSM/A\n9re15e/w05PhxgE4OAdO/6zKWdGQitgZSwjB71d+Z/zu8WTmZLJ64Gq9n79/HKrMSB9UOyzVNNHD\nZYrMu+A9H079AHWt4alvwLHyFAwlBRFCsPlsBAt2X6ly4Z0VoqOTlghhJ+HmMQg9rtprWuSCYggi\nB2rUgy6vQZfJUKvkyJgHyVj1GDS5fPJakjOTmX1iNgdCD9DLuhfze8ynnlm9cmlb16h20ztVgrDT\nsP0tiL8B7V+AAfOhho6tR1Qj8m/O7mhZW+/DO8tNR+feHQg9oXLwN49CzGVAgKEJWHcGux5g3wOs\nu8Cty3BsGVzbBUY1oMOL0H0KWBTVxb/0bwT/bSq/ZCz/2/5MOzKNmLsxvNvhXV50frFKj+6l09dX\nstLh34Vw4luo3RieXAatBmnbqmpN/vDOsV1smT6oFRY19SvJLnHLVqI/+QQzF2dsfvwRo3oPMdpN\njVM5+NDjcPM4xPqrzhuZqZy8fU+Vo7fuBMY1im8j9qrqb/riHyq5knYjocc70Fgl0ZybK/j9s1OY\n1TZm5PTHi6QRQrDhyga+Pvs1DWs05MteX+Ju6f5YbeoD0unrO5FnYfsUiA0A1+dg0CKoqb+jTH3n\nvnrnryduYlHDmJlD2vBsByutJjBpykPr6KTcgtBjKgd/8xjcvqY6b1wTbLqqRvF2PcGqAxg9ZBh0\nUiSc+h58f4Wsu+A0AHpOJTjBkT0/Xmbgqy44drR8tA8KJGUk8enxT/EO96aPdR/m95xPXVPt76db\nGUinXxXIzoSjX8HRr1XzokO/hrbDtW1VtSYgKpmPt13iXFgiXezrM3+ECy11VMdHYx2dpMi8UXze\nnHx8oOq8SW2w7ZY3XdNTlUleXuKB9+7AmVVw+ke4d5utqctIUWwY/3kfDIwfbV3uUtwl3j/yPrH3\nYpnacSovtH1BL27K5UW5On1FUQYB3wCGwEohxKJC198DXgGygTjgZSFEaN61CcDHeUXnCyHWltaX\ndPrFEHMJtr0JMRdVTn/I11BbNzdyqA7k5gr+OhvOwj1XSU3PZpKnA+/0c9KpIIICOjrPPUeTTz95\noKOTGPZgFB96DBJuqs6b1gG77g/m5Ju4gWEFf6asNGIP/MlfO2zoYf4r7nbXVBnr7UZrrFMlhOC3\ngN9YdnYZljUt+bL3l7g2cq1Yu3WQcnP6iqIYAteB/kAEcAYYK4QIyFfGCzgthLinKMobQB8hxHOK\notQHfIFOqKIqzwIdhRAJJfUnnX4J5GTB8W/gyGLVCGzwF6p50Wo0ktE17tzNZFFebkizumZ8NsyZ\nAW0fU567HCioozOZRi8OQ1EvvB6HpDBVQTOLBw7erodKCVYLqpL3k7EmjL+N6ZmlcOsSmDcDj7eg\n4wRVeHMJJGUk8fGxj/k34l+8bLyY12NetZnOKUx5On0PYLYQYmDe8UwAIcTCEsq3B5YLIXooijIW\n1Q3gtbxrPwH/CiE2ltSfdPplEHtVFeET6QuthsDQJVBH7gylTXxv3uHjbZe5GpNC39aWzBnmjE19\n7WRY56amEvHGq9w944flYAcaWIdASpTqYs0GqpG8vafKyVu21fq+zqkJGaz76ATt+ljTc7STapE3\n6JAq4ufmUTCrC51fha6vF3m69Yv148P/PiQuLY5pHacxrs04rd9wtUl5au9YAeH5jiOA0gRjJgF7\nSqlrVbiCoiiTgckAtrZFQ7kk+bBsDZP2qxbDvOfDiq4w6HNwHydH/Vqik319dv6vJ2uO32Tpwev0\nX3qE//V14lXP5pgYVbBTFQLirkHoMbID/iV8pS/pt6Fp10QsmmWDbY8Hc/KNWuvc34g6GatvXjKW\nooDjE6pXxFk4vlS1pnVyuWqHOo8p5NazY63/Wr499y2NazVm3eB1uDSsnE1WqgLlOmGnKMp4VFM5\nvR+mnhDiZ+BnUI30y9OmKomBIXT/n2qkv32KauR/eYsqqcvCRtvWVUuMDQ14tVdznnRrytydAXy5\n7xpbzkUwb7hL+cp45+ZC3BXVNE3oMVW8/N04su4ZEPZfY7JSDbB+92nMn30JGjjqnJPPT2Z6Nv5H\nI2nevhF1GhYT6mndEZ5bD7dvqMI9z/1Gwrk1fOzQhv9yknjC9gnm9JhDHZM6lW+8HqOJ048E8nsS\n67xzBVAU5QngI6C3ECIjX90+her++yiGSoqhQQuYuAvOrISDs+H7btB/LnR8SeuP7dWVpnVr8MP4\njhy+Fstn2/15fuVpnnZvxqyhbbA0fwQRt9wcVYLTzbw4+dATkHZHda2uDbToR4Zpa8K+2Epu1j1s\nVuuOjk5ZXDsVQ8a9bNyfKOPpvqETDPuO8+2G88GxWdzJTmRmfAJjlZsokX6q6SodvrnpGprM6Ruh\nWsjth8qJnwGeF0L45yvTHtgMDBJC3Mh3vj6qxdsOeafOoVrIvVNSf3JO/xFJuAk73oaQI6p/gmHf\nQf1ySLGXPDLpWTl8fziQH48EY2pswAcDWzGuqx2GpWlC5WSrorTuL7qGnYD0JNU1C7sHiVD2PaGe\nHWn+/oS/OhkAm19+poazcyV8ssdH5O2MpUkyVq7IZfXl1Sw/v5xmtZvxZdfPcA4+rpItuRsLzTpA\nz6nQeqhWFqJ1hfIO2RwCLEMVsrlaCLFAUZS5gK8QYoeiKAeBdkB0XpUwIcSwvLovA7Pyzi8QQvxa\nWl/S6T8GQsC5tbDvY5XmSb9PVZonctSvVYLjUvlk+2WOB8bTzqouC0a4PJD7zsmCKL8HyVBhpyAz\nT+StfosHiVD2PVS6TPmoEB2dSiLkQhy7f7jEgFeccerUuMRyd9LvMOvYLI5HHmeA3QBmd5+NuUle\nNE9WOlz4HY5/Cwkhqums7m+D25iHTxqrAsjkrOpMUgTsfBcCD4BNNxi+XPWILNEaQgh2Xoxm4c4L\nWN27wmt20fQxvYFxpI8qMxWgYcsHo3i7HqVGZZWbjo6W2Pr1OZLj03hhnkeJG6WcvXWWD498SGJG\nIh92/pDRrUYXH52TmwMB2+H4MpXYW+0m0O0N6PQymFWf+f5q5/QzszPx370eYdMU0bghaGNLRF1C\nCNVmLad/VI0mO7wAziOq9eNveVDPrB7Wta0xMdRQeycrXRVem7fwKsLPoGSnARCEDTj0pHnHgSj2\nPaC2ZvIDiVu2Ev3xx5i1c3l4HR0dIC4shT8/P0P3Zx1p37/ofH6uyGXlpZWs8FuBjbkNX/X+itb1\nW5fdsBAQ/K/K+Qf/C6Z1ofPL0PUNMC/5aaKqUO22S0yKCcXswy8ByDSEmPoQVV8hqgFE1leIaqAQ\nVR/SzKrZgk/D2qqfkf+oXpLHxkAxoGmtptiY22BXx07909bcFmvT+phEX3gwJx9xBnIyAAUau6B0\nnAB2Pbhi2o4Ze6O4cCURj4wGzLOsgWPtsvt+aB0dHcTvUBjGpoa07dmsyLX4tHhmHp3JyeiTDLYf\nzKcen1LbRIMvBlSLuS28VK+o86pY/+PfwMnvwX2sauqnQcVutK4PVJ2RftpdLhzdgkF4NIZhMRiE\nR2MQHoNBZCxKbq66XG79uuTaNCHHtim5Nk3U76v004EQqpR7n58g8x64jgGXZyo+xb6KIYTgdtpt\nwlLCCEtWvUKTQ0nJerDRiiIETbNzsMnOxs64Drb1HLFt2hlbh75YN3LG1PDBXHNOrmDTmTAW77lK\nWlYOr3o25399nahhUvRpTGMdHR2nSDJWPs7EnGH6f9NJykhiRtcZjHQa+fjJVvFBcOI78PsdcrOg\nzTDo+a5KR6iKUe2md0pCZGWRGR5BZkgwmSEhZASHkBkSQmZwMDlJSepyiokJJna2mDg0x8TBARMH\ne0ybq94bmuumoNZDc3Zd7ZAAABUsSURBVPc27P4A/LeoUu6Hr4Cmbtq2Sr9IT4bw0w/EyaLOk0gu\nYcYmhFm2IMyiGWFmtQjLTSPsbhRJGfn+xlBoUqsJtua22NaxVf80N2rChqN32XY+Fut6NZgzzJl+\nbR5MR4icHGJmzyHxr7+K6ujoGSe3BXF+Xyjj53moY/NzcnP4+dLP/HjhR2zNbfmq91e0qt+qfDtO\nuQWnf1CJvGUkg0NvVcRP8z5VJtxTOn0NyE5IUN0AQkLICA4mM+QmmcHBZIaHQ06Oupxho4aY2juo\nbgbNHTB1UL03trLSz3++Kzvhn/fgXjzUs9e2NfqDyIXEUNVPAyNVqKB93sKrTddiNWKSMpJUTwQp\noYQnhz94SkgJIzEjUV1OQaGeaSNSUy1ITbXAsZ49E7t0wq2+HaYLfuDe/oM0eO01Gr37jt5KDWRl\n5LB25nGsW9Vj0GuqnbFup91mxtEZnI4+zdDmQ/mk2yfUMq7AKav0ZDj7q2rKJzVGNejp8a5KyFDP\n17uk038MqsXTwb07cGwJJEeXXVbygPoOqsgamy5g8njOKSkjifCUcEKTQ9U3g9DkMG7cCSE9NwXT\nTMEHf+fielOwZVAdgge7YGNug20dW+zM7bCpY4ONuQ01jErYuETHuL8z1jMfdKRpi7qcjj7N9P+m\nk5qVyqyusxjhOKLybmjZGXBhkyrTNz4Q6jmo1D3dngfjR0ii0wGk068gNH46aNhQ/URg4uCAaXM9\nfzqQVCpXrl8j8rW3aBITxa9PuJMypCn3xC3CksNIyCgoUmtZ01K9kJx/cdm2jq3O3BBErmDD7FOY\n1TLm6ffd+enST/x04Sfs69rzde+vcaqnpZDi3By4uksV8RN5FmpZQrfXodMkvduqVDr9SkZkZpIZ\nEZHvhlDC04GxMSb2dpjYO2DSvLnq6SDvxmBYp/rEFEtKJismhrBJr5AVHs7t9z5jeowFkYlpPNvB\nmplDWmNikkF4Srh6MTn/lNGd9ILJ7pY1LFXrB/nWEO7fHGoaV54SaMjF2+z+/iLdXrDh+9RF+MT4\nMKzFMD7q+lGl2lEiQqhUPY8tU6l8mphDp5eg25t6o2Irnb4OoX46CA4mIyREPh1ISiQjJISwSZPI\nTUrG+geVjk5aZg7fed/gl6PB1DQx4sNBrRjb2RaDYuQcUjJTCEsJU68fhCaHqqeQCt8QGtVoVORm\ncP9neTvibUvOEXsrkd/d53I35y4fdfuIpx2fLtc+yo3oi6pQT/8tqrUb1+dU+/nqeIKjdPp6wCM9\nHRRaTJZPB1WH/Do6tit/waxt2wLXA2NT+HjbZU4F38HNxoIFT7vgYqX5hiGpmamqp4J8Iaf3bwjx\n6fEFyjas0VB9E1BPF+UdP+xCa0xoIn8vPMdJu22ktgnj6z5f08JCD+Ll74SoJJ3Pr1etAbQeqor4\nsX68jdsrCun09ZyHejqwt8+bKnqwmCyfDvQLTXV0hBBs84tkwa4r3LmbyYse9kwb0BJzs8fbu/Zu\n1t0iU0X3f95Ou12gbAOzBgWS0mzq5N0QzG2LJFLF3ovlh6XbqRNpRcIoH2b0/FA3pnMehtS4/7d3\n58F11dcBx7+/p/UtkqynXTLCMpYM8gJ4QbYpewjLsAbaSTslQwZKaAo0Cw3NjCGJS4AsBZo2nQFS\nIOmSGQjFIbRsKQVCwZKNMdjyIq+SLFm7LL19/fWP+zZbXrT5LXrnM+N5lnQl/Tzjd+6953fOuUaP\nS9uzxvC7BZcYFT+Lrkqrck8J+nOU3B3MPdOZozPmCfDTt/bwb62dVNgKWH9DMzcurzkj1S/ugHvC\nySCaNhr0DB5zrL3QHjshVFuref3zN7lh0zcoWRHmK39xzayvLal8Dvjkl/Dxz42nkVUtMxq9mm9J\ni0ZHCfpZaMLdQfSEcIq7A/P5y7G0rCF//oQHmokkmOkcnc+6j7J+4w6294zxR4vK2XDzEhZWTHJs\nwSxwB9zGpvJx+wfd490MeAa4duAOFhxYxZ9vWEtJRXpUEs1Y0A/bXzby/kN7jJHX6+43nl6Xn7q7\nGAn6IuZkdwe+AwcIR+4O8urqsKxpwbpmDZaLWsirmtzwLzF9w8+/wMCPfzzjOTqhsObfWzv5yZt7\n8AXD3HvZQr5+xSIK81Kb3ht3OXnp4a3HNGPNKeEwdLxhVPwcbjOeQdzyl7D6LrDYk74cCfritLTW\n+Pftw7WpFVfrJtxtmwmPjwOQ39CApeWiyEngInLtyf9PPFdprRl88imGn3tuVufoDDi8PPZfu9i4\nrZd6u4Uf3LyEKxan5uStw5rP//cwH768ly89uIKaRZlV8z4lWkPXx/DhU7D3bcizwso7Ye3XJzwD\n4UySoC+mTIdCeHfvxr2pFVdbK57NWwi73QAUNDXF7wRWrZJ9gWlKxhydj/YNsf63Ozgw6OK6pdU8\ncmMzNSVnLrXiHvcz3OtkpMfFSK+T4V4XI70uAr4QVQ3F3PadlRk7OmLK+tuNtM/23xibvNFyz4pZ\nniV0AhL0xYzpQABve3vsTsCz9VO0zwcmE4XNzVjXtGBpacGyYkVGjvhNtrDfT+/ffAfHW2+d8Tk6\nvmCIX/zhID/7n73kmBTf/EITd168gLwZTJL1e4KMHHEx3ONkpNdlBPpeFx5HIHZMoTWPsjor9job\nZbVWFl5Qgbko86aBzthop7Hhu/VXEPTA4uuNip/6ljP2KyXoi1kX9vvxbNsWvxP47HMIBCA3F/Py\n5UY6qGUN5gsvwFSQfY+rO5Wwy8Xh++/H9dHHVD70EGVfvTMpv7d7xM33Xmvn3d0DnFtdxKO3LGXV\nglOn6kKBMKP9LoZ7XPHg3uPCMeKNHZNbkENZrRV7rZWyWpvxWmfDXJSXPVf1k+EaNko9254BzyjU\nrzVq/Ru/OOvlnhL0xRkXdrtxf/qpcRJobcW7YweEw6j8fMwXXhi7EzAvW4bKm1kdeSYLjo7S/bV7\n8ba3U/Poo8y7NbmdqFpr3t7Zzw9ea6d3zMufrJrP3153HvPMeYwPemKBfTiSnjk64EGHjbhgylGU\nVluwJwT2slorRfZC1Kke8C6O5XfB1n81ZvuPH4bKZiPts/Q2yJmd94YEfZF0IYcD95YtkTuBNny7\ndgGgLBYsK1dibbkIS8saCpvPy5rGscQ5OnVPP0XRlVcmfQ1aa1xH/fR2jvG7DzrZv+8oldpERdgE\nocj7X0FxuTl+9V5nBPl5lRZycufow4VSIRSAHa8Yef+BnVByFqy9z3ic6QyntkrQFykXHB3F3bYZ\nd6txJ+Dfvx8AU1ERltWrY3cCBY2NKNPcCyy+AwfpuvvYOTpnmtcVYKQ3sqHaE8+7+9zB2DH5tjz6\nVIgDfj/WykLuuKaRFcsqySvIjhNxWtDaqPT58Cmj8sdsh4vuMf5Yy6b1IyXoi7QTGBiInAQ24Wpt\nI9DVBUBOaSmWlpbYnUB+w4KMzwufbo7OTAX8IUaPRHLusY1VF66jvtgx+ebcCVfu9lorZls+Wmte\n2drDY/+9izFPgK+uW8A3rm7CVpD6ztKs09WK7/0nKdj/Jq7ic7B+85Np5fsl6Iu0F+jpwdXaFrsT\nCPb1AZBbWWmcBNa0ZGS38GTn6ExGOBTm6IDnuODuZGzQA5G3bk6uidIai7GhWhffWLWVFpz25HnU\n7edHb+7h121dVBcX8siNzVy3tDrjT7rpaswTYG+/gz39Djr6Iq/9TkZcfhapw7SU+/jhtx+Y1s+W\noC8yitaaQGdn5CRg3AmEho3Jj5nULez4/e/p+da3pzRHB4x/v2PEO+HKfbTPRThovEeVgpJKi3H1\nHtlQtddaKakwY5pBKSbA1q5R1r+6g51HxrmsqYINNy/h7DIpw50utz/IvgEne/ocdPQ72NPvZG+/\ngyNj8QooW0EujVU2FlcV0VRVxOJq47WiaHqVbxL0RUZL7BZ2t7XiatscGxmR39BgnARaWtKqW3iy\nc3Q8Dj/DCcE92tAU8MbnI9lKC7DX2iirs0aCu43SGgu5Z3C0QjAU5lcfd/LkOx34Q2H+6vJFfO2y\nhSkf55DO/MEwB4biwb2j30lHv4OuETfR0Jqfa6KxMhLcq4tir7UlhbN6RyVBX8wpsW7h1jajUSzN\nuoVPNEfH7zWamUYSNlSHe5wnbmaKlkRGruILzKnLrfePe/m713fy+udHaCi3suHmJVzSWJGy9aSD\nUFjTOeyKBfVoeubgkItgpLw1x6RYWG6NB/bI1Xu93UJOEspbZzXoK6WuBf4ByAF+obV+4rivXwo8\nDSwHvqy1/k3C10LA9siHXVrrm071uyToi8lI7BZ2t7Xi/mRrSrqFtdb0//3TdP/6dULrriN8+U2M\n9nsZ7nHiGE5oZso3GVfux22sWorz0zZ//kHHII/8dgeHht3csLyGh29opqo4Mx8aPllaa3rHvPF8\ne+R134ATXzAMGGm2ervFCOpVRUaKprqIhnIrBbmpuyuataCvlMoBOoCrgcPAZuBPtdY7E45ZABQD\nDwKvHRf0nVrrSc96laAvpiPWLRy9EzgD3cI6rBkf9sSamIZ7nPRvO4QzUIg2GW92k0kxr9oSS8lE\nr+KLyzKzmckbCPHM+wf4+Xv7yM8x8a2rm/jK2rPJneEeQqpprRly+o2r9lje3cHefidOX7y8taak\nkMaqIhZX2WJX7osqbVjy06/KaTaD/lrg+1rrayIffxdAa/34CY59EXhdgr5ItZl0C2utjSFiCRuq\nIz1ORo64CPrDseMsuLAM7ae8qYqzbrmCsjob86rmZjPToSEXj7zWzgcdgzTXFPPorUtZUT+12f+p\nMuYO0DHgSMi7xytmokoteSxOyLcbV/BFlJgzp5N8NoP+7cC1Wuu7Ix/fAbRore87wbEvMjHoB4Ft\nQBB4Qmu98QTfdw9wD0B9ff3Kzs7O061biCk5WbdwsMhO8ILL8Decj6uknjFPPsNHXPhc8as9S3F+\nfMZMnZVSew6enzyM76M/JHWOTqpprXljRx8bfreTfoeXL6+u56FrFzPPkh4D1dz+IHv7nZErdqNi\npqPPQd/4sRUzTZF0TDw9U0S5LX3TbJM12aCfjHuUs7XWPUqphcC7SqntWuv9iQdorZ8FngXjSj8J\naxJZRhdY8J6zilHzuYw03c5Q5yjD3eO4PZE3ehfkBEewefuptoUpbyilamUjVaubsJTE89jROTq+\n9nZqHn886XN0UkkpxfXLari0qYKn3+nghY8O8XZ7H9+9/jxuW1GXtKDpC4Y4OOSKp2X6jM3V7tF4\nxUxBronGKhvrFpXFgvuZqJjJRJMJ+j3AWQkfz498blK01j2R1wNKqfeAC4H9p/wmIaYpHAozNhjP\nu0fTM2MD8YAQbWaav7w61shUUuBF7fkMT9tBo1v4vS68L8DhhG7hgsWLOfLwIwS6u5n/jz9LyRyd\ndGAryGX9Dc18acV81m/czoMvf8ZLm7t59NalNFUVzdrviVfMxAP7nn6jYiYUqZjJNSkayq0sm1/C\n7SvnJ71iJhNNJr2Ti7GRexVGsN8M/JnWuv0Ex75IQnpHKVUKuLXWPqVUOfAxcHPiJvDxJKcvJkNr\njXPUl1DrbpRFjh5xE0qosiiptMTGD5RFNlYn08x0sm5hk9WatDk6mSAc1rz8STePv7EbpzfIXZc0\n8NdXNU5po1NrTc9Rz7HBvc/BvkEn/pNUzETz7g3lVvLn4B7KdMx2yeb1GCWZOcDzWusfKqU2AFu0\n1q8ppVYDrwKlgBfo01ovUUqtA54BwoAJeFpr/S+n+l0S9MXxvM4Awz3RJzLFRwD7JzQzWRMammyU\nVlvIzZ95CZ3WmkBXF+6tn2I+/3wKFk5/rMJcNeLy88Qbu3hpy2FqSwr53k1L+GJz1TGpFK01g04f\nHX2JefcTV8xEr9gbK21pXTGTTqQ5S2ScgC90zBOZolfx7vF4lUWBJTdW4x4bIlZjpdCaOVUWc9mW\nQyOs37iD3X0Orjy3kivOrTSCeyT/PuqON6bZrfmRJiZbxlbMpBMJ+iJthUJhjva5Jzy8Y3wooZkp\nzxRPy0SDfK0NS0nmV1nMdYFQmF9+dIgn3+nA7Q+dsGKmqbqIcps8XW02pVP1jshSRjOTN/6w7EiK\n5mi/m3Dk4R3KpJhXZaHy7GLOW1cTG0dQXG7GJBtxGSkvx8Tdlyzkj1eehdMflIqZNCNBX8xYtJkp\ntqEazb8fcRH0xfPuRWWFlNVaWbC8PD5ErMpCTp5sxM1FJZY8SiySqkk3EvTFlPg9wQkbqsO9LrzO\neK7WXJSHvdZG88U1sZJIe62V/EL57yZEqsm7UJxQMBBiNJJ3T3z0nnMk/mSmvIIc7LVWFp5fnjDf\n3YalOD06NIUQE0nQz3LhsGZ80DOhYubogAcdaYAx5ShKq63UnDOPskvjT2YqKpNcrRCZZs4Efa8r\nwH/+dGuql5FRdNh4WlMoEBkipqCk3Iy91so5KypjFTMlVWZyMnyqohDCMGeCvjIp7DWWVC8j4yxY\nVhZraCqtsZI3C81MQoj0NWeCfoE5l2vvWZbqZQghRFqTe3YhhMgiEvSFECKLSNAXQogsIkFfCCGy\niAR9IYTIIhL0hRAii0jQF0KILCJBXwghskjaPURFKTUIdM7gR5QDQ7O0nNkk65oaWdfUyLqmZi6u\n62ytdcXpDkq7oD9TSqktk3l6TLLJuqZG1jU1sq6pyeZ1SXpHCCGyiAR9IYTIInMx6D+b6gWchKxr\namRdUyPrmpqsXdecy+kLIYQ4ubl4pS+EEOIkJOgLIUQWkaAvhBBZRIK+EEJkEQn6QgiRRSToCyFE\nFpGgL4QQWUSCvhAJlFIblVKfKKXalVL3RD53l1KqQynVppR6Tin1T5HPVyilXlFKbY78uTi1qxfi\n9KQ5S4gESim71npEKWUGNgPXAP8HrAAcwLvAZ1rr+5RS/wH8s9b6Q6VUPfCW1vq8lC1eiEnITfUC\nhEgzDyilbo38/SzgDuB9rfUIgFLqZaAp8vUvAM1Kqej3FiulbFprZzIXLMRUSNAXIkIpdTlGIF+r\ntXYrpd4DdgMnu3o3AWu01t7krFCImZOcvhBxJcBoJOCfC6wBrMBlSqlSpVQucFvC8W8D90c/UEpd\nkNTVCjENEvSFiHsTyFVK7QKeADYBPcBjQBtGbv8QMBY5/gFglVLqc6XUTuDepK9YiCmSjVwhTiOa\np49c6b8KPK+1fjXV6xJiOuRKX4jT+75SahuwAzgIbEzxeoSYNrnSF0KILCJX+kIIkUUk6AshRBaR\noC+EEFlEgr4QQmQRCfpCCJFFJOgLIUQW+X9S0MmvYIPlqgAAAABJRU5ErkJggg==\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "trhIwav9O91C",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 233
+        },
+        "outputId": "911df390-4e29-4d59-c898-6cb919d0c036"
+      },
+      "source": [
+        "pd.crosstab(age_bins, exercise_bins, normalize='columns')"
+      ],
+      "execution_count": 67,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th>exercise_time</th>\n",
+              "      <th>(-0.0, 60.0]</th>\n",
+              "      <th>(60.0, 120.0]</th>\n",
+              "      <th>(120.0, 180.0]</th>\n",
+              "      <th>(180.0, 240.0]</th>\n",
+              "      <th>(240.0, 300.0]</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>age</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>(18.0, 30.0]</th>\n",
+              "      <td>0.187050</td>\n",
+              "      <td>0.145570</td>\n",
+              "      <td>0.242152</td>\n",
+              "      <td>0.317708</td>\n",
+              "      <td>0.225131</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(30.0, 43.0]</th>\n",
+              "      <td>0.187050</td>\n",
+              "      <td>0.174051</td>\n",
+              "      <td>0.188341</td>\n",
+              "      <td>0.244792</td>\n",
+              "      <td>0.298429</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(43.0, 55.0]</th>\n",
+              "      <td>0.147482</td>\n",
+              "      <td>0.132911</td>\n",
+              "      <td>0.174888</td>\n",
+              "      <td>0.177083</td>\n",
+              "      <td>0.350785</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(55.0, 68.0]</th>\n",
+              "      <td>0.165468</td>\n",
+              "      <td>0.224684</td>\n",
+              "      <td>0.179372</td>\n",
+              "      <td>0.213542</td>\n",
+              "      <td>0.125654</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(68.0, 80.0]</th>\n",
+              "      <td>0.312950</td>\n",
+              "      <td>0.322785</td>\n",
+              "      <td>0.215247</td>\n",
+              "      <td>0.046875</td>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "exercise_time  (-0.0, 60.0]       ...        (240.0, 300.0]\n",
+              "age                               ...                      \n",
+              "(18.0, 30.0]       0.187050       ...              0.225131\n",
+              "(30.0, 43.0]       0.187050       ...              0.298429\n",
+              "(43.0, 55.0]       0.147482       ...              0.350785\n",
+              "(55.0, 68.0]       0.165468       ...              0.125654\n",
+              "(68.0, 80.0]       0.312950       ...              0.000000\n",
+              "\n",
+              "[5 rows x 5 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 67
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "pJN-2_qYD3n8",
+        "colab_type": "code",
+        "outputId": "7220bf25-7201-4453-8fdf-0bcdabf53c2f",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 301
+        }
+      },
+      "source": [
+        "# Looks like nobody in the highest age bin exercised 4-5 hours?\n",
+        "ct = pd.crosstab(exercise_bins, [age_bins, weight_bins], normalize='index')\n",
+        "ct"
+      ],
+      "execution_count": 59,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead tr th {\n",
+              "        text-align: left;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead tr:last-of-type th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr>\n",
+              "      <th>age</th>\n",
+              "      <th colspan=\"5\" halign=\"left\">(18.0, 30.0]</th>\n",
+              "      <th colspan=\"5\" halign=\"left\">(30.0, 43.0]</th>\n",
+              "      <th colspan=\"5\" halign=\"left\">(43.0, 55.0]</th>\n",
+              "      <th colspan=\"5\" halign=\"left\">(55.0, 68.0]</th>\n",
+              "      <th colspan=\"5\" halign=\"left\">(68.0, 80.0]</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>weight</th>\n",
+              "      <th>(100.0, 129.0]</th>\n",
+              "      <th>(129.0, 158.0]</th>\n",
+              "      <th>(158.0, 188.0]</th>\n",
+              "      <th>(188.0, 217.0]</th>\n",
+              "      <th>(217.0, 246.0]</th>\n",
+              "      <th>(100.0, 129.0]</th>\n",
+              "      <th>(129.0, 158.0]</th>\n",
+              "      <th>(158.0, 188.0]</th>\n",
+              "      <th>(188.0, 217.0]</th>\n",
+              "      <th>(217.0, 246.0]</th>\n",
+              "      <th>(100.0, 129.0]</th>\n",
+              "      <th>(129.0, 158.0]</th>\n",
+              "      <th>(158.0, 188.0]</th>\n",
+              "      <th>(188.0, 217.0]</th>\n",
+              "      <th>(217.0, 246.0]</th>\n",
+              "      <th>(100.0, 129.0]</th>\n",
+              "      <th>(129.0, 158.0]</th>\n",
+              "      <th>(158.0, 188.0]</th>\n",
+              "      <th>(188.0, 217.0]</th>\n",
+              "      <th>(217.0, 246.0]</th>\n",
+              "      <th>(100.0, 129.0]</th>\n",
+              "      <th>(129.0, 158.0]</th>\n",
+              "      <th>(158.0, 188.0]</th>\n",
+              "      <th>(188.0, 217.0]</th>\n",
+              "      <th>(217.0, 246.0]</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>exercise_time</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>(-0.0, 60.0]</th>\n",
+              "      <td>0.035971</td>\n",
+              "      <td>0.025180</td>\n",
+              "      <td>0.039568</td>\n",
+              "      <td>0.061151</td>\n",
+              "      <td>0.02518</td>\n",
+              "      <td>0.028777</td>\n",
+              "      <td>0.035971</td>\n",
+              "      <td>0.035971</td>\n",
+              "      <td>0.061151</td>\n",
+              "      <td>0.02518</td>\n",
+              "      <td>0.025180</td>\n",
+              "      <td>0.025180</td>\n",
+              "      <td>0.039568</td>\n",
+              "      <td>0.032374</td>\n",
+              "      <td>0.025180</td>\n",
+              "      <td>0.025180</td>\n",
+              "      <td>0.021583</td>\n",
+              "      <td>0.035971</td>\n",
+              "      <td>0.053957</td>\n",
+              "      <td>0.028777</td>\n",
+              "      <td>0.075540</td>\n",
+              "      <td>0.050360</td>\n",
+              "      <td>0.068345</td>\n",
+              "      <td>0.064748</td>\n",
+              "      <td>0.053957</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(60.0, 120.0]</th>\n",
+              "      <td>0.028481</td>\n",
+              "      <td>0.047468</td>\n",
+              "      <td>0.037975</td>\n",
+              "      <td>0.031646</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.060127</td>\n",
+              "      <td>0.025316</td>\n",
+              "      <td>0.050633</td>\n",
+              "      <td>0.037975</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.018987</td>\n",
+              "      <td>0.028481</td>\n",
+              "      <td>0.044304</td>\n",
+              "      <td>0.037975</td>\n",
+              "      <td>0.003165</td>\n",
+              "      <td>0.031646</td>\n",
+              "      <td>0.063291</td>\n",
+              "      <td>0.060127</td>\n",
+              "      <td>0.066456</td>\n",
+              "      <td>0.003165</td>\n",
+              "      <td>0.066456</td>\n",
+              "      <td>0.075949</td>\n",
+              "      <td>0.101266</td>\n",
+              "      <td>0.056962</td>\n",
+              "      <td>0.022152</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(120.0, 180.0]</th>\n",
+              "      <td>0.076233</td>\n",
+              "      <td>0.089686</td>\n",
+              "      <td>0.044843</td>\n",
+              "      <td>0.031390</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.085202</td>\n",
+              "      <td>0.035874</td>\n",
+              "      <td>0.058296</td>\n",
+              "      <td>0.008969</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.040359</td>\n",
+              "      <td>0.058296</td>\n",
+              "      <td>0.053812</td>\n",
+              "      <td>0.022422</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.058296</td>\n",
+              "      <td>0.062780</td>\n",
+              "      <td>0.026906</td>\n",
+              "      <td>0.031390</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.058296</td>\n",
+              "      <td>0.053812</td>\n",
+              "      <td>0.067265</td>\n",
+              "      <td>0.035874</td>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(180.0, 240.0]</th>\n",
+              "      <td>0.098958</td>\n",
+              "      <td>0.151042</td>\n",
+              "      <td>0.067708</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.130208</td>\n",
+              "      <td>0.078125</td>\n",
+              "      <td>0.036458</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.093750</td>\n",
+              "      <td>0.036458</td>\n",
+              "      <td>0.046875</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.062500</td>\n",
+              "      <td>0.098958</td>\n",
+              "      <td>0.046875</td>\n",
+              "      <td>0.005208</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.026042</td>\n",
+              "      <td>0.020833</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>(240.0, 300.0]</th>\n",
+              "      <td>0.130890</td>\n",
+              "      <td>0.078534</td>\n",
+              "      <td>0.015707</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.172775</td>\n",
+              "      <td>0.109948</td>\n",
+              "      <td>0.015707</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.00000</td>\n",
+              "      <td>0.198953</td>\n",
+              "      <td>0.136126</td>\n",
+              "      <td>0.015707</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.057592</td>\n",
+              "      <td>0.062827</td>\n",
+              "      <td>0.005236</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "      <td>0.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "age              (18.0, 30.0]      ...         (68.0, 80.0]\n",
+              "weight         (100.0, 129.0]      ...       (217.0, 246.0]\n",
+              "exercise_time                      ...                     \n",
+              "(-0.0, 60.0]         0.035971      ...             0.053957\n",
+              "(60.0, 120.0]        0.028481      ...             0.022152\n",
+              "(120.0, 180.0]       0.076233      ...             0.000000\n",
+              "(180.0, 240.0]       0.098958      ...             0.000000\n",
+              "(240.0, 300.0]       0.130890      ...             0.000000\n",
+              "\n",
+              "[5 rows x 25 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 59
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "wG-8EGsCLv_w",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# Create subsets\n",
+        "ct_youngest = ct.iloc[:, [0,1,2,3,4]]\n",
+        "ct_second_young = ct.iloc[:, [5,6,7,8,9]]\n",
+        "ct_middle_age = ct.iloc[:, [10,11,12,13,14]]\n",
+        "ct_second_old = ct.iloc[:, [15,16,17,18,19]]\n",
+        "ct_oldest = ct.iloc[:, [20,21,22,23,24]]"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "UQ4xJ3PcIBbF",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 292
+        },
+        "outputId": "1dc735b9-d060-4981-f697-4a8930096369"
+      },
+      "source": [
+        "ct_young.plot()\n",
+        "# Among the youngest cohort, only the very lowest exercisers are in the highest weight bracket.\n",
+        "# As exercise time increases, chance of being in two lowest weight brackets increases."
+      ],
+      "execution_count": 64,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f57371c5240>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 64
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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/HR7DtF9OsvdsFNWdHZj3ZCO6+7nk2cRGa2PWaISIbAI23bPurXR/B6N3+9y7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\n6SuKoniR/w82yXShAaTLAAAAAABJRU5ErkJggg==\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Fdr5cGldNzDx",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 292
+        },
+        "outputId": "9fe64ffa-77e3-4a29-a606-a13a87335770"
+      },
+      "source": [
+        "ct_oldest.plot()\n",
+        "# This may be deceptive because older people just tend to exercise less in general."
+      ],
+      "execution_count": 66,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f5737147b00>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 66
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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1wPD8z6HA9vwxpstAZwBFUWyBtsDpsjC8IknMSmTklpGsvbCWVwJfYXrIdKzM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\n0B1ZwDvzAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "BT9gdS7viJZa",
+        "colab_type": "text"
+      },
+      "source": [
+        "### Assignment questions\n",
+        "\n",
+        "After you've worked on some code, answer the following questions in this text block:\n",
+        "\n",
+        "1.  What are the variable types in the data?\n",
+        "\n",
+        "The variables are continuous.\n",
+        "\n",
+        "2.  What are the relationships between the variables?\n",
+        "\n",
+        "Exercise time decreases as age increases. Weight decreases as exercise time increases.\n",
+        "\n",
+        "3.  Which relationships are \"real\", and which spurious?\n",
+        "\n",
+        "There sometimes appears to be a relationship between age and weight, and sometimes not, in the crosstables and corresponding graphs. But a scatter plot shows no relationship, so it seems like there's no relationship."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_XXg2crAipwP",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Stretch goals and resources\n",
+        "\n",
+        "Following are *optional* things for you to take a look at. Focus on the above assignment first, and make sure to commit and push your changes to GitHub.\n",
+        "\n",
+        "- [Spurious Correlations](http://tylervigen.com/spurious-correlations)\n",
+        "- [NIH on controlling for confounding variables](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017459/)\n",
+        "\n",
+        "Stretch goals:\n",
+        "\n",
+        "- Produce your own plot inspired by the Spurious Correlation visualizations (and consider writing a blog post about it - both the content and how you made it)\n",
+        "- Pick one of the techniques that NIH highlights for confounding variables - we'll be going into many of them later, but see if you can find which Python modules may help (hint - check scikit-learn)"
+      ]
+    }
+  ]
+}
\ No newline at end of file

From 1b47e5cebfd8b2e1806038379f9c89d40ca51a66 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Thu, 12 Sep 2019 23:29:03 -0400
Subject: [PATCH 6/9] Ben Whitman Assignment 4

---
 .../LS_DS_114_Make_Features_Assignment.ipynb  | 12223 +++++++++++++++-
 1 file changed, 12220 insertions(+), 3 deletions(-)

diff --git a/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb b/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb
index adf6cb92..bb58d3e2 100644
--- a/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb
+++ b/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb
@@ -6,7 +6,10 @@
       "name": "LS_DS_114_Make_Features_Assignment.ipynb",
       "version": "0.3.2",
       "provenance": [],
-      "collapsed_sections": []
+      "collapsed_sections": [
+        "e9240Lt4h6rI"
+      ],
+      "include_colab_link": true
     },
     "kernelspec": {
       "display_name": "Python 3",
@@ -27,6 +30,16 @@
     }
   },
   "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/b-whitman/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -56,6 +69,16 @@
         "- Make `last_pymnt_d_month` and `last_pymnt_d_year` columns."
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "e9240Lt4h6rI",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Weather Dataset"
+      ]
+    },
     {
       "cell_type": "code",
       "metadata": {
@@ -64,11 +87,12205 @@
         "colab": {}
       },
       "source": [
-        "##### Begin Working Here #####"
+        "import pandas as pd\n",
+        "import numpy as np"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "rj1qjHciVKik",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "url = 'https://raw.githubusercontent.com/jvns/pandas-cookbook/master/data/weather_2012.csv'"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "GkaBzaznVbrh",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 202
+        },
+        "outputId": "0ec19261-fd9c-4cbd-a29e-33082aa425a4"
+      },
+      "source": [
+        "df_weather = pd.read_csv(url, parse_dates=True) #, index_col='Date/Time')\n",
+        "df_weather.head()"
+      ],
+      "execution_count": 5,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Date/Time</th>\n",
+              "      <th>Temp (C)</th>\n",
+              "      <th>Dew Point Temp (C)</th>\n",
+              "      <th>Rel Hum (%)</th>\n",
+              "      <th>Wind Spd (km/h)</th>\n",
+              "      <th>Visibility (km)</th>\n",
+              "      <th>Stn Press (kPa)</th>\n",
+              "      <th>Weather</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>2012-01-01 00:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.9</td>\n",
+              "      <td>86</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2012-01-01 01:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.7</td>\n",
+              "      <td>87</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2012-01-01 02:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.4</td>\n",
+              "      <td>89</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.26</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>2012-01-01 03:00:00</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.2</td>\n",
+              "      <td>88</td>\n",
+              "      <td>6</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.27</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>2012-01-01 04:00:00</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.3</td>\n",
+              "      <td>88</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>101.23</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "             Date/Time  Temp (C)  ...  Stn Press (kPa)               Weather\n",
+              "0  2012-01-01 00:00:00      -1.8  ...           101.24                   Fog\n",
+              "1  2012-01-01 01:00:00      -1.8  ...           101.24                   Fog\n",
+              "2  2012-01-01 02:00:00      -1.8  ...           101.26  Freezing Drizzle,Fog\n",
+              "3  2012-01-01 03:00:00      -1.5  ...           101.27  Freezing Drizzle,Fog\n",
+              "4  2012-01-01 04:00:00      -1.5  ...           101.23                   Fog\n",
+              "\n",
+              "[5 rows x 8 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 5
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "vXDSbf2DV9k9",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df_weather['Date/Time'] = pd.to_datetime(df_weather['Date/Time'])"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "htGzAKIjWKzC",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "463fce31-85cc-4dcf-f9cb-529bfab8057c"
+      },
+      "source": [
+        "df_weather.set_index('Date/Time')"
+      ],
+      "execution_count": 7,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Temp (C)</th>\n",
+              "      <th>Dew Point Temp (C)</th>\n",
+              "      <th>Rel Hum (%)</th>\n",
+              "      <th>Wind Spd (km/h)</th>\n",
+              "      <th>Visibility (km)</th>\n",
+              "      <th>Stn Press (kPa)</th>\n",
+              "      <th>Weather</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Date/Time</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 00:00:00</th>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.9</td>\n",
+              "      <td>86</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 01:00:00</th>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.7</td>\n",
+              "      <td>87</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 02:00:00</th>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.4</td>\n",
+              "      <td>89</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.26</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 03:00:00</th>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.2</td>\n",
+              "      <td>88</td>\n",
+              "      <td>6</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.27</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 04:00:00</th>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.3</td>\n",
+              "      <td>88</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>101.23</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 05:00:00</th>\n",
+              "      <td>-1.4</td>\n",
+              "      <td>-3.3</td>\n",
+              "      <td>87</td>\n",
+              "      <td>9</td>\n",
+              "      <td>6.4</td>\n",
+              "      <td>101.27</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 06:00:00</th>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.1</td>\n",
+              "      <td>89</td>\n",
+              "      <td>7</td>\n",
+              "      <td>6.4</td>\n",
+              "      <td>101.29</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 07:00:00</th>\n",
+              "      <td>-1.4</td>\n",
+              "      <td>-3.6</td>\n",
+              "      <td>85</td>\n",
+              "      <td>7</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.26</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 08:00:00</th>\n",
+              "      <td>-1.4</td>\n",
+              "      <td>-3.6</td>\n",
+              "      <td>85</td>\n",
+              "      <td>9</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.23</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 09:00:00</th>\n",
+              "      <td>-1.3</td>\n",
+              "      <td>-3.1</td>\n",
+              "      <td>88</td>\n",
+              "      <td>15</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.20</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 10:00:00</th>\n",
+              "      <td>-1.0</td>\n",
+              "      <td>-2.3</td>\n",
+              "      <td>91</td>\n",
+              "      <td>9</td>\n",
+              "      <td>1.2</td>\n",
+              "      <td>101.15</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 11:00:00</th>\n",
+              "      <td>-0.5</td>\n",
+              "      <td>-2.1</td>\n",
+              "      <td>89</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>100.98</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 12:00:00</th>\n",
+              "      <td>-0.2</td>\n",
+              "      <td>-2.0</td>\n",
+              "      <td>88</td>\n",
+              "      <td>9</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>100.79</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 13:00:00</th>\n",
+              "      <td>0.2</td>\n",
+              "      <td>-1.7</td>\n",
+              "      <td>87</td>\n",
+              "      <td>13</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>100.58</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 14:00:00</th>\n",
+              "      <td>0.8</td>\n",
+              "      <td>-1.1</td>\n",
+              "      <td>87</td>\n",
+              "      <td>20</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>100.31</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 15:00:00</th>\n",
+              "      <td>1.8</td>\n",
+              "      <td>-0.4</td>\n",
+              "      <td>85</td>\n",
+              "      <td>22</td>\n",
+              "      <td>6.4</td>\n",
+              "      <td>100.07</td>\n",
+              "      <td>Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 16:00:00</th>\n",
+              "      <td>2.6</td>\n",
+              "      <td>-0.2</td>\n",
+              "      <td>82</td>\n",
+              "      <td>13</td>\n",
+              "      <td>12.9</td>\n",
+              "      <td>99.93</td>\n",
+              "      <td>Mostly Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 17:00:00</th>\n",
+              "      <td>3.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>81</td>\n",
+              "      <td>13</td>\n",
+              "      <td>16.1</td>\n",
+              "      <td>99.81</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 18:00:00</th>\n",
+              "      <td>3.8</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>82</td>\n",
+              "      <td>15</td>\n",
+              "      <td>12.9</td>\n",
+              "      <td>99.74</td>\n",
+              "      <td>Rain</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 19:00:00</th>\n",
+              "      <td>3.1</td>\n",
+              "      <td>1.3</td>\n",
+              "      <td>88</td>\n",
+              "      <td>15</td>\n",
+              "      <td>12.9</td>\n",
+              "      <td>99.68</td>\n",
+              "      <td>Rain</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 20:00:00</th>\n",
+              "      <td>3.2</td>\n",
+              "      <td>1.3</td>\n",
+              "      <td>87</td>\n",
+              "      <td>19</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.50</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 21:00:00</th>\n",
+              "      <td>4.0</td>\n",
+              "      <td>1.7</td>\n",
+              "      <td>85</td>\n",
+              "      <td>20</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.39</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 22:00:00</th>\n",
+              "      <td>4.4</td>\n",
+              "      <td>1.9</td>\n",
+              "      <td>84</td>\n",
+              "      <td>24</td>\n",
+              "      <td>19.3</td>\n",
+              "      <td>99.32</td>\n",
+              "      <td>Rain Showers</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-01 23:00:00</th>\n",
+              "      <td>5.3</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>79</td>\n",
+              "      <td>30</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.31</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-02 00:00:00</th>\n",
+              "      <td>5.2</td>\n",
+              "      <td>1.5</td>\n",
+              "      <td>77</td>\n",
+              "      <td>35</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.26</td>\n",
+              "      <td>Rain Showers</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-02 01:00:00</th>\n",
+              "      <td>4.6</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>72</td>\n",
+              "      <td>39</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.26</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-02 02:00:00</th>\n",
+              "      <td>3.9</td>\n",
+              "      <td>-0.9</td>\n",
+              "      <td>71</td>\n",
+              "      <td>32</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.26</td>\n",
+              "      <td>Mostly Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-02 03:00:00</th>\n",
+              "      <td>3.7</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>69</td>\n",
+              "      <td>33</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.30</td>\n",
+              "      <td>Mostly Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-02 04:00:00</th>\n",
+              "      <td>2.9</td>\n",
+              "      <td>-2.3</td>\n",
+              "      <td>69</td>\n",
+              "      <td>32</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.26</td>\n",
+              "      <td>Mostly Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-01-02 05:00:00</th>\n",
+              "      <td>2.6</td>\n",
+              "      <td>-2.3</td>\n",
+              "      <td>70</td>\n",
+              "      <td>32</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>99.21</td>\n",
+              "      <td>Mostly Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-30 18:00:00</th>\n",
+              "      <td>-12.6</td>\n",
+              "      <td>-16.0</td>\n",
+              "      <td>76</td>\n",
+              "      <td>24</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.36</td>\n",
+              "      <td>Mainly Clear</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-30 19:00:00</th>\n",
+              "      <td>-13.4</td>\n",
+              "      <td>-16.5</td>\n",
+              "      <td>77</td>\n",
+              "      <td>26</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.47</td>\n",
+              "      <td>Mainly Clear</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-30 20:00:00</th>\n",
+              "      <td>-13.8</td>\n",
+              "      <td>-16.5</td>\n",
+              "      <td>80</td>\n",
+              "      <td>24</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.52</td>\n",
+              "      <td>Clear</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-30 21:00:00</th>\n",
+              "      <td>-13.8</td>\n",
+              "      <td>-16.5</td>\n",
+              "      <td>80</td>\n",
+              "      <td>20</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.50</td>\n",
+              "      <td>Mainly Clear</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-30 22:00:00</th>\n",
+              "      <td>-13.7</td>\n",
+              "      <td>-16.3</td>\n",
+              "      <td>81</td>\n",
+              "      <td>19</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.54</td>\n",
+              "      <td>Mainly Clear</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-30 23:00:00</th>\n",
+              "      <td>-12.1</td>\n",
+              "      <td>-15.1</td>\n",
+              "      <td>78</td>\n",
+              "      <td>28</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.52</td>\n",
+              "      <td>Mostly Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 00:00:00</th>\n",
+              "      <td>-11.1</td>\n",
+              "      <td>-14.4</td>\n",
+              "      <td>77</td>\n",
+              "      <td>26</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.51</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 01:00:00</th>\n",
+              "      <td>-10.7</td>\n",
+              "      <td>-14.0</td>\n",
+              "      <td>77</td>\n",
+              "      <td>15</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.50</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 02:00:00</th>\n",
+              "      <td>-10.1</td>\n",
+              "      <td>-13.4</td>\n",
+              "      <td>77</td>\n",
+              "      <td>9</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.45</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 03:00:00</th>\n",
+              "      <td>-11.8</td>\n",
+              "      <td>-14.4</td>\n",
+              "      <td>81</td>\n",
+              "      <td>6</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.42</td>\n",
+              "      <td>Mostly Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 04:00:00</th>\n",
+              "      <td>-10.5</td>\n",
+              "      <td>-12.8</td>\n",
+              "      <td>83</td>\n",
+              "      <td>11</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.34</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 05:00:00</th>\n",
+              "      <td>-10.2</td>\n",
+              "      <td>-12.4</td>\n",
+              "      <td>84</td>\n",
+              "      <td>6</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.28</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 06:00:00</th>\n",
+              "      <td>-9.7</td>\n",
+              "      <td>-11.7</td>\n",
+              "      <td>85</td>\n",
+              "      <td>4</td>\n",
+              "      <td>25.0</td>\n",
+              "      <td>101.23</td>\n",
+              "      <td>Cloudy</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 07:00:00</th>\n",
+              "      <td>-9.3</td>\n",
+              "      <td>-11.3</td>\n",
+              "      <td>85</td>\n",
+              "      <td>0</td>\n",
+              "      <td>19.3</td>\n",
+              "      <td>101.19</td>\n",
+              "      <td>Snow Showers</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 08:00:00</th>\n",
+              "      <td>-8.6</td>\n",
+              "      <td>-10.3</td>\n",
+              "      <td>87</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3.2</td>\n",
+              "      <td>101.14</td>\n",
+              "      <td>Snow Showers</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 09:00:00</th>\n",
+              "      <td>-8.1</td>\n",
+              "      <td>-9.6</td>\n",
+              "      <td>89</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2.4</td>\n",
+              "      <td>101.09</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 10:00:00</th>\n",
+              "      <td>-7.4</td>\n",
+              "      <td>-8.9</td>\n",
+              "      <td>89</td>\n",
+              "      <td>4</td>\n",
+              "      <td>6.4</td>\n",
+              "      <td>101.05</td>\n",
+              "      <td>Snow,Fog</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 11:00:00</th>\n",
+              "      <td>-6.7</td>\n",
+              "      <td>-7.9</td>\n",
+              "      <td>91</td>\n",
+              "      <td>9</td>\n",
+              "      <td>9.7</td>\n",
+              "      <td>100.93</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 12:00:00</th>\n",
+              "      <td>-5.8</td>\n",
+              "      <td>-7.5</td>\n",
+              "      <td>88</td>\n",
+              "      <td>4</td>\n",
+              "      <td>12.9</td>\n",
+              "      <td>100.78</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 13:00:00</th>\n",
+              "      <td>-4.6</td>\n",
+              "      <td>-6.6</td>\n",
+              "      <td>86</td>\n",
+              "      <td>4</td>\n",
+              "      <td>12.9</td>\n",
+              "      <td>100.63</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 14:00:00</th>\n",
+              "      <td>-3.4</td>\n",
+              "      <td>-5.7</td>\n",
+              "      <td>84</td>\n",
+              "      <td>6</td>\n",
+              "      <td>11.3</td>\n",
+              "      <td>100.57</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 15:00:00</th>\n",
+              "      <td>-2.3</td>\n",
+              "      <td>-4.6</td>\n",
+              "      <td>84</td>\n",
+              "      <td>9</td>\n",
+              "      <td>9.7</td>\n",
+              "      <td>100.47</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 16:00:00</th>\n",
+              "      <td>-1.4</td>\n",
+              "      <td>-4.0</td>\n",
+              "      <td>82</td>\n",
+              "      <td>13</td>\n",
+              "      <td>12.9</td>\n",
+              "      <td>100.40</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 17:00:00</th>\n",
+              "      <td>-1.1</td>\n",
+              "      <td>-3.3</td>\n",
+              "      <td>85</td>\n",
+              "      <td>19</td>\n",
+              "      <td>9.7</td>\n",
+              "      <td>100.30</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 18:00:00</th>\n",
+              "      <td>-1.3</td>\n",
+              "      <td>-3.1</td>\n",
+              "      <td>88</td>\n",
+              "      <td>17</td>\n",
+              "      <td>9.7</td>\n",
+              "      <td>100.19</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 19:00:00</th>\n",
+              "      <td>0.1</td>\n",
+              "      <td>-2.7</td>\n",
+              "      <td>81</td>\n",
+              "      <td>30</td>\n",
+              "      <td>9.7</td>\n",
+              "      <td>100.13</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 20:00:00</th>\n",
+              "      <td>0.2</td>\n",
+              "      <td>-2.4</td>\n",
+              "      <td>83</td>\n",
+              "      <td>24</td>\n",
+              "      <td>9.7</td>\n",
+              "      <td>100.03</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 21:00:00</th>\n",
+              "      <td>-0.5</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>93</td>\n",
+              "      <td>28</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>99.95</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 22:00:00</th>\n",
+              "      <td>-0.2</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>89</td>\n",
+              "      <td>28</td>\n",
+              "      <td>9.7</td>\n",
+              "      <td>99.91</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2012-12-31 23:00:00</th>\n",
+              "      <td>0.0</td>\n",
+              "      <td>-2.1</td>\n",
+              "      <td>86</td>\n",
+              "      <td>30</td>\n",
+              "      <td>11.3</td>\n",
+              "      <td>99.89</td>\n",
+              "      <td>Snow</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>8784 rows × 7 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                     Temp (C)  ...               Weather\n",
+              "Date/Time                      ...                      \n",
+              "2012-01-01 00:00:00      -1.8  ...                   Fog\n",
+              "2012-01-01 01:00:00      -1.8  ...                   Fog\n",
+              "2012-01-01 02:00:00      -1.8  ...  Freezing Drizzle,Fog\n",
+              "2012-01-01 03:00:00      -1.5  ...  Freezing Drizzle,Fog\n",
+              "2012-01-01 04:00:00      -1.5  ...                   Fog\n",
+              "2012-01-01 05:00:00      -1.4  ...                   Fog\n",
+              "2012-01-01 06:00:00      -1.5  ...                   Fog\n",
+              "2012-01-01 07:00:00      -1.4  ...                   Fog\n",
+              "2012-01-01 08:00:00      -1.4  ...                   Fog\n",
+              "2012-01-01 09:00:00      -1.3  ...                   Fog\n",
+              "2012-01-01 10:00:00      -1.0  ...                   Fog\n",
+              "2012-01-01 11:00:00      -0.5  ...                   Fog\n",
+              "2012-01-01 12:00:00      -0.2  ...                   Fog\n",
+              "2012-01-01 13:00:00       0.2  ...                   Fog\n",
+              "2012-01-01 14:00:00       0.8  ...                   Fog\n",
+              "2012-01-01 15:00:00       1.8  ...                   Fog\n",
+              "2012-01-01 16:00:00       2.6  ...         Mostly Cloudy\n",
+              "2012-01-01 17:00:00       3.0  ...                Cloudy\n",
+              "2012-01-01 18:00:00       3.8  ...                  Rain\n",
+              "2012-01-01 19:00:00       3.1  ...                  Rain\n",
+              "2012-01-01 20:00:00       3.2  ...                Cloudy\n",
+              "2012-01-01 21:00:00       4.0  ...                Cloudy\n",
+              "2012-01-01 22:00:00       4.4  ...          Rain Showers\n",
+              "2012-01-01 23:00:00       5.3  ...                Cloudy\n",
+              "2012-01-02 00:00:00       5.2  ...          Rain Showers\n",
+              "2012-01-02 01:00:00       4.6  ...                Cloudy\n",
+              "2012-01-02 02:00:00       3.9  ...         Mostly Cloudy\n",
+              "2012-01-02 03:00:00       3.7  ...         Mostly Cloudy\n",
+              "2012-01-02 04:00:00       2.9  ...         Mostly Cloudy\n",
+              "2012-01-02 05:00:00       2.6  ...         Mostly Cloudy\n",
+              "...                       ...  ...                   ...\n",
+              "2012-12-30 18:00:00     -12.6  ...          Mainly Clear\n",
+              "2012-12-30 19:00:00     -13.4  ...          Mainly Clear\n",
+              "2012-12-30 20:00:00     -13.8  ...                 Clear\n",
+              "2012-12-30 21:00:00     -13.8  ...          Mainly Clear\n",
+              "2012-12-30 22:00:00     -13.7  ...          Mainly Clear\n",
+              "2012-12-30 23:00:00     -12.1  ...         Mostly Cloudy\n",
+              "2012-12-31 00:00:00     -11.1  ...                Cloudy\n",
+              "2012-12-31 01:00:00     -10.7  ...                Cloudy\n",
+              "2012-12-31 02:00:00     -10.1  ...                Cloudy\n",
+              "2012-12-31 03:00:00     -11.8  ...         Mostly Cloudy\n",
+              "2012-12-31 04:00:00     -10.5  ...                Cloudy\n",
+              "2012-12-31 05:00:00     -10.2  ...                Cloudy\n",
+              "2012-12-31 06:00:00      -9.7  ...                Cloudy\n",
+              "2012-12-31 07:00:00      -9.3  ...          Snow Showers\n",
+              "2012-12-31 08:00:00      -8.6  ...          Snow Showers\n",
+              "2012-12-31 09:00:00      -8.1  ...                  Snow\n",
+              "2012-12-31 10:00:00      -7.4  ...              Snow,Fog\n",
+              "2012-12-31 11:00:00      -6.7  ...                  Snow\n",
+              "2012-12-31 12:00:00      -5.8  ...                  Snow\n",
+              "2012-12-31 13:00:00      -4.6  ...                  Snow\n",
+              "2012-12-31 14:00:00      -3.4  ...                  Snow\n",
+              "2012-12-31 15:00:00      -2.3  ...                  Snow\n",
+              "2012-12-31 16:00:00      -1.4  ...                  Snow\n",
+              "2012-12-31 17:00:00      -1.1  ...                  Snow\n",
+              "2012-12-31 18:00:00      -1.3  ...                  Snow\n",
+              "2012-12-31 19:00:00       0.1  ...                  Snow\n",
+              "2012-12-31 20:00:00       0.2  ...                  Snow\n",
+              "2012-12-31 21:00:00      -0.5  ...                  Snow\n",
+              "2012-12-31 22:00:00      -0.2  ...                  Snow\n",
+              "2012-12-31 23:00:00       0.0  ...                  Snow\n",
+              "\n",
+              "[8784 rows x 7 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 7
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Uqf8d7d3WS-Q",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "ecaa74b3-a5f8-4b25-f717-4d109dcc7be2"
+      },
+      "source": [
+        "df_weather['Weather'].str.contains('Snow')"
+      ],
+      "execution_count": 8,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0       False\n",
+              "1       False\n",
+              "2       False\n",
+              "3       False\n",
+              "4       False\n",
+              "5       False\n",
+              "6       False\n",
+              "7       False\n",
+              "8       False\n",
+              "9       False\n",
+              "10      False\n",
+              "11      False\n",
+              "12      False\n",
+              "13      False\n",
+              "14      False\n",
+              "15      False\n",
+              "16      False\n",
+              "17      False\n",
+              "18      False\n",
+              "19      False\n",
+              "20      False\n",
+              "21      False\n",
+              "22      False\n",
+              "23      False\n",
+              "24      False\n",
+              "25      False\n",
+              "26      False\n",
+              "27      False\n",
+              "28      False\n",
+              "29      False\n",
+              "        ...  \n",
+              "8754    False\n",
+              "8755    False\n",
+              "8756    False\n",
+              "8757    False\n",
+              "8758    False\n",
+              "8759    False\n",
+              "8760    False\n",
+              "8761    False\n",
+              "8762    False\n",
+              "8763    False\n",
+              "8764    False\n",
+              "8765    False\n",
+              "8766    False\n",
+              "8767     True\n",
+              "8768     True\n",
+              "8769     True\n",
+              "8770     True\n",
+              "8771     True\n",
+              "8772     True\n",
+              "8773     True\n",
+              "8774     True\n",
+              "8775     True\n",
+              "8776     True\n",
+              "8777     True\n",
+              "8778     True\n",
+              "8779     True\n",
+              "8780     True\n",
+              "8781     True\n",
+              "8782     True\n",
+              "8783     True\n",
+              "Name: Weather, Length: 8784, dtype: bool"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 8
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "DI4vt5lTWmwN",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "f4a1ffa5-569a-489c-e432-acc6843c90b8"
+      },
+      "source": [
+        "df_weather['Weather'].str.contains('Rain')"
+      ],
+      "execution_count": 9,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0       False\n",
+              "1       False\n",
+              "2       False\n",
+              "3       False\n",
+              "4       False\n",
+              "5       False\n",
+              "6       False\n",
+              "7       False\n",
+              "8       False\n",
+              "9       False\n",
+              "10      False\n",
+              "11      False\n",
+              "12      False\n",
+              "13      False\n",
+              "14      False\n",
+              "15      False\n",
+              "16      False\n",
+              "17      False\n",
+              "18       True\n",
+              "19       True\n",
+              "20      False\n",
+              "21      False\n",
+              "22       True\n",
+              "23      False\n",
+              "24       True\n",
+              "25      False\n",
+              "26      False\n",
+              "27      False\n",
+              "28      False\n",
+              "29      False\n",
+              "        ...  \n",
+              "8754    False\n",
+              "8755    False\n",
+              "8756    False\n",
+              "8757    False\n",
+              "8758    False\n",
+              "8759    False\n",
+              "8760    False\n",
+              "8761    False\n",
+              "8762    False\n",
+              "8763    False\n",
+              "8764    False\n",
+              "8765    False\n",
+              "8766    False\n",
+              "8767    False\n",
+              "8768    False\n",
+              "8769    False\n",
+              "8770    False\n",
+              "8771    False\n",
+              "8772    False\n",
+              "8773    False\n",
+              "8774    False\n",
+              "8775    False\n",
+              "8776    False\n",
+              "8777    False\n",
+              "8778    False\n",
+              "8779    False\n",
+              "8780    False\n",
+              "8781    False\n",
+              "8782    False\n",
+              "8783    False\n",
+              "Name: Weather, Length: 8784, dtype: bool"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 9
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Aweq95dZWvO9",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "b4cc863a-2000-438e-ce05-d9c488cad296"
+      },
+      "source": [
+        "is_precipitation = df_weather['Weather'].str.contains('Snow') | df_weather['Weather'].str.contains('Rain')\n",
+        "is_precipitation"
+      ],
+      "execution_count": 10,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0       False\n",
+              "1       False\n",
+              "2       False\n",
+              "3       False\n",
+              "4       False\n",
+              "5       False\n",
+              "6       False\n",
+              "7       False\n",
+              "8       False\n",
+              "9       False\n",
+              "10      False\n",
+              "11      False\n",
+              "12      False\n",
+              "13      False\n",
+              "14      False\n",
+              "15      False\n",
+              "16      False\n",
+              "17      False\n",
+              "18       True\n",
+              "19       True\n",
+              "20      False\n",
+              "21      False\n",
+              "22       True\n",
+              "23      False\n",
+              "24       True\n",
+              "25      False\n",
+              "26      False\n",
+              "27      False\n",
+              "28      False\n",
+              "29      False\n",
+              "        ...  \n",
+              "8754    False\n",
+              "8755    False\n",
+              "8756    False\n",
+              "8757    False\n",
+              "8758    False\n",
+              "8759    False\n",
+              "8760    False\n",
+              "8761    False\n",
+              "8762    False\n",
+              "8763    False\n",
+              "8764    False\n",
+              "8765    False\n",
+              "8766    False\n",
+              "8767     True\n",
+              "8768     True\n",
+              "8769     True\n",
+              "8770     True\n",
+              "8771     True\n",
+              "8772     True\n",
+              "8773     True\n",
+              "8774     True\n",
+              "8775     True\n",
+              "8776     True\n",
+              "8777     True\n",
+              "8778     True\n",
+              "8779     True\n",
+              "8780     True\n",
+              "8781     True\n",
+              "8782     True\n",
+              "8783     True\n",
+              "Name: Weather, Length: 8784, dtype: bool"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 10
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "DKWSzh6lW_Ir",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 306
+        },
+        "outputId": "22a3de8a-41ca-4a86-ccef-1c910d7d4cdd"
+      },
+      "source": [
+        "df_weather['is_precipitation'] = is_precipitation\n",
+        "df_weather.head()"
+      ],
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Date/Time</th>\n",
+              "      <th>Temp (C)</th>\n",
+              "      <th>Dew Point Temp (C)</th>\n",
+              "      <th>Rel Hum (%)</th>\n",
+              "      <th>Wind Spd (km/h)</th>\n",
+              "      <th>Visibility (km)</th>\n",
+              "      <th>Stn Press (kPa)</th>\n",
+              "      <th>Weather</th>\n",
+              "      <th>is_precipitation</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>2012-01-01 00:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.9</td>\n",
+              "      <td>86</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2012-01-01 01:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.7</td>\n",
+              "      <td>87</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2012-01-01 02:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.4</td>\n",
+              "      <td>89</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.26</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>2012-01-01 03:00:00</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.2</td>\n",
+              "      <td>88</td>\n",
+              "      <td>6</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.27</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>2012-01-01 04:00:00</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.3</td>\n",
+              "      <td>88</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>101.23</td>\n",
+              "      <td>Fog</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            Date/Time  Temp (C)  ...               Weather  is_precipitation\n",
+              "0 2012-01-01 00:00:00      -1.8  ...                   Fog             False\n",
+              "1 2012-01-01 01:00:00      -1.8  ...                   Fog             False\n",
+              "2 2012-01-01 02:00:00      -1.8  ...  Freezing Drizzle,Fog             False\n",
+              "3 2012-01-01 03:00:00      -1.5  ...  Freezing Drizzle,Fog             False\n",
+              "4 2012-01-01 04:00:00      -1.5  ...                   Fog             False\n",
+              "\n",
+              "[5 rows x 9 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 12
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "W-HLzNjeXJDf",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 306
+        },
+        "outputId": "a0594b8b-746a-40eb-95da-34250f8a95f3"
+      },
+      "source": [
+        "df_weather['visibility (mi)'] = df_weather['Visibility (km)']*0.621\n",
+        "df_weather.head()"
+      ],
+      "execution_count": 13,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Date/Time</th>\n",
+              "      <th>Temp (C)</th>\n",
+              "      <th>Dew Point Temp (C)</th>\n",
+              "      <th>Rel Hum (%)</th>\n",
+              "      <th>Wind Spd (km/h)</th>\n",
+              "      <th>Visibility (km)</th>\n",
+              "      <th>Stn Press (kPa)</th>\n",
+              "      <th>Weather</th>\n",
+              "      <th>is_precipitation</th>\n",
+              "      <th>visibility (mi)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>2012-01-01 00:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.9</td>\n",
+              "      <td>86</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "      <td>False</td>\n",
+              "      <td>4.9680</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2012-01-01 01:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.7</td>\n",
+              "      <td>87</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>101.24</td>\n",
+              "      <td>Fog</td>\n",
+              "      <td>False</td>\n",
+              "      <td>4.9680</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2012-01-01 02:00:00</td>\n",
+              "      <td>-1.8</td>\n",
+              "      <td>-3.4</td>\n",
+              "      <td>89</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.26</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2.4840</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>2012-01-01 03:00:00</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.2</td>\n",
+              "      <td>88</td>\n",
+              "      <td>6</td>\n",
+              "      <td>4.0</td>\n",
+              "      <td>101.27</td>\n",
+              "      <td>Freezing Drizzle,Fog</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2.4840</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>2012-01-01 04:00:00</td>\n",
+              "      <td>-1.5</td>\n",
+              "      <td>-3.3</td>\n",
+              "      <td>88</td>\n",
+              "      <td>7</td>\n",
+              "      <td>4.8</td>\n",
+              "      <td>101.23</td>\n",
+              "      <td>Fog</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2.9808</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            Date/Time  Temp (C)  ...  is_precipitation  visibility (mi)\n",
+              "0 2012-01-01 00:00:00      -1.8  ...             False           4.9680\n",
+              "1 2012-01-01 01:00:00      -1.8  ...             False           4.9680\n",
+              "2 2012-01-01 02:00:00      -1.8  ...             False           2.4840\n",
+              "3 2012-01-01 03:00:00      -1.5  ...             False           2.4840\n",
+              "4 2012-01-01 04:00:00      -1.5  ...             False           2.9808\n",
+              "\n",
+              "[5 rows x 10 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 13
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0ZGBxJ_DXlLh",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Lending Club Data"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9Fv_aNMniGBK",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Get Data"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "DyFN4nuZXkbd",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 208
+        },
+        "outputId": "e019440c-51c7-45b2-c5b2-e50b323dc922"
+      },
+      "source": [
+        "!wget https://resources.lendingclub.com/LoanStats_2018Q4.csv.zip"
+      ],
+      "execution_count": 14,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "--2019-09-13 02:07:39--  https://resources.lendingclub.com/LoanStats_2018Q4.csv.zip\n",
+            "Resolving resources.lendingclub.com (resources.lendingclub.com)... 64.48.1.20\n",
+            "Connecting to resources.lendingclub.com (resources.lendingclub.com)|64.48.1.20|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: unspecified [application/zip]\n",
+            "Saving to: ‘LoanStats_2018Q4.csv.zip’\n",
+            "\n",
+            "LoanStats_2018Q4.cs     [        <=>         ]  21.58M   434KB/s    in 50s     \n",
+            "\n",
+            "2019-09-13 02:08:30 (438 KB/s) - ‘LoanStats_2018Q4.csv.zip’ saved [22631049]\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "FSYY1EgMYX-m",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 52
+        },
+        "outputId": "3d3a6b6d-87b5-43fe-9f03-bfbb0f96340f"
+      },
+      "source": [
+        "!unzip LoanStats_2018Q4.csv.zip"
+      ],
+      "execution_count": 15,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Archive:  LoanStats_2018Q4.csv.zip\n",
+            "  inflating: LoanStats_2018Q4.csv    \n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "KYn74a1PYekG",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 211
+        },
+        "outputId": "ed396edd-8b60-485e-e4ec-5134b8cf6c67"
+      },
+      "source": [
+        "!head LoanStats_2018Q4.csv"
+      ],
+      "execution_count": 16,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Notes offered by Prospectus (https://www.lendingclub.com/info/prospectus.action)\n",
+            "\"id\",\"member_id\",\"loan_amnt\",\"funded_amnt\",\"funded_amnt_inv\",\"term\",\"int_rate\",\"installment\",\"grade\",\"sub_grade\",\"emp_title\",\"emp_length\",\"home_ownership\",\"annual_inc\",\"verification_status\",\"issue_d\",\"loan_status\",\"pymnt_plan\",\"url\",\"desc\",\"purpose\",\"title\",\"zip_code\",\"addr_state\",\"dti\",\"delinq_2yrs\",\"earliest_cr_line\",\"inq_last_6mths\",\"mths_since_last_delinq\",\"mths_since_last_record\",\"open_acc\",\"pub_rec\",\"revol_bal\",\"revol_util\",\"total_acc\",\"initial_list_status\",\"out_prncp\",\"out_prncp_inv\",\"total_pymnt\",\"total_pymnt_inv\",\"total_rec_prncp\",\"total_rec_int\",\"total_rec_late_fee\",\"recoveries\",\"collection_recovery_fee\",\"last_pymnt_d\",\"last_pymnt_amnt\",\"next_pymnt_d\",\"last_credit_pull_d\",\"collections_12_mths_ex_med\",\"mths_since_last_major_derog\",\"policy_code\",\"application_type\",\"annual_inc_joint\",\"dti_joint\",\"verification_status_joint\",\"acc_now_delinq\",\"tot_coll_amt\",\"tot_cur_bal\",\"open_acc_6m\",\"open_act_il\",\"open_il_12m\",\"open_il_24m\",\"mths_since_rcnt_il\",\"total_bal_il\",\"il_util\",\"open_rv_12m\",\"open_rv_24m\",\"max_bal_bc\",\"all_util\",\"total_rev_hi_lim\",\"inq_fi\",\"total_cu_tl\",\"inq_last_12m\",\"acc_open_past_24mths\",\"avg_cur_bal\",\"bc_open_to_buy\",\"bc_util\",\"chargeoff_within_12_mths\",\"delinq_amnt\",\"mo_sin_old_il_acct\",\"mo_sin_old_rev_tl_op\",\"mo_sin_rcnt_rev_tl_op\",\"mo_sin_rcnt_tl\",\"mort_acc\",\"mths_since_recent_bc\",\"mths_since_recent_bc_dlq\",\"mths_since_recent_inq\",\"mths_since_recent_revol_delinq\",\"num_accts_ever_120_pd\",\"num_actv_bc_tl\",\"num_actv_rev_tl\",\"num_bc_sats\",\"num_bc_tl\",\"num_il_tl\",\"num_op_rev_tl\",\"num_rev_accts\",\"num_rev_tl_bal_gt_0\",\"num_sats\",\"num_tl_120dpd_2m\",\"num_tl_30dpd\",\"num_tl_90g_dpd_24m\",\"num_tl_op_past_12m\",\"pct_tl_nvr_dlq\",\"percent_bc_gt_75\",\"pub_rec_bankruptcies\",\"tax_liens\",\"tot_hi_cred_lim\",\"total_bal_ex_mort\",\"total_bc_limit\",\"total_il_high_credit_limit\",\"revol_bal_joint\",\"sec_app_earliest_cr_line\",\"sec_app_inq_last_6mths\",\"sec_app_mort_acc\",\"sec_app_open_acc\",\"sec_app_revol_util\",\"sec_app_open_act_il\",\"sec_app_num_rev_accts\",\"sec_app_chargeoff_within_12_mths\",\"sec_app_collections_12_mths_ex_med\",\"sec_app_mths_since_last_major_derog\",\"hardship_flag\",\"hardship_type\",\"hardship_reason\",\"hardship_status\",\"deferral_term\",\"hardship_amount\",\"hardship_start_date\",\"hardship_end_date\",\"payment_plan_start_date\",\"hardship_length\",\"hardship_dpd\",\"hardship_loan_status\",\"orig_projected_additional_accrued_interest\",\"hardship_payoff_balance_amount\",\"hardship_last_payment_amount\",\"debt_settlement_flag\",\"debt_settlement_flag_date\",\"settlement_status\",\"settlement_date\",\"settlement_amount\",\"settlement_percentage\",\"settlement_term\"\n",
+            "\"\",\"\",\"10000\",\"10000\",\"10000\",\" 36 months\",\" 10.33%\",\"324.23\",\"B\",\"B1\",\"\",\"< 1 year\",\"MORTGAGE\",\"280000\",\"Not Verified\",\"Dec-2018\",\"Current\",\"n\",\"\",\"\",\"debt_consolidation\",\"Debt consolidation\",\"974xx\",\"OR\",\"6.15\",\"2\",\"Jan-1996\",\"0\",\"18\",\"\",\"14\",\"0\",\"9082\",\"38%\",\"23\",\"w\",\"8289.30\",\"8289.30\",\"2261.0\",\"2261.00\",\"1710.70\",\"550.30\",\"0.0\",\"0.0\",\"0.0\",\"Jul-2019\",\"324.23\",\"Sep-2019\",\"Aug-2019\",\"0\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"671\",\"246828\",\"1\",\"3\",\"2\",\"3\",\"1\",\"48552\",\"62\",\"1\",\"3\",\"4923\",\"46\",\"23900\",\"2\",\"7\",\"1\",\"7\",\"17631\",\"11897\",\"43.1\",\"0\",\"0\",\"158\",\"275\",\"11\",\"1\",\"1\",\"11\",\"\",\"11\",\"\",\"0\",\"3\",\"4\",\"7\",\"7\",\"10\",\"9\",\"11\",\"4\",\"14\",\"0\",\"0\",\"0\",\"4\",\"91.3\",\"28.6\",\"0\",\"0\",\"367828\",\"61364\",\"20900\",\"54912\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n",
+            "\"\",\"\",\"4000\",\"4000\",\"4000\",\" 36 months\",\" 23.40%\",\"155.68\",\"E\",\"E1\",\"Security\",\"3 years\",\"RENT\",\"90000\",\"Source Verified\",\"Dec-2018\",\"Current\",\"n\",\"\",\"\",\"debt_consolidation\",\"Debt consolidation\",\"070xx\",\"NJ\",\"26.33\",\"0\",\"Sep-2006\",\"4\",\"59\",\"\",\"15\",\"0\",\"5199\",\"19.2%\",\"20\",\"w\",\"3423.38\",\"3423.38\",\"1081.96\",\"1081.96\",\"576.62\",\"505.34\",\"0.0\",\"0.0\",\"0.0\",\"Jul-2019\",\"155.68\",\"Sep-2019\",\"Aug-2019\",\"0\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"0\",\"66926\",\"5\",\"4\",\"3\",\"4\",\"5\",\"61727\",\"86\",\"6\",\"11\",\"1353\",\"68\",\"27100\",\"4\",\"0\",\"4\",\"15\",\"4462\",\"20174\",\"7.9\",\"0\",\"0\",\"147\",\"118\",\"2\",\"2\",\"0\",\"2\",\"\",\"0\",\"\",\"0\",\"5\",\"7\",\"9\",\"9\",\"8\",\"11\",\"12\",\"7\",\"15\",\"0\",\"0\",\"0\",\"9\",\"95\",\"0\",\"0\",\"0\",\"98655\",\"66926\",\"21900\",\"71555\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n",
+            "\"\",\"\",\"5000\",\"5000\",\"5000\",\" 36 months\",\" 17.97%\",\"180.69\",\"D\",\"D1\",\"Administrative\",\"6 years\",\"MORTGAGE\",\"59280\",\"Source Verified\",\"Dec-2018\",\"Late (31-120 days)\",\"n\",\"\",\"\",\"debt_consolidation\",\"Debt consolidation\",\"490xx\",\"MI\",\"10.51\",\"0\",\"Apr-2011\",\"0\",\"\",\"\",\"8\",\"0\",\"4599\",\"19.1%\",\"13\",\"w\",\"4456.17\",\"4456.17\",\"895.96\",\"895.96\",\"543.83\",\"352.13\",\"0.0\",\"0.0\",\"0.0\",\"Jun-2019\",\"180.69\",\"Sep-2019\",\"Aug-2019\",\"0\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"0\",\"110299\",\"0\",\"1\",\"0\",\"2\",\"14\",\"7150\",\"72\",\"0\",\"2\",\"0\",\"35\",\"24100\",\"1\",\"5\",\"0\",\"4\",\"18383\",\"13800\",\"0\",\"0\",\"0\",\"87\",\"92\",\"15\",\"14\",\"2\",\"77\",\"\",\"14\",\"\",\"0\",\"0\",\"3\",\"3\",\"3\",\"4\",\"6\",\"7\",\"3\",\"8\",\"0\",\"0\",\"0\",\"0\",\"100\",\"0\",\"0\",\"0\",\"136927\",\"11749\",\"13800\",\"10000\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n",
+            "\"\",\"\",\"23000\",\"23000\",\"23000\",\" 60 months\",\" 20.89%\",\"620.81\",\"D\",\"D4\",\"Operator\",\"5 years\",\"RENT\",\"68107\",\"Source Verified\",\"Dec-2018\",\"Current\",\"n\",\"\",\"\",\"debt_consolidation\",\"Debt consolidation\",\"672xx\",\"KS\",\"0.52\",\"0\",\"Feb-1997\",\"0\",\"\",\"\",\"5\",\"0\",\"976\",\"13%\",\"10\",\"w\",\"21353.16\",\"21353.16\",\"4307.45\",\"4307.45\",\"1646.84\",\"2660.61\",\"0.0\",\"0.0\",\"0.0\",\"Jul-2019\",\"620.81\",\"Sep-2019\",\"Aug-2019\",\"1\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"2693\",\"976\",\"0\",\"0\",\"0\",\"0\",\"36\",\"0\",\"\",\"3\",\"4\",\"0\",\"13\",\"7500\",\"2\",\"2\",\"4\",\"4\",\"195\",\"3300\",\"0\",\"0\",\"0\",\"237\",\"262\",\"10\",\"10\",\"0\",\"10\",\"\",\"9\",\"\",\"0\",\"0\",\"1\",\"3\",\"4\",\"3\",\"5\",\"7\",\"1\",\"5\",\"0\",\"0\",\"0\",\"3\",\"100\",\"0\",\"0\",\"0\",\"7500\",\"976\",\"3300\",\"0\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n",
+            "\"\",\"\",\"8000\",\"8000\",\"8000\",\" 36 months\",\" 23.40%\",\"311.35\",\"E\",\"E1\",\"Manager\",\"10+ years\",\"OWN\",\"43000\",\"Source Verified\",\"Dec-2018\",\"Current\",\"n\",\"\",\"\",\"debt_consolidation\",\"Debt consolidation\",\"357xx\",\"AL\",\"33.24\",\"0\",\"Jan-1995\",\"0\",\"\",\"107\",\"8\",\"1\",\"9019\",\"81.3%\",\"16\",\"w\",\"6846.83\",\"6846.83\",\"2163.85\",\"2163.85\",\"1153.17\",\"1010.68\",\"0.0\",\"0.0\",\"0.0\",\"Jul-2019\",\"311.35\",\"Sep-2019\",\"Aug-2019\",\"0\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"0\",\"169223\",\"0\",\"3\",\"2\",\"2\",\"7\",\"22059\",\"69\",\"0\",\"0\",\"2174\",\"72\",\"11100\",\"1\",\"1\",\"1\",\"2\",\"21153\",\"126\",\"94.5\",\"0\",\"0\",\"148\",\"287\",\"44\",\"7\",\"1\",\"51\",\"\",\"7\",\"\",\"0\",\"1\",\"4\",\"1\",\"2\",\"8\",\"4\",\"7\",\"4\",\"8\",\"0\",\"0\",\"0\",\"2\",\"100\",\"100\",\"1\",\"0\",\"199744\",\"31078\",\"2300\",\"32206\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n",
+            "\"\",\"\",\"32075\",\"32075\",\"32075\",\" 60 months\",\" 11.80%\",\"710.26\",\"B\",\"B4\",\"Nursing Supervisor\",\"10+ years\",\"MORTGAGE\",\"150000\",\"Not Verified\",\"Dec-2018\",\"Current\",\"n\",\"\",\"\",\"credit_card\",\"Credit card refinancing\",\"231xx\",\"VA\",\"22.21\",\"0\",\"Aug-2005\",\"0\",\"\",\"\",\"17\",\"0\",\"19077\",\"32%\",\"24\",\"w\",\"29228.12\",\"29228.12\",\"4940.28\",\"4940.28\",\"2846.88\",\"2093.40\",\"0.0\",\"0.0\",\"0.0\",\"Jul-2019\",\"710.26\",\"Sep-2019\",\"Aug-2019\",\"0\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"0\",\"272667\",\"1\",\"4\",\"1\",\"1\",\"9\",\"37558\",\"47\",\"1\",\"1\",\"3910\",\"41\",\"59600\",\"1\",\"2\",\"0\",\"3\",\"16039\",\"10446\",\"47.8\",\"0\",\"0\",\"160\",\"70\",\"4\",\"4\",\"2\",\"27\",\"\",\"14\",\"\",\"0\",\"4\",\"10\",\"4\",\"4\",\"8\",\"12\",\"14\",\"10\",\"17\",\"0\",\"0\",\"0\",\"2\",\"100\",\"50\",\"0\",\"0\",\"360433\",\"56635\",\"20000\",\"80125\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n",
+            "\"\",\"\",\"9600\",\"9600\",\"9600\",\" 36 months\",\" 12.98%\",\"323.37\",\"B\",\"B5\",\"\",\"n/a\",\"MORTGAGE\",\"35704\",\"Not Verified\",\"Dec-2018\",\"Current\",\"n\",\"\",\"\",\"home_improvement\",\"Home improvement\",\"401xx\",\"KY\",\"0.84\",\"0\",\"Nov-2003\",\"0\",\"69\",\"\",\"5\",\"0\",\"748\",\"11.5%\",\"23\",\"w\",\"8012.51\",\"8012.51\",\"2287.83\",\"2287.83\",\"1587.49\",\"700.34\",\"0.0\",\"0.0\",\"0.0\",\"Aug-2019\",\"323.37\",\"Sep-2019\",\"Aug-2019\",\"0\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"0\",\"748\",\"0\",\"0\",\"0\",\"0\",\"44\",\"0\",\"\",\"0\",\"3\",\"748\",\"12\",\"6500\",\"0\",\"0\",\"1\",\"3\",\"150\",\"3452\",\"17.8\",\"0\",\"0\",\"181\",\"100\",\"13\",\"13\",\"0\",\"16\",\"\",\"3\",\"\",\"0\",\"1\",\"1\",\"2\",\"2\",\"16\",\"5\",\"7\",\"1\",\"5\",\"0\",\"0\",\"0\",\"0\",\"95.5\",\"0\",\"0\",\"0\",\"6500\",\"748\",\"4200\",\"0\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n",
+            "\"\",\"\",\"30000\",\"30000\",\"30000\",\" 60 months\",\" 18.94%\",\"777.23\",\"D\",\"D2\",\"Postmaster \",\"10+ years\",\"MORTGAGE\",\"90000\",\"Source Verified\",\"Dec-2018\",\"Current\",\"n\",\"\",\"\",\"debt_consolidation\",\"Debt consolidation\",\"713xx\",\"LA\",\"26.52\",\"0\",\"Jun-1987\",\"0\",\"71\",\"75\",\"13\",\"1\",\"12315\",\"24.2%\",\"44\",\"w\",\"19969.40\",\"19969.40\",\"12893.26\",\"12893.26\",\"10030.60\",\"2862.66\",\"0.0\",\"0.0\",\"0.0\",\"Jul-2019\",\"777.23\",\"Sep-2019\",\"Aug-2019\",\"0\",\"\",\"1\",\"Individual\",\"\",\"\",\"\",\"0\",\"1208\",\"321915\",\"4\",\"4\",\"2\",\"3\",\"3\",\"87153\",\"88\",\"4\",\"5\",\"998\",\"57\",\"50800\",\"2\",\"15\",\"2\",\"10\",\"24763\",\"13761\",\"8.3\",\"0\",\"0\",\"163\",\"378\",\"4\",\"3\",\"3\",\"4\",\"\",\"4\",\"\",\"0\",\"2\",\"4\",\"4\",\"9\",\"27\",\"8\",\"14\",\"4\",\"13\",\"0\",\"0\",\"0\",\"6\",\"95\",\"0\",\"1\",\"0\",\"372872\",\"99468\",\"15000\",\"94072\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"N\",\"\",\"\",\"\",\"\",\"\",\"\"\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Um4OaTU1iKIC",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Load Data"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "5a0UPTFVYjWA",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 343
+        },
+        "outputId": "229bbcf2-411d-435c-a5c8-a3a4af75e1f8"
+      },
+      "source": [
+        "df = pd.read_csv('LoanStats_2018Q4.csv')\n",
+        "df.head()"
+      ],
+      "execution_count": 17,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (0,1,2,3,4,7,13,18,19,24,25,27,28,29,30,31,32,34,36,37,38,39,40,41,42,43,44,46,49,50,51,53,54,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,113,114,115,116,117,118,119,120,121,123,124,125,126,127,128,129,130,131,132,133,134,135,136,138,139,140,141,142,143) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+            "  interactivity=interactivity, compiler=compiler, result=result)\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
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+              "    .dataframe tbody tr th {\n",
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+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th>Notes offered by Prospectus (https://www.lendingclub.com/info/prospectus.action)</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>id</th>\n",
+              "      <th>member_id</th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>url</th>\n",
+              "      <th>desc</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>mths_since_last_record</th>\n",
+              "      <th>open_acc</th>\n",
+              "      <th>pub_rec</th>\n",
+              "      <th>revol_bal</th>\n",
+              "      <th>revol_util</th>\n",
+              "      <th>total_acc</th>\n",
+              "      <th>initial_list_status</th>\n",
+              "      <th>out_prncp</th>\n",
+              "      <th>out_prncp_inv</th>\n",
+              "      <th>total_pymnt</th>\n",
+              "      <th>total_pymnt_inv</th>\n",
+              "      <th>total_rec_prncp</th>\n",
+              "      <th>total_rec_int</th>\n",
+              "      <th>total_rec_late_fee</th>\n",
+              "      <th>recoveries</th>\n",
+              "      <th>collection_recovery_fee</th>\n",
+              "      <th>last_pymnt_d</th>\n",
+              "      <th>last_pymnt_amnt</th>\n",
+              "      <th>next_pymnt_d</th>\n",
+              "      <th>last_credit_pull_d</th>\n",
+              "      <th>collections_12_mths_ex_med</th>\n",
+              "      <th>mths_since_last_major_derog</th>\n",
+              "      <th>policy_code</th>\n",
+              "      <th>application_type</th>\n",
+              "      <th>annual_inc_joint</th>\n",
+              "      <th>dti_joint</th>\n",
+              "      <th>verification_status_joint</th>\n",
+              "      <th>acc_now_delinq</th>\n",
+              "      <th>tot_coll_amt</th>\n",
+              "      <th>tot_cur_bal</th>\n",
+              "      <th>open_acc_6m</th>\n",
+              "      <th>open_act_il</th>\n",
+              "      <th>open_il_12m</th>\n",
+              "      <th>open_il_24m</th>\n",
+              "      <th>mths_since_rcnt_il</th>\n",
+              "      <th>total_bal_il</th>\n",
+              "      <th>il_util</th>\n",
+              "      <th>open_rv_12m</th>\n",
+              "      <th>open_rv_24m</th>\n",
+              "      <th>max_bal_bc</th>\n",
+              "      <th>all_util</th>\n",
+              "      <th>total_rev_hi_lim</th>\n",
+              "      <th>inq_fi</th>\n",
+              "      <th>total_cu_tl</th>\n",
+              "      <th>inq_last_12m</th>\n",
+              "      <th>acc_open_past_24mths</th>\n",
+              "      <th>avg_cur_bal</th>\n",
+              "      <th>bc_open_to_buy</th>\n",
+              "      <th>bc_util</th>\n",
+              "      <th>chargeoff_within_12_mths</th>\n",
+              "      <th>delinq_amnt</th>\n",
+              "      <th>mo_sin_old_il_acct</th>\n",
+              "      <th>mo_sin_old_rev_tl_op</th>\n",
+              "      <th>mo_sin_rcnt_rev_tl_op</th>\n",
+              "      <th>mo_sin_rcnt_tl</th>\n",
+              "      <th>mort_acc</th>\n",
+              "      <th>mths_since_recent_bc</th>\n",
+              "      <th>mths_since_recent_bc_dlq</th>\n",
+              "      <th>mths_since_recent_inq</th>\n",
+              "      <th>mths_since_recent_revol_delinq</th>\n",
+              "      <th>num_accts_ever_120_pd</th>\n",
+              "      <th>num_actv_bc_tl</th>\n",
+              "      <th>num_actv_rev_tl</th>\n",
+              "      <th>num_bc_sats</th>\n",
+              "      <th>num_bc_tl</th>\n",
+              "      <th>num_il_tl</th>\n",
+              "      <th>num_op_rev_tl</th>\n",
+              "      <th>num_rev_accts</th>\n",
+              "      <th>num_rev_tl_bal_gt_0</th>\n",
+              "      <th>num_sats</th>\n",
+              "      <th>num_tl_120dpd_2m</th>\n",
+              "      <th>num_tl_30dpd</th>\n",
+              "      <th>num_tl_90g_dpd_24m</th>\n",
+              "      <th>num_tl_op_past_12m</th>\n",
+              "      <th>pct_tl_nvr_dlq</th>\n",
+              "      <th>percent_bc_gt_75</th>\n",
+              "      <th>pub_rec_bankruptcies</th>\n",
+              "      <th>tax_liens</th>\n",
+              "      <th>tot_hi_cred_lim</th>\n",
+              "      <th>total_bal_ex_mort</th>\n",
+              "      <th>total_bc_limit</th>\n",
+              "      <th>total_il_high_credit_limit</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>hardship_flag</th>\n",
+              "      <th>hardship_type</th>\n",
+              "      <th>hardship_reason</th>\n",
+              "      <th>hardship_status</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>hardship_amount</th>\n",
+              "      <th>hardship_start_date</th>\n",
+              "      <th>hardship_end_date</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>hardship_length</th>\n",
+              "      <th>hardship_dpd</th>\n",
+              "      <th>hardship_loan_status</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>hardship_payoff_balance_amount</th>\n",
+              "      <th>hardship_last_payment_amount</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <td>settlement_term</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th rowspan=\"4\" valign=\"top\">NaN</th>\n",
+              "      <th rowspan=\"4\" valign=\"top\">NaN</th>\n",
+              "      <th>10000</th>\n",
+              "      <th>10000</th>\n",
+              "      <th>10000</th>\n",
+              "      <th>36 months</th>\n",
+              "      <th>10.33%</th>\n",
+              "      <th>324.23</th>\n",
+              "      <th>B</th>\n",
+              "      <th>B1</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>&lt; 1 year</th>\n",
+              "      <th>MORTGAGE</th>\n",
+              "      <th>280000</th>\n",
+              "      <th>Not Verified</th>\n",
+              "      <th>Dec-2018</th>\n",
+              "      <th>Current</th>\n",
+              "      <th>n</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>debt_consolidation</th>\n",
+              "      <th>Debt consolidation</th>\n",
+              "      <th>974xx</th>\n",
+              "      <th>OR</th>\n",
+              "      <th>6.15</th>\n",
+              "      <th>2</th>\n",
+              "      <th>Jan-1996</th>\n",
+              "      <th>0</th>\n",
+              "      <th>18</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>14</th>\n",
+              "      <th>0</th>\n",
+              "      <th>9082</th>\n",
+              "      <th>38%</th>\n",
+              "      <th>23</th>\n",
+              "      <th>w</th>\n",
+              "      <th>8289.30</th>\n",
+              "      <th>8289.30</th>\n",
+              "      <th>2261.0</th>\n",
+              "      <th>2261.00</th>\n",
+              "      <th>1710.70</th>\n",
+              "      <th>550.30</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>Jul-2019</th>\n",
+              "      <th>324.23</th>\n",
+              "      <th>Sep-2019</th>\n",
+              "      <th>Aug-2019</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>1</th>\n",
+              "      <th>Individual</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>671</th>\n",
+              "      <th>246828</th>\n",
+              "      <th>1</th>\n",
+              "      <th>3</th>\n",
+              "      <th>2</th>\n",
+              "      <th>3</th>\n",
+              "      <th>1</th>\n",
+              "      <th>48552</th>\n",
+              "      <th>62</th>\n",
+              "      <th>1</th>\n",
+              "      <th>3</th>\n",
+              "      <th>4923</th>\n",
+              "      <th>46</th>\n",
+              "      <th>23900</th>\n",
+              "      <th>2</th>\n",
+              "      <th>7</th>\n",
+              "      <th>1</th>\n",
+              "      <th>7</th>\n",
+              "      <th>17631</th>\n",
+              "      <th>11897</th>\n",
+              "      <th>43.1</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>158</th>\n",
+              "      <th>275</th>\n",
+              "      <th>11</th>\n",
+              "      <th>1</th>\n",
+              "      <th>1</th>\n",
+              "      <th>11</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>11</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>3</th>\n",
+              "      <th>4</th>\n",
+              "      <th>7</th>\n",
+              "      <th>7</th>\n",
+              "      <th>10</th>\n",
+              "      <th>9</th>\n",
+              "      <th>11</th>\n",
+              "      <th>4</th>\n",
+              "      <th>14</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>4</th>\n",
+              "      <th>91.3</th>\n",
+              "      <th>28.6</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>367828</th>\n",
+              "      <th>61364</th>\n",
+              "      <th>20900</th>\n",
+              "      <th>54912</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4000</th>\n",
+              "      <th>4000</th>\n",
+              "      <th>4000</th>\n",
+              "      <th>36 months</th>\n",
+              "      <th>23.40%</th>\n",
+              "      <th>155.68</th>\n",
+              "      <th>E</th>\n",
+              "      <th>E1</th>\n",
+              "      <th>Security</th>\n",
+              "      <th>3 years</th>\n",
+              "      <th>RENT</th>\n",
+              "      <th>90000</th>\n",
+              "      <th>Source Verified</th>\n",
+              "      <th>Dec-2018</th>\n",
+              "      <th>Current</th>\n",
+              "      <th>n</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>debt_consolidation</th>\n",
+              "      <th>Debt consolidation</th>\n",
+              "      <th>070xx</th>\n",
+              "      <th>NJ</th>\n",
+              "      <th>26.33</th>\n",
+              "      <th>0</th>\n",
+              "      <th>Sep-2006</th>\n",
+              "      <th>4</th>\n",
+              "      <th>59</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>15</th>\n",
+              "      <th>0</th>\n",
+              "      <th>5199</th>\n",
+              "      <th>19.2%</th>\n",
+              "      <th>20</th>\n",
+              "      <th>w</th>\n",
+              "      <th>3423.38</th>\n",
+              "      <th>3423.38</th>\n",
+              "      <th>1081.96</th>\n",
+              "      <th>1081.96</th>\n",
+              "      <th>576.62</th>\n",
+              "      <th>505.34</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>Jul-2019</th>\n",
+              "      <th>155.68</th>\n",
+              "      <th>Sep-2019</th>\n",
+              "      <th>Aug-2019</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>1</th>\n",
+              "      <th>Individual</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>66926</th>\n",
+              "      <th>5</th>\n",
+              "      <th>4</th>\n",
+              "      <th>3</th>\n",
+              "      <th>4</th>\n",
+              "      <th>5</th>\n",
+              "      <th>61727</th>\n",
+              "      <th>86</th>\n",
+              "      <th>6</th>\n",
+              "      <th>11</th>\n",
+              "      <th>1353</th>\n",
+              "      <th>68</th>\n",
+              "      <th>27100</th>\n",
+              "      <th>4</th>\n",
+              "      <th>0</th>\n",
+              "      <th>4</th>\n",
+              "      <th>15</th>\n",
+              "      <th>4462</th>\n",
+              "      <th>20174</th>\n",
+              "      <th>7.9</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>147</th>\n",
+              "      <th>118</th>\n",
+              "      <th>2</th>\n",
+              "      <th>2</th>\n",
+              "      <th>0</th>\n",
+              "      <th>2</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>5</th>\n",
+              "      <th>7</th>\n",
+              "      <th>9</th>\n",
+              "      <th>9</th>\n",
+              "      <th>8</th>\n",
+              "      <th>11</th>\n",
+              "      <th>12</th>\n",
+              "      <th>7</th>\n",
+              "      <th>15</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>9</th>\n",
+              "      <th>95</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>98655</th>\n",
+              "      <th>66926</th>\n",
+              "      <th>21900</th>\n",
+              "      <th>71555</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5000</th>\n",
+              "      <th>5000</th>\n",
+              "      <th>5000</th>\n",
+              "      <th>36 months</th>\n",
+              "      <th>17.97%</th>\n",
+              "      <th>180.69</th>\n",
+              "      <th>D</th>\n",
+              "      <th>D1</th>\n",
+              "      <th>Administrative</th>\n",
+              "      <th>6 years</th>\n",
+              "      <th>MORTGAGE</th>\n",
+              "      <th>59280</th>\n",
+              "      <th>Source Verified</th>\n",
+              "      <th>Dec-2018</th>\n",
+              "      <th>Late (31-120 days)</th>\n",
+              "      <th>n</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>debt_consolidation</th>\n",
+              "      <th>Debt consolidation</th>\n",
+              "      <th>490xx</th>\n",
+              "      <th>MI</th>\n",
+              "      <th>10.51</th>\n",
+              "      <th>0</th>\n",
+              "      <th>Apr-2011</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>8</th>\n",
+              "      <th>0</th>\n",
+              "      <th>4599</th>\n",
+              "      <th>19.1%</th>\n",
+              "      <th>13</th>\n",
+              "      <th>w</th>\n",
+              "      <th>4456.17</th>\n",
+              "      <th>4456.17</th>\n",
+              "      <th>895.96</th>\n",
+              "      <th>895.96</th>\n",
+              "      <th>543.83</th>\n",
+              "      <th>352.13</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>Jun-2019</th>\n",
+              "      <th>180.69</th>\n",
+              "      <th>Sep-2019</th>\n",
+              "      <th>Aug-2019</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>1</th>\n",
+              "      <th>Individual</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>110299</th>\n",
+              "      <th>0</th>\n",
+              "      <th>1</th>\n",
+              "      <th>0</th>\n",
+              "      <th>2</th>\n",
+              "      <th>14</th>\n",
+              "      <th>7150</th>\n",
+              "      <th>72</th>\n",
+              "      <th>0</th>\n",
+              "      <th>2</th>\n",
+              "      <th>0</th>\n",
+              "      <th>35</th>\n",
+              "      <th>24100</th>\n",
+              "      <th>1</th>\n",
+              "      <th>5</th>\n",
+              "      <th>0</th>\n",
+              "      <th>4</th>\n",
+              "      <th>18383</th>\n",
+              "      <th>13800</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>87</th>\n",
+              "      <th>92</th>\n",
+              "      <th>15</th>\n",
+              "      <th>14</th>\n",
+              "      <th>2</th>\n",
+              "      <th>77</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>14</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>3</th>\n",
+              "      <th>3</th>\n",
+              "      <th>3</th>\n",
+              "      <th>4</th>\n",
+              "      <th>6</th>\n",
+              "      <th>7</th>\n",
+              "      <th>3</th>\n",
+              "      <th>8</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>100</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>136927</th>\n",
+              "      <th>11749</th>\n",
+              "      <th>13800</th>\n",
+              "      <th>10000</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>23000</th>\n",
+              "      <th>23000</th>\n",
+              "      <th>23000</th>\n",
+              "      <th>60 months</th>\n",
+              "      <th>20.89%</th>\n",
+              "      <th>620.81</th>\n",
+              "      <th>D</th>\n",
+              "      <th>D4</th>\n",
+              "      <th>Operator</th>\n",
+              "      <th>5 years</th>\n",
+              "      <th>RENT</th>\n",
+              "      <th>68107</th>\n",
+              "      <th>Source Verified</th>\n",
+              "      <th>Dec-2018</th>\n",
+              "      <th>Current</th>\n",
+              "      <th>n</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>debt_consolidation</th>\n",
+              "      <th>Debt consolidation</th>\n",
+              "      <th>672xx</th>\n",
+              "      <th>KS</th>\n",
+              "      <th>0.52</th>\n",
+              "      <th>0</th>\n",
+              "      <th>Feb-1997</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>5</th>\n",
+              "      <th>0</th>\n",
+              "      <th>976</th>\n",
+              "      <th>13%</th>\n",
+              "      <th>10</th>\n",
+              "      <th>w</th>\n",
+              "      <th>21353.16</th>\n",
+              "      <th>21353.16</th>\n",
+              "      <th>4307.45</th>\n",
+              "      <th>4307.45</th>\n",
+              "      <th>1646.84</th>\n",
+              "      <th>2660.61</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>0.0</th>\n",
+              "      <th>Jul-2019</th>\n",
+              "      <th>620.81</th>\n",
+              "      <th>Sep-2019</th>\n",
+              "      <th>Aug-2019</th>\n",
+              "      <th>1</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>1</th>\n",
+              "      <th>Individual</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>2693</th>\n",
+              "      <th>976</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>36</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>3</th>\n",
+              "      <th>4</th>\n",
+              "      <th>0</th>\n",
+              "      <th>13</th>\n",
+              "      <th>7500</th>\n",
+              "      <th>2</th>\n",
+              "      <th>2</th>\n",
+              "      <th>4</th>\n",
+              "      <th>4</th>\n",
+              "      <th>195</th>\n",
+              "      <th>3300</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>237</th>\n",
+              "      <th>262</th>\n",
+              "      <th>10</th>\n",
+              "      <th>10</th>\n",
+              "      <th>0</th>\n",
+              "      <th>10</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>9</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>1</th>\n",
+              "      <th>3</th>\n",
+              "      <th>4</th>\n",
+              "      <th>3</th>\n",
+              "      <th>5</th>\n",
+              "      <th>7</th>\n",
+              "      <th>1</th>\n",
+              "      <th>5</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>3</th>\n",
+              "      <th>100</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>0</th>\n",
+              "      <th>7500</th>\n",
+              "      <th>976</th>\n",
+              "      <th>3300</th>\n",
+              "      <th>0</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>N</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <th>NaN</th>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         Notes offered by Prospectus (https://www.lendingclub.com/info/prospectus.action)\n",
+              "id  member_id loan_amnt funded_amnt funded_amnt_inv term       int_rate installment grade sub_grade emp_title      emp_length home_ownership annual_inc verification_status issue_d  loan_status        pymnt_plan url desc purpose            title              zip_code addr_state dti   delinq_2yrs earliest_cr_line inq_last_6mths mths_since_last_delinq mths_since_last_record open_acc pub_rec revol_bal revol_util total_acc initial_list_status out_prncp out_prncp_inv total_pymnt total_pymnt_inv total_rec_prncp total_rec_int total_rec_late_fee recoveries collection_recovery_fee last_pymnt_d last_pymnt_amnt next_pymnt_d last_credit_pull_d collections_12_mths_ex_med mths_since_last_major_derog policy_code application_type annual_inc_joint dti_joint verification_status_joint acc_now_delinq tot_coll_amt tot_cur_bal open_acc_6m open_act_il open_il_12m open_il_24m mths_since_rcnt_il total_bal_il il_util open_rv_12m open_rv_24m max_bal_bc all_util total_rev_hi_lim inq_fi total_cu_tl inq_last_12m acc_open_past_24mths avg_cur_bal bc_open_to_buy bc_util chargeoff_within_12_mths delinq_amnt mo_sin_old_il_acct mo_sin_old_rev_tl_op mo_sin_rcnt_rev_tl_op mo_sin_rcnt_tl mort_acc mths_since_recent_bc mths_since_recent_bc_dlq mths_since_recent_inq mths_since_recent_revol_delinq num_accts_ever_120_pd num_actv_bc_tl num_actv_rev_tl num_bc_sats num_bc_tl num_il_tl num_op_rev_tl num_rev_accts num_rev_tl_bal_gt_0 num_sats num_tl_120dpd_2m num_tl_30dpd num_tl_90g_dpd_24m num_tl_op_past_12m pct_tl_nvr_dlq percent_bc_gt_75 pub_rec_bankruptcies tax_liens tot_hi_cred_lim total_bal_ex_mort total_bc_limit total_il_high_credit_limit revol_bal_joint sec_app_earliest_cr_line sec_app_inq_last_6mths sec_app_mort_acc sec_app_open_acc sec_app_revol_util sec_app_open_act_il sec_app_num_rev_accts sec_app_chargeoff_within_12_mths sec_app_collections_12_mths_ex_med sec_app_mths_since_last_major_derog hardship_flag hardship_type hardship_reason hardship_status deferral_term hardship_amount hardship_start_date hardship_end_date payment_plan_start_date hardship_length hardship_dpd hardship_loan_status orig_projected_additional_accrued_interest hardship_payoff_balance_amount hardship_last_payment_amount debt_settlement_flag debt_settlement_flag_date settlement_status settlement_date settlement_amount settlement_percentage                                    settlement_term                              \n",
+              "NaN NaN       10000     10000       10000            36 months  10.33%  324.23      B     B1        NaN            < 1 year   MORTGAGE       280000     Not Verified        Dec-2018 Current            n          NaN NaN  debt_consolidation Debt consolidation 974xx    OR         6.15  2           Jan-1996         0              18                     NaN                    14       0       9082      38%        23        w                   8289.30   8289.30       2261.0      2261.00         1710.70         550.30        0.0                0.0        0.0                     Jul-2019     324.23          Sep-2019     Aug-2019           0                          NaN                         1           Individual       NaN              NaN       NaN                       0              671          246828      1           3           2           3           1                  48552        62      1           3           4923       46       23900            2      7           1            7                    17631       11897          43.1    0                        0           158                275                  11                    1              1        11                   NaN                      11                    NaN                            0                     3              4               7           7         10        9             11            4                   14       0                0            0                  4                  91.3           28.6             0                    0         367828          61364             20900          54912                      NaN             NaN                      NaN                    NaN              NaN              NaN                NaN                 NaN                   NaN                              NaN                                NaN                                 N             NaN           NaN             NaN             NaN           NaN             NaN                 NaN               NaN                     NaN             NaN          NaN                  NaN                                        NaN                            NaN                          N                    NaN                       NaN               NaN             NaN               NaN                                                                  NaN                              \n",
+              "              4000      4000        4000             36 months  23.40%  155.68      E     E1        Security       3 years    RENT           90000      Source Verified     Dec-2018 Current            n          NaN NaN  debt_consolidation Debt consolidation 070xx    NJ         26.33 0           Sep-2006         4              59                     NaN                    15       0       5199      19.2%      20        w                   3423.38   3423.38       1081.96     1081.96         576.62          505.34        0.0                0.0        0.0                     Jul-2019     155.68          Sep-2019     Aug-2019           0                          NaN                         1           Individual       NaN              NaN       NaN                       0              0            66926       5           4           3           4           5                  61727        86      6           11          1353       68       27100            4      0           4            15                   4462        20174          7.9     0                        0           147                118                  2                     2              0        2                    NaN                      0                     NaN                            0                     5              7               9           9         8         11            12            7                   15       0                0            0                  9                  95             0                0                    0         98655           66926             21900          71555                      NaN             NaN                      NaN                    NaN              NaN              NaN                NaN                 NaN                   NaN                              NaN                                NaN                                 N             NaN           NaN             NaN             NaN           NaN             NaN                 NaN               NaN                     NaN             NaN          NaN                  NaN                                        NaN                            NaN                          N                    NaN                       NaN               NaN             NaN               NaN                                                                  NaN                              \n",
+              "              5000      5000        5000             36 months  17.97%  180.69      D     D1        Administrative 6 years    MORTGAGE       59280      Source Verified     Dec-2018 Late (31-120 days) n          NaN NaN  debt_consolidation Debt consolidation 490xx    MI         10.51 0           Apr-2011         0              NaN                    NaN                    8        0       4599      19.1%      13        w                   4456.17   4456.17       895.96      895.96          543.83          352.13        0.0                0.0        0.0                     Jun-2019     180.69          Sep-2019     Aug-2019           0                          NaN                         1           Individual       NaN              NaN       NaN                       0              0            110299      0           1           0           2           14                 7150         72      0           2           0          35       24100            1      5           0            4                    18383       13800          0       0                        0           87                 92                   15                    14             2        77                   NaN                      14                    NaN                            0                     0              3               3           3         4         6             7             3                   8        0                0            0                  0                  100            0                0                    0         136927          11749             13800          10000                      NaN             NaN                      NaN                    NaN              NaN              NaN                NaN                 NaN                   NaN                              NaN                                NaN                                 N             NaN           NaN             NaN             NaN           NaN             NaN                 NaN               NaN                     NaN             NaN          NaN                  NaN                                        NaN                            NaN                          N                    NaN                       NaN               NaN             NaN               NaN                                                                  NaN                              \n",
+              "              23000     23000       23000            60 months  20.89%  620.81      D     D4        Operator       5 years    RENT           68107      Source Verified     Dec-2018 Current            n          NaN NaN  debt_consolidation Debt consolidation 672xx    KS         0.52  0           Feb-1997         0              NaN                    NaN                    5        0       976       13%        10        w                   21353.16  21353.16      4307.45     4307.45         1646.84         2660.61       0.0                0.0        0.0                     Jul-2019     620.81          Sep-2019     Aug-2019           1                          NaN                         1           Individual       NaN              NaN       NaN                       0              2693         976         0           0           0           0           36                 0            NaN     3           4           0          13       7500             2      2           4            4                    195         3300           0       0                        0           237                262                  10                    10             0        10                   NaN                      9                     NaN                            0                     0              1               3           4         3         5             7             1                   5        0                0            0                  3                  100            0                0                    0         7500            976               3300           0                          NaN             NaN                      NaN                    NaN              NaN              NaN                NaN                 NaN                   NaN                              NaN                                NaN                                 N             NaN           NaN             NaN             NaN           NaN             NaN                 NaN               NaN                     NaN             NaN          NaN                  NaN                                        NaN                            NaN                          N                    NaN                       NaN               NaN             NaN               NaN                                                                  NaN                              "
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 17
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Z2p4xZKqZife",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "d1faa0b0-6af6-4628-8d2b-e9eb9505d8c6"
+      },
+      "source": [
+        "df = pd.read_csv('LoanStats_2018Q4.csv', header=1, skipfooter=2, engine='python')\n",
+        "df.head()"
+      ],
+      "execution_count": 18,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>id</th>\n",
+              "      <th>member_id</th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>url</th>\n",
+              "      <th>desc</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>mths_since_last_record</th>\n",
+              "      <th>open_acc</th>\n",
+              "      <th>pub_rec</th>\n",
+              "      <th>revol_bal</th>\n",
+              "      <th>revol_util</th>\n",
+              "      <th>total_acc</th>\n",
+              "      <th>initial_list_status</th>\n",
+              "      <th>out_prncp</th>\n",
+              "      <th>out_prncp_inv</th>\n",
+              "      <th>total_pymnt</th>\n",
+              "      <th>total_pymnt_inv</th>\n",
+              "      <th>...</th>\n",
+              "      <th>percent_bc_gt_75</th>\n",
+              "      <th>pub_rec_bankruptcies</th>\n",
+              "      <th>tax_liens</th>\n",
+              "      <th>tot_hi_cred_lim</th>\n",
+              "      <th>total_bal_ex_mort</th>\n",
+              "      <th>total_bc_limit</th>\n",
+              "      <th>total_il_high_credit_limit</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>hardship_flag</th>\n",
+              "      <th>hardship_type</th>\n",
+              "      <th>hardship_reason</th>\n",
+              "      <th>hardship_status</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>hardship_amount</th>\n",
+              "      <th>hardship_start_date</th>\n",
+              "      <th>hardship_end_date</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>hardship_length</th>\n",
+              "      <th>hardship_dpd</th>\n",
+              "      <th>hardship_loan_status</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>hardship_payoff_balance_amount</th>\n",
+              "      <th>hardship_last_payment_amount</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>10.33%</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Jan-1996</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>14</td>\n",
+              "      <td>0</td>\n",
+              "      <td>9082</td>\n",
+              "      <td>38%</td>\n",
+              "      <td>23</td>\n",
+              "      <td>w</td>\n",
+              "      <td>8289.30</td>\n",
+              "      <td>8289.30</td>\n",
+              "      <td>2261.00</td>\n",
+              "      <td>2261.00</td>\n",
+              "      <td>...</td>\n",
+              "      <td>28.6</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>367828</td>\n",
+              "      <td>61364</td>\n",
+              "      <td>20900</td>\n",
+              "      <td>54912</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40%</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-2006</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>15</td>\n",
+              "      <td>0</td>\n",
+              "      <td>5199</td>\n",
+              "      <td>19.2%</td>\n",
+              "      <td>20</td>\n",
+              "      <td>w</td>\n",
+              "      <td>3423.38</td>\n",
+              "      <td>3423.38</td>\n",
+              "      <td>1081.96</td>\n",
+              "      <td>1081.96</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>98655</td>\n",
+              "      <td>66926</td>\n",
+              "      <td>21900</td>\n",
+              "      <td>71555</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>17.97%</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>Administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2011</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>8</td>\n",
+              "      <td>0</td>\n",
+              "      <td>4599</td>\n",
+              "      <td>19.1%</td>\n",
+              "      <td>13</td>\n",
+              "      <td>w</td>\n",
+              "      <td>4456.17</td>\n",
+              "      <td>4456.17</td>\n",
+              "      <td>895.96</td>\n",
+              "      <td>895.96</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>136927</td>\n",
+              "      <td>11749</td>\n",
+              "      <td>13800</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>20.89%</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>Operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Feb-1997</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>5</td>\n",
+              "      <td>0</td>\n",
+              "      <td>976</td>\n",
+              "      <td>13%</td>\n",
+              "      <td>10</td>\n",
+              "      <td>w</td>\n",
+              "      <td>21353.16</td>\n",
+              "      <td>21353.16</td>\n",
+              "      <td>4307.45</td>\n",
+              "      <td>4307.45</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>7500</td>\n",
+              "      <td>976</td>\n",
+              "      <td>3300</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40%</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jan-1995</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>107.0</td>\n",
+              "      <td>8</td>\n",
+              "      <td>1</td>\n",
+              "      <td>9019</td>\n",
+              "      <td>81.3%</td>\n",
+              "      <td>16</td>\n",
+              "      <td>w</td>\n",
+              "      <td>6846.83</td>\n",
+              "      <td>6846.83</td>\n",
+              "      <td>2163.85</td>\n",
+              "      <td>2163.85</td>\n",
+              "      <td>...</td>\n",
+              "      <td>100.0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>199744</td>\n",
+              "      <td>31078</td>\n",
+              "      <td>2300</td>\n",
+              "      <td>32206</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 144 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   id  member_id  ...  settlement_percentage  settlement_term\n",
+              "0 NaN        NaN  ...                    NaN              NaN\n",
+              "1 NaN        NaN  ...                    NaN              NaN\n",
+              "2 NaN        NaN  ...                    NaN              NaN\n",
+              "3 NaN        NaN  ...                    NaN              NaN\n",
+              "4 NaN        NaN  ...                    NaN              NaN\n",
+              "\n",
+              "[5 rows x 144 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 18
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "vlvHeYn6bD3z",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 355
+        },
+        "outputId": "06d73f7a-26da-4bec-dfe1-92b61b4a3273"
+      },
+      "source": [
+        "df.tail()"
+      ],
+      "execution_count": 19,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>id</th>\n",
+              "      <th>member_id</th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>url</th>\n",
+              "      <th>desc</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>mths_since_last_record</th>\n",
+              "      <th>open_acc</th>\n",
+              "      <th>pub_rec</th>\n",
+              "      <th>revol_bal</th>\n",
+              "      <th>revol_util</th>\n",
+              "      <th>total_acc</th>\n",
+              "      <th>initial_list_status</th>\n",
+              "      <th>out_prncp</th>\n",
+              "      <th>out_prncp_inv</th>\n",
+              "      <th>total_pymnt</th>\n",
+              "      <th>total_pymnt_inv</th>\n",
+              "      <th>...</th>\n",
+              "      <th>percent_bc_gt_75</th>\n",
+              "      <th>pub_rec_bankruptcies</th>\n",
+              "      <th>tax_liens</th>\n",
+              "      <th>tot_hi_cred_lim</th>\n",
+              "      <th>total_bal_ex_mort</th>\n",
+              "      <th>total_bc_limit</th>\n",
+              "      <th>total_il_high_credit_limit</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>hardship_flag</th>\n",
+              "      <th>hardship_type</th>\n",
+              "      <th>hardship_reason</th>\n",
+              "      <th>hardship_status</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>hardship_amount</th>\n",
+              "      <th>hardship_start_date</th>\n",
+              "      <th>hardship_end_date</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>hardship_length</th>\n",
+              "      <th>hardship_dpd</th>\n",
+              "      <th>hardship_loan_status</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>hardship_payoff_balance_amount</th>\n",
+              "      <th>hardship_last_payment_amount</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>128407</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>797.53</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>Tax Consultant</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>75000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Charged Off</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>352xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>20.95</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Aug-1985</td>\n",
+              "      <td>2</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>12</td>\n",
+              "      <td>0</td>\n",
+              "      <td>22465</td>\n",
+              "      <td>43.6%</td>\n",
+              "      <td>28</td>\n",
+              "      <td>w</td>\n",
+              "      <td>0.00</td>\n",
+              "      <td>0.00</td>\n",
+              "      <td>1547.08</td>\n",
+              "      <td>1547.08</td>\n",
+              "      <td>...</td>\n",
+              "      <td>14.3</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>296500</td>\n",
+              "      <td>40614</td>\n",
+              "      <td>47100</td>\n",
+              "      <td>21000</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128408</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>346.76</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>security guard</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>38000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>443xx</td>\n",
+              "      <td>OH</td>\n",
+              "      <td>13.16</td>\n",
+              "      <td>3</td>\n",
+              "      <td>Jul-1982</td>\n",
+              "      <td>0</td>\n",
+              "      <td>6.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>11</td>\n",
+              "      <td>0</td>\n",
+              "      <td>5634</td>\n",
+              "      <td>37.1%</td>\n",
+              "      <td>16</td>\n",
+              "      <td>w</td>\n",
+              "      <td>7655.00</td>\n",
+              "      <td>7655.00</td>\n",
+              "      <td>3459.26</td>\n",
+              "      <td>3459.26</td>\n",
+              "      <td>...</td>\n",
+              "      <td>40.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>91403</td>\n",
+              "      <td>9323</td>\n",
+              "      <td>9100</td>\n",
+              "      <td>2000</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128409</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>13.56%</td>\n",
+              "      <td>169.83</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C1</td>\n",
+              "      <td>Payoff Clerk</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>35360.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>381xx</td>\n",
+              "      <td>TN</td>\n",
+              "      <td>11.30</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Jun-2006</td>\n",
+              "      <td>0</td>\n",
+              "      <td>21.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>9</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2597</td>\n",
+              "      <td>27.3%</td>\n",
+              "      <td>15</td>\n",
+              "      <td>f</td>\n",
+              "      <td>3807.30</td>\n",
+              "      <td>3807.30</td>\n",
+              "      <td>1694.53</td>\n",
+              "      <td>1694.53</td>\n",
+              "      <td>...</td>\n",
+              "      <td>50.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>93908</td>\n",
+              "      <td>4976</td>\n",
+              "      <td>3000</td>\n",
+              "      <td>6028</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128410</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>9750.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>11.06%</td>\n",
+              "      <td>327.68</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B3</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>44400.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>980xx</td>\n",
+              "      <td>WA</td>\n",
+              "      <td>11.78</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2008</td>\n",
+              "      <td>2</td>\n",
+              "      <td>40.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>15</td>\n",
+              "      <td>0</td>\n",
+              "      <td>6269</td>\n",
+              "      <td>13.1%</td>\n",
+              "      <td>25</td>\n",
+              "      <td>f</td>\n",
+              "      <td>7544.75</td>\n",
+              "      <td>7356.13</td>\n",
+              "      <td>3261.44</td>\n",
+              "      <td>3179.90</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>57871</td>\n",
+              "      <td>16440</td>\n",
+              "      <td>20500</td>\n",
+              "      <td>10171</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128411</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>16.91%</td>\n",
+              "      <td>356.08</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C5</td>\n",
+              "      <td>Key Accounts Manager</td>\n",
+              "      <td>2 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>80000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>other</td>\n",
+              "      <td>Other</td>\n",
+              "      <td>021xx</td>\n",
+              "      <td>MA</td>\n",
+              "      <td>17.72</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Sep-2006</td>\n",
+              "      <td>0</td>\n",
+              "      <td>14.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>17</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1942</td>\n",
+              "      <td>30.8%</td>\n",
+              "      <td>31</td>\n",
+              "      <td>w</td>\n",
+              "      <td>7706.67</td>\n",
+              "      <td>7706.67</td>\n",
+              "      <td>3551.41</td>\n",
+              "      <td>3551.41</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>73669</td>\n",
+              "      <td>59194</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>67369</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 144 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "        id  member_id  ...  settlement_percentage  settlement_term\n",
+              "128407 NaN        NaN  ...                    NaN              NaN\n",
+              "128408 NaN        NaN  ...                    NaN              NaN\n",
+              "128409 NaN        NaN  ...                    NaN              NaN\n",
+              "128410 NaN        NaN  ...                    NaN              NaN\n",
+              "128411 NaN        NaN  ...                    NaN              NaN\n",
+              "\n",
+              "[5 rows x 144 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 19
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "pLXf3em3bG5m",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "655c2d10-ebcc-42e7-9b9c-4fd509ebfd8e"
+      },
+      "source": [
+        "df.shape"
+      ],
+      "execution_count": 21,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(128412, 144)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 21
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "QjyQIKN1bNN-",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "pd.set_option('display.max_rows', 50)\n",
+        "pd.set_option('display.max_columns', 50)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "dphWD1kIbfkG",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "a3034afe-05ba-4ded-8c51-eaeef81798b6"
+      },
+      "source": [
+        "df.isnull().sum()"
+      ],
+      "execution_count": 23,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "id                                            128412\n",
+              "member_id                                     128412\n",
+              "loan_amnt                                          0\n",
+              "funded_amnt                                        0\n",
+              "funded_amnt_inv                                    0\n",
+              "term                                               0\n",
+              "int_rate                                           0\n",
+              "installment                                        0\n",
+              "grade                                              0\n",
+              "sub_grade                                          0\n",
+              "emp_title                                      20947\n",
+              "emp_length                                     11704\n",
+              "home_ownership                                     0\n",
+              "annual_inc                                         0\n",
+              "verification_status                                0\n",
+              "issue_d                                            0\n",
+              "loan_status                                        0\n",
+              "pymnt_plan                                         0\n",
+              "url                                           128412\n",
+              "desc                                          128412\n",
+              "purpose                                            0\n",
+              "title                                              0\n",
+              "zip_code                                           0\n",
+              "addr_state                                         0\n",
+              "dti                                              237\n",
+              "                                               ...  \n",
+              "sec_app_chargeoff_within_12_mths              111630\n",
+              "sec_app_collections_12_mths_ex_med            111630\n",
+              "sec_app_mths_since_last_major_derog           123258\n",
+              "hardship_flag                                      0\n",
+              "hardship_type                                 128385\n",
+              "hardship_reason                               128385\n",
+              "hardship_status                               128385\n",
+              "deferral_term                                 128385\n",
+              "hardship_amount                               128385\n",
+              "hardship_start_date                           128385\n",
+              "hardship_end_date                             128385\n",
+              "payment_plan_start_date                       128385\n",
+              "hardship_length                               128385\n",
+              "hardship_dpd                                  128385\n",
+              "hardship_loan_status                          128385\n",
+              "orig_projected_additional_accrued_interest    128386\n",
+              "hardship_payoff_balance_amount                128385\n",
+              "hardship_last_payment_amount                  128385\n",
+              "debt_settlement_flag                               0\n",
+              "debt_settlement_flag_date                     128301\n",
+              "settlement_status                             128301\n",
+              "settlement_date                               128301\n",
+              "settlement_amount                             128301\n",
+              "settlement_percentage                         128301\n",
+              "settlement_term                               128301\n",
+              "Length: 144, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 23
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "3TTvqGvgbimD",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "63474b13-af62-41f7-fbd3-f02edf7158c5"
+      },
+      "source": [
+        "df.isnull().sum().sort_values(ascending=False)"
+      ],
+      "execution_count": 24,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "id                                            128412\n",
+              "desc                                          128412\n",
+              "member_id                                     128412\n",
+              "url                                           128412\n",
+              "orig_projected_additional_accrued_interest    128386\n",
+              "hardship_type                                 128385\n",
+              "hardship_last_payment_amount                  128385\n",
+              "hardship_payoff_balance_amount                128385\n",
+              "hardship_reason                               128385\n",
+              "hardship_loan_status                          128385\n",
+              "hardship_dpd                                  128385\n",
+              "hardship_length                               128385\n",
+              "payment_plan_start_date                       128385\n",
+              "hardship_end_date                             128385\n",
+              "hardship_start_date                           128385\n",
+              "hardship_amount                               128385\n",
+              "deferral_term                                 128385\n",
+              "hardship_status                               128385\n",
+              "settlement_percentage                         128301\n",
+              "settlement_term                               128301\n",
+              "settlement_status                             128301\n",
+              "settlement_amount                             128301\n",
+              "settlement_date                               128301\n",
+              "debt_settlement_flag_date                     128301\n",
+              "sec_app_mths_since_last_major_derog           123258\n",
+              "                                               ...  \n",
+              "total_il_high_credit_limit                         0\n",
+              "mort_acc                                           0\n",
+              "mo_sin_rcnt_tl                                     0\n",
+              "mo_sin_rcnt_rev_tl_op                              0\n",
+              "mo_sin_old_rev_tl_op                               0\n",
+              "policy_code                                        0\n",
+              "application_type                                   0\n",
+              "acc_now_delinq                                     0\n",
+              "tot_coll_amt                                       0\n",
+              "tot_cur_bal                                        0\n",
+              "open_acc_6m                                        0\n",
+              "open_act_il                                        0\n",
+              "hardship_flag                                      0\n",
+              "open_il_24m                                        0\n",
+              "total_bal_il                                       0\n",
+              "open_rv_12m                                        0\n",
+              "open_rv_24m                                        0\n",
+              "max_bal_bc                                         0\n",
+              "total_rev_hi_lim                                   0\n",
+              "total_cu_tl                                        0\n",
+              "inq_last_12m                                       0\n",
+              "acc_open_past_24mths                               0\n",
+              "chargeoff_within_12_mths                           0\n",
+              "delinq_amnt                                        0\n",
+              "inq_fi                                             0\n",
+              "Length: 144, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 24
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "G-GCgnEtib8E",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Work With Strings"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "rJ1H2XOLbr2z",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "b680ade8-61a4-4577-d5db-416efe4e03f9"
+      },
+      "source": [
+        "df.drop(columns=['id', 'member_id', 'desc', 'url'])"
+      ],
+      "execution_count": 25,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>hardship_flag</th>\n",
+              "      <th>hardship_type</th>\n",
+              "      <th>hardship_reason</th>\n",
+              "      <th>hardship_status</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>hardship_amount</th>\n",
+              "      <th>hardship_start_date</th>\n",
+              "      <th>hardship_end_date</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>hardship_length</th>\n",
+              "      <th>hardship_dpd</th>\n",
+              "      <th>hardship_loan_status</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>hardship_payoff_balance_amount</th>\n",
+              "      <th>hardship_last_payment_amount</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>10.33%</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Jan-1996</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40%</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-2006</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>17.97%</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>Administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2011</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>20.89%</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>Operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Feb-1997</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40%</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jan-1995</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>32075</td>\n",
+              "      <td>32075</td>\n",
+              "      <td>32075.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>11.80%</td>\n",
+              "      <td>710.26</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B4</td>\n",
+              "      <td>Nursing Supervisor</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>150000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>231xx</td>\n",
+              "      <td>VA</td>\n",
+              "      <td>22.21</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Aug-2005</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>9600</td>\n",
+              "      <td>9600</td>\n",
+              "      <td>9600.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>12.98%</td>\n",
+              "      <td>323.37</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B5</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>35704.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>home_improvement</td>\n",
+              "      <td>Home improvement</td>\n",
+              "      <td>401xx</td>\n",
+              "      <td>KY</td>\n",
+              "      <td>0.84</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Nov-2003</td>\n",
+              "      <td>0</td>\n",
+              "      <td>69.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7</th>\n",
+              "      <td>30000</td>\n",
+              "      <td>30000</td>\n",
+              "      <td>30000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>18.94%</td>\n",
+              "      <td>777.23</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D2</td>\n",
+              "      <td>Postmaster</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>713xx</td>\n",
+              "      <td>LA</td>\n",
+              "      <td>26.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jun-1987</td>\n",
+              "      <td>0</td>\n",
+              "      <td>71.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8</th>\n",
+              "      <td>2500</td>\n",
+              "      <td>2500</td>\n",
+              "      <td>2500.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>13.56%</td>\n",
+              "      <td>84.92</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C1</td>\n",
+              "      <td>Chef</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>55000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Fully Paid</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>109xx</td>\n",
+              "      <td>NY</td>\n",
+              "      <td>18.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2001</td>\n",
+              "      <td>1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>9</th>\n",
+              "      <td>12000</td>\n",
+              "      <td>12000</td>\n",
+              "      <td>12000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>13.56%</td>\n",
+              "      <td>276.49</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>40000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>180xx</td>\n",
+              "      <td>PA</td>\n",
+              "      <td>19.23</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Aug-2005</td>\n",
+              "      <td>2</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>19.92%</td>\n",
+              "      <td>264.50</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D3</td>\n",
+              "      <td>Material Handler</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>80000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>648xx</td>\n",
+              "      <td>MO</td>\n",
+              "      <td>20.67</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2005</td>\n",
+              "      <td>0</td>\n",
+              "      <td>37.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11</th>\n",
+              "      <td>16000</td>\n",
+              "      <td>16000</td>\n",
+              "      <td>16000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>17.97%</td>\n",
+              "      <td>406.04</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>Instructional Coordinator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>51000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>284xx</td>\n",
+              "      <td>NC</td>\n",
+              "      <td>21.91</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2005</td>\n",
+              "      <td>1</td>\n",
+              "      <td>52.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12</th>\n",
+              "      <td>16000</td>\n",
+              "      <td>16000</td>\n",
+              "      <td>16000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>26.31%</td>\n",
+              "      <td>481.99</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E4</td>\n",
+              "      <td>Financial Relationship Associate</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>33000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>290xx</td>\n",
+              "      <td>SC</td>\n",
+              "      <td>33.62</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-2010</td>\n",
+              "      <td>1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13</th>\n",
+              "      <td>15000</td>\n",
+              "      <td>15000</td>\n",
+              "      <td>14975.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>14.47%</td>\n",
+              "      <td>352.69</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C2</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>30000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>756xx</td>\n",
+              "      <td>TX</td>\n",
+              "      <td>41.60</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-1999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14</th>\n",
+              "      <td>13000</td>\n",
+              "      <td>13000</td>\n",
+              "      <td>13000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40%</td>\n",
+              "      <td>505.95</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Sale Representative</td>\n",
+              "      <td>2 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>other</td>\n",
+              "      <td>Other</td>\n",
+              "      <td>191xx</td>\n",
+              "      <td>PA</td>\n",
+              "      <td>39.73</td>\n",
+              "      <td>0</td>\n",
+              "      <td>May-2007</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>15</th>\n",
+              "      <td>9600</td>\n",
+              "      <td>9600</td>\n",
+              "      <td>9600.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40%</td>\n",
+              "      <td>373.62</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>driver coordinator</td>\n",
+              "      <td>9 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>65000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>265xx</td>\n",
+              "      <td>WV</td>\n",
+              "      <td>23.01</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Sep-2003</td>\n",
+              "      <td>0</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16</th>\n",
+              "      <td>3500</td>\n",
+              "      <td>3500</td>\n",
+              "      <td>3500.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>20.89%</td>\n",
+              "      <td>131.67</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>gas attendant</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>40000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>car</td>\n",
+              "      <td>Car financing</td>\n",
+              "      <td>078xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>9.09</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2004</td>\n",
+              "      <td>1</td>\n",
+              "      <td>24.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>46.0</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17</th>\n",
+              "      <td>25000</td>\n",
+              "      <td>25000</td>\n",
+              "      <td>25000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>16.91%</td>\n",
+              "      <td>620.11</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C5</td>\n",
+              "      <td>Processor</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>23878.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>453xx</td>\n",
+              "      <td>OH</td>\n",
+              "      <td>6.26</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2010</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18</th>\n",
+              "      <td>16000</td>\n",
+              "      <td>16000</td>\n",
+              "      <td>16000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>20.89%</td>\n",
+              "      <td>431.87</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>Neonatal Nurse Practitioner</td>\n",
+              "      <td>4 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>120000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>720xx</td>\n",
+              "      <td>AR</td>\n",
+              "      <td>27.57</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Jul-2005</td>\n",
+              "      <td>0</td>\n",
+              "      <td>8.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>19</th>\n",
+              "      <td>13000</td>\n",
+              "      <td>13000</td>\n",
+              "      <td>13000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>14.47%</td>\n",
+              "      <td>305.67</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C2</td>\n",
+              "      <td>Stationary Engineer</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>75000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Fully Paid</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>741xx</td>\n",
+              "      <td>OK</td>\n",
+              "      <td>26.16</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Feb-2001</td>\n",
+              "      <td>1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>13.56%</td>\n",
+              "      <td>339.65</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>65000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>937xx</td>\n",
+              "      <td>CA</td>\n",
+              "      <td>10.62</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Dec-2004</td>\n",
+              "      <td>1</td>\n",
+              "      <td>30.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>21</th>\n",
+              "      <td>13000</td>\n",
+              "      <td>13000</td>\n",
+              "      <td>13000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>14.47%</td>\n",
+              "      <td>447.29</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C2</td>\n",
+              "      <td>Exhibits director</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>55000.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>611xx</td>\n",
+              "      <td>IL</td>\n",
+              "      <td>10.58</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2001</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>22</th>\n",
+              "      <td>7000</td>\n",
+              "      <td>7000</td>\n",
+              "      <td>7000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>12.98%</td>\n",
+              "      <td>235.80</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B5</td>\n",
+              "      <td>Worship Director</td>\n",
+              "      <td>4 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>102500.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>house</td>\n",
+              "      <td>Home buying</td>\n",
+              "      <td>436xx</td>\n",
+              "      <td>OH</td>\n",
+              "      <td>15.20</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Dec-2002</td>\n",
+              "      <td>0</td>\n",
+              "      <td>38.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>23</th>\n",
+              "      <td>3300</td>\n",
+              "      <td>3300</td>\n",
+              "      <td>3300.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40%</td>\n",
+              "      <td>128.44</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Program Manager</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>49700.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>vacation</td>\n",
+              "      <td>Vacation</td>\n",
+              "      <td>310xx</td>\n",
+              "      <td>GA</td>\n",
+              "      <td>14.32</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Nov-2006</td>\n",
+              "      <td>1</td>\n",
+              "      <td>43.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>24</th>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>11.80%</td>\n",
+              "      <td>442.88</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B4</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>47590.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>156xx</td>\n",
+              "      <td>PA</td>\n",
+              "      <td>9.53</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-1999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>62.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128387</th>\n",
+              "      <td>6000</td>\n",
+              "      <td>6000</td>\n",
+              "      <td>6000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>11.55%</td>\n",
+              "      <td>198.00</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B4</td>\n",
+              "      <td>ENGINEER</td>\n",
+              "      <td>2 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>076xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>1.64</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-2010</td>\n",
+              "      <td>1</td>\n",
+              "      <td>53.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128388</th>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>8.46%</td>\n",
+              "      <td>630.99</td>\n",
+              "      <td>A</td>\n",
+              "      <td>A5</td>\n",
+              "      <td>Welder/Blacksmith</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>97000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>604xx</td>\n",
+              "      <td>IL</td>\n",
+              "      <td>15.59</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jul-1999</td>\n",
+              "      <td>1</td>\n",
+              "      <td>64.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128389</th>\n",
+              "      <td>6000</td>\n",
+              "      <td>6000</td>\n",
+              "      <td>5750.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>11.55%</td>\n",
+              "      <td>198.00</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B4</td>\n",
+              "      <td>RN Supervisor</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>70000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Charged Off</td>\n",
+              "      <td>n</td>\n",
+              "      <td>medical</td>\n",
+              "      <td>Medical expenses</td>\n",
+              "      <td>912xx</td>\n",
+              "      <td>CA</td>\n",
+              "      <td>11.52</td>\n",
+              "      <td>4</td>\n",
+              "      <td>Dec-1993</td>\n",
+              "      <td>0</td>\n",
+              "      <td>17.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128390</th>\n",
+              "      <td>24000</td>\n",
+              "      <td>24000</td>\n",
+              "      <td>24000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>19.92%</td>\n",
+              "      <td>890.95</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D3</td>\n",
+              "      <td>Corrections officer</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>34000.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>344xx</td>\n",
+              "      <td>FL</td>\n",
+              "      <td>74.09</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jun-2006</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>75.0</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128391</th>\n",
+              "      <td>35000</td>\n",
+              "      <td>35000</td>\n",
+              "      <td>34975.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>6.67%</td>\n",
+              "      <td>1075.43</td>\n",
+              "      <td>A</td>\n",
+              "      <td>A2</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>85000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Fully Paid</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>301xx</td>\n",
+              "      <td>GA</td>\n",
+              "      <td>22.15</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-1997</td>\n",
+              "      <td>2</td>\n",
+              "      <td>54.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128392</th>\n",
+              "      <td>6500</td>\n",
+              "      <td>6500</td>\n",
+              "      <td>6500.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>26.31%</td>\n",
+              "      <td>262.97</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E4</td>\n",
+              "      <td>Merchandise Team Captain</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>35000.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>home_improvement</td>\n",
+              "      <td>Home improvement</td>\n",
+              "      <td>328xx</td>\n",
+              "      <td>FL</td>\n",
+              "      <td>39.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Mar-2004</td>\n",
+              "      <td>0</td>\n",
+              "      <td>70.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128393</th>\n",
+              "      <td>6500</td>\n",
+              "      <td>6500</td>\n",
+              "      <td>6500.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>16.91%</td>\n",
+              "      <td>231.46</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C5</td>\n",
+              "      <td>Senior Accountant, Fixed Assets Acctg</td>\n",
+              "      <td>7 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>74160.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>600xx</td>\n",
+              "      <td>IL</td>\n",
+              "      <td>27.79</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jun-2006</td>\n",
+              "      <td>0</td>\n",
+              "      <td>38.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>58.0</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128394</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>6.11%</td>\n",
+              "      <td>152.36</td>\n",
+              "      <td>A</td>\n",
+              "      <td>A1</td>\n",
+              "      <td>Implementation Manager</td>\n",
+              "      <td>9 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>82000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>other</td>\n",
+              "      <td>Other</td>\n",
+              "      <td>750xx</td>\n",
+              "      <td>TX</td>\n",
+              "      <td>1.35</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Feb-2005</td>\n",
+              "      <td>0</td>\n",
+              "      <td>33.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>13.0</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128395</th>\n",
+              "      <td>22000</td>\n",
+              "      <td>22000</td>\n",
+              "      <td>22000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>11.55%</td>\n",
+              "      <td>726.00</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B4</td>\n",
+              "      <td>Sr. application analyst</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>72000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>481xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>46.98</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jun-1999</td>\n",
+              "      <td>0</td>\n",
+              "      <td>26.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128396</th>\n",
+              "      <td>24000</td>\n",
+              "      <td>24000</td>\n",
+              "      <td>24000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>571.22</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>Instructional Technology Specialist</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>60000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>750xx</td>\n",
+              "      <td>TX</td>\n",
+              "      <td>9.72</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-1999</td>\n",
+              "      <td>1</td>\n",
+              "      <td>43.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128397</th>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>476.01</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>Technical Supvervisor</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>75000.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Fully Paid</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>786xx</td>\n",
+              "      <td>TX</td>\n",
+              "      <td>24.82</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-1991</td>\n",
+              "      <td>2</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128398</th>\n",
+              "      <td>12000</td>\n",
+              "      <td>12000</td>\n",
+              "      <td>12000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>18.94%</td>\n",
+              "      <td>310.90</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D2</td>\n",
+              "      <td>Senior Business Account Executive</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>128000.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>937xx</td>\n",
+              "      <td>CA</td>\n",
+              "      <td>13.32</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Nov-2007</td>\n",
+              "      <td>1</td>\n",
+              "      <td>46.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128399</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>173.38</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>Tech</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>35000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>324xx</td>\n",
+              "      <td>FL</td>\n",
+              "      <td>31.76</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Jun-2003</td>\n",
+              "      <td>0</td>\n",
+              "      <td>15.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128400</th>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>476.01</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>production supervisor</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>80000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>117xx</td>\n",
+              "      <td>NY</td>\n",
+              "      <td>16.94</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2005</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128401</th>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000</td>\n",
+              "      <td>20000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>11.55%</td>\n",
+              "      <td>660.00</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B4</td>\n",
+              "      <td>secondary opps/lead coater</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>45000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>home_improvement</td>\n",
+              "      <td>Home improvement</td>\n",
+              "      <td>015xx</td>\n",
+              "      <td>MA</td>\n",
+              "      <td>22.13</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Dec-2003</td>\n",
+              "      <td>0</td>\n",
+              "      <td>41.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128402</th>\n",
+              "      <td>17500</td>\n",
+              "      <td>17500</td>\n",
+              "      <td>17500.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>22.35%</td>\n",
+              "      <td>486.82</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D5</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>25000.0</td>\n",
+              "      <td>Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>640xx</td>\n",
+              "      <td>MO</td>\n",
+              "      <td>27.75</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2001</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128403</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>16.14%</td>\n",
+              "      <td>176.14</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C4</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>9200.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>365xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>23.50</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2015</td>\n",
+              "      <td>1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128404</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>16.14%</td>\n",
+              "      <td>176.14</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C4</td>\n",
+              "      <td>Oncology Medical Assistant</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>46400.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Fully Paid</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>338xx</td>\n",
+              "      <td>FL</td>\n",
+              "      <td>16.85</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Nov-2003</td>\n",
+              "      <td>0</td>\n",
+              "      <td>29.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128405</th>\n",
+              "      <td>22000</td>\n",
+              "      <td>22000</td>\n",
+              "      <td>22000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>7.84%</td>\n",
+              "      <td>444.40</td>\n",
+              "      <td>A</td>\n",
+              "      <td>A4</td>\n",
+              "      <td>Owner</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>55000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>other</td>\n",
+              "      <td>Other</td>\n",
+              "      <td>982xx</td>\n",
+              "      <td>WA</td>\n",
+              "      <td>2.18</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-1987</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128406</th>\n",
+              "      <td>5600</td>\n",
+              "      <td>5600</td>\n",
+              "      <td>5600.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>13.56%</td>\n",
+              "      <td>190.21</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>15600.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>836xx</td>\n",
+              "      <td>ID</td>\n",
+              "      <td>15.31</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Aug-2012</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128407</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>797.53</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>Tax Consultant</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>75000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Charged Off</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>352xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>20.95</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Aug-1985</td>\n",
+              "      <td>2</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128408</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>15.02%</td>\n",
+              "      <td>346.76</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C3</td>\n",
+              "      <td>security guard</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>38000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>443xx</td>\n",
+              "      <td>OH</td>\n",
+              "      <td>13.16</td>\n",
+              "      <td>3</td>\n",
+              "      <td>Jul-1982</td>\n",
+              "      <td>0</td>\n",
+              "      <td>6.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128409</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>13.56%</td>\n",
+              "      <td>169.83</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C1</td>\n",
+              "      <td>Payoff Clerk</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>35360.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>381xx</td>\n",
+              "      <td>TN</td>\n",
+              "      <td>11.30</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Jun-2006</td>\n",
+              "      <td>0</td>\n",
+              "      <td>21.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128410</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>9750.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>11.06%</td>\n",
+              "      <td>327.68</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B3</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>44400.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>credit_card</td>\n",
+              "      <td>Credit card refinancing</td>\n",
+              "      <td>980xx</td>\n",
+              "      <td>WA</td>\n",
+              "      <td>11.78</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Oct-2008</td>\n",
+              "      <td>2</td>\n",
+              "      <td>40.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>128411</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>16.91%</td>\n",
+              "      <td>356.08</td>\n",
+              "      <td>C</td>\n",
+              "      <td>C5</td>\n",
+              "      <td>Key Accounts Manager</td>\n",
+              "      <td>2 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>80000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>other</td>\n",
+              "      <td>Other</td>\n",
+              "      <td>021xx</td>\n",
+              "      <td>MA</td>\n",
+              "      <td>17.72</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Sep-2006</td>\n",
+              "      <td>0</td>\n",
+              "      <td>14.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>128412 rows × 140 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "        loan_amnt  funded_amnt  funded_amnt_inv        term int_rate  \\\n",
+              "0           10000        10000          10000.0   36 months   10.33%   \n",
+              "1            4000         4000           4000.0   36 months   23.40%   \n",
+              "2            5000         5000           5000.0   36 months   17.97%   \n",
+              "3           23000        23000          23000.0   60 months   20.89%   \n",
+              "4            8000         8000           8000.0   36 months   23.40%   \n",
+              "5           32075        32075          32075.0   60 months   11.80%   \n",
+              "6            9600         9600           9600.0   36 months   12.98%   \n",
+              "7           30000        30000          30000.0   60 months   18.94%   \n",
+              "8            2500         2500           2500.0   36 months   13.56%   \n",
+              "9           12000        12000          12000.0   60 months   13.56%   \n",
+              "10          10000        10000          10000.0   60 months   19.92%   \n",
+              "11          16000        16000          16000.0   60 months   17.97%   \n",
+              "12          16000        16000          16000.0   60 months   26.31%   \n",
+              "13          15000        15000          14975.0   60 months   14.47%   \n",
+              "14          13000        13000          13000.0   36 months   23.40%   \n",
+              "15           9600         9600           9600.0   36 months   23.40%   \n",
+              "16           3500         3500           3500.0   36 months   20.89%   \n",
+              "17          25000        25000          25000.0   60 months   16.91%   \n",
+              "18          16000        16000          16000.0   60 months   20.89%   \n",
+              "19          13000        13000          13000.0   60 months   14.47%   \n",
+              "20          10000        10000          10000.0   36 months   13.56%   \n",
+              "21          13000        13000          13000.0   36 months   14.47%   \n",
+              "22           7000         7000           7000.0   36 months   12.98%   \n",
+              "23           3300         3300           3300.0   36 months   23.40%   \n",
+              "24          20000        20000          20000.0   60 months   11.80%   \n",
+              "...           ...          ...              ...         ...      ...   \n",
+              "128387       6000         6000           6000.0   36 months   11.55%   \n",
+              "128388      20000        20000          20000.0   36 months    8.46%   \n",
+              "128389       6000         6000           5750.0   36 months   11.55%   \n",
+              "128390      24000        24000          24000.0   36 months   19.92%   \n",
+              "128391      35000        35000          34975.0   36 months    6.67%   \n",
+              "128392       6500         6500           6500.0   36 months   26.31%   \n",
+              "128393       6500         6500           6500.0   36 months   16.91%   \n",
+              "128394       5000         5000           5000.0   36 months    6.11%   \n",
+              "128395      22000        22000          22000.0   36 months   11.55%   \n",
+              "128396      24000        24000          24000.0   60 months   15.02%   \n",
+              "128397      20000        20000          20000.0   60 months   15.02%   \n",
+              "128398      12000        12000          12000.0   60 months   18.94%   \n",
+              "128399       5000         5000           5000.0   36 months   15.02%   \n",
+              "128400      20000        20000          20000.0   60 months   15.02%   \n",
+              "128401      20000        20000          20000.0   36 months   11.55%   \n",
+              "128402      17500        17500          17500.0   60 months   22.35%   \n",
+              "128403       5000         5000           5000.0   36 months   16.14%   \n",
+              "128404       5000         5000           5000.0   36 months   16.14%   \n",
+              "128405      22000        22000          22000.0   60 months    7.84%   \n",
+              "128406       5600         5600           5600.0   36 months   13.56%   \n",
+              "128407      23000        23000          23000.0   36 months   15.02%   \n",
+              "128408      10000        10000          10000.0   36 months   15.02%   \n",
+              "128409       5000         5000           5000.0   36 months   13.56%   \n",
+              "128410      10000        10000           9750.0   36 months   11.06%   \n",
+              "128411      10000        10000          10000.0   36 months   16.91%   \n",
+              "\n",
+              "        installment grade sub_grade                              emp_title  \\\n",
+              "0            324.23     B        B1                                    NaN   \n",
+              "1            155.68     E        E1                               Security   \n",
+              "2            180.69     D        D1                         Administrative   \n",
+              "3            620.81     D        D4                               Operator   \n",
+              "4            311.35     E        E1                                Manager   \n",
+              "5            710.26     B        B4                     Nursing Supervisor   \n",
+              "6            323.37     B        B5                                    NaN   \n",
+              "7            777.23     D        D2                            Postmaster    \n",
+              "8             84.92     C        C1                                   Chef   \n",
+              "9            276.49     C        C1                                    NaN   \n",
+              "10           264.50     D        D3                       Material Handler   \n",
+              "11           406.04     D        D1              Instructional Coordinator   \n",
+              "12           481.99     E        E4       Financial Relationship Associate   \n",
+              "13           352.69     C        C2                                    NaN   \n",
+              "14           505.95     E        E1                    Sale Representative   \n",
+              "15           373.62     E        E1                    driver coordinator    \n",
+              "16           131.67     D        D4                          gas attendant   \n",
+              "17           620.11     C        C5                             Processor    \n",
+              "18           431.87     D        D4            Neonatal Nurse Practitioner   \n",
+              "19           305.67     C        C2                    Stationary Engineer   \n",
+              "20           339.65     C        C1                                    NaN   \n",
+              "21           447.29     C        C2                      Exhibits director   \n",
+              "22           235.80     B        B5                       Worship Director   \n",
+              "23           128.44     E        E1                        Program Manager   \n",
+              "24           442.88     B        B4                                    NaN   \n",
+              "...             ...   ...       ...                                    ...   \n",
+              "128387       198.00     B        B4                               ENGINEER   \n",
+              "128388       630.99     A        A5                      Welder/Blacksmith   \n",
+              "128389       198.00     B        B4                          RN Supervisor   \n",
+              "128390       890.95     D        D3                    Corrections officer   \n",
+              "128391      1075.43     A        A2                                    NaN   \n",
+              "128392       262.97     E        E4               Merchandise Team Captain   \n",
+              "128393       231.46     C        C5  Senior Accountant, Fixed Assets Acctg   \n",
+              "128394       152.36     A        A1                Implementation Manager    \n",
+              "128395       726.00     B        B4                Sr. application analyst   \n",
+              "128396       571.22     C        C3    Instructional Technology Specialist   \n",
+              "128397       476.01     C        C3                  Technical Supvervisor   \n",
+              "128398       310.90     D        D2      Senior Business Account Executive   \n",
+              "128399       173.38     C        C3                                   Tech   \n",
+              "128400       476.01     C        C3                 production supervisor    \n",
+              "128401       660.00     B        B4             secondary opps/lead coater   \n",
+              "128402       486.82     D        D5                                    NaN   \n",
+              "128403       176.14     C        C4                                    NaN   \n",
+              "128404       176.14     C        C4             Oncology Medical Assistant   \n",
+              "128405       444.40     A        A4                                  Owner   \n",
+              "128406       190.21     C        C1                                    NaN   \n",
+              "128407       797.53     C        C3                         Tax Consultant   \n",
+              "128408       346.76     C        C3                         security guard   \n",
+              "128409       169.83     C        C1                           Payoff Clerk   \n",
+              "128410       327.68     B        B3                                    NaN   \n",
+              "128411       356.08     C        C5                   Key Accounts Manager   \n",
+              "\n",
+              "       emp_length home_ownership  annual_inc verification_status   issue_d  \\\n",
+              "0        < 1 year       MORTGAGE    280000.0        Not Verified  Dec-2018   \n",
+              "1         3 years           RENT     90000.0     Source Verified  Dec-2018   \n",
+              "2         6 years       MORTGAGE     59280.0     Source Verified  Dec-2018   \n",
+              "3         5 years           RENT     68107.0     Source Verified  Dec-2018   \n",
+              "4       10+ years            OWN     43000.0     Source Verified  Dec-2018   \n",
+              "5       10+ years       MORTGAGE    150000.0        Not Verified  Dec-2018   \n",
+              "6             NaN       MORTGAGE     35704.0        Not Verified  Dec-2018   \n",
+              "7       10+ years       MORTGAGE     90000.0     Source Verified  Dec-2018   \n",
+              "8       10+ years           RENT     55000.0        Not Verified  Dec-2018   \n",
+              "9        < 1 year       MORTGAGE     40000.0        Not Verified  Dec-2018   \n",
+              "10      10+ years       MORTGAGE     80000.0        Not Verified  Dec-2018   \n",
+              "11        5 years       MORTGAGE     51000.0        Not Verified  Dec-2018   \n",
+              "12       < 1 year           RENT     33000.0     Source Verified  Dec-2018   \n",
+              "13            NaN       MORTGAGE     30000.0     Source Verified  Dec-2018   \n",
+              "14        2 years       MORTGAGE     90000.0            Verified  Dec-2018   \n",
+              "15        9 years           RENT     65000.0        Not Verified  Dec-2018   \n",
+              "16      10+ years       MORTGAGE     40000.0     Source Verified  Dec-2018   \n",
+              "17      10+ years       MORTGAGE     23878.0        Not Verified  Dec-2018   \n",
+              "18        4 years       MORTGAGE    120000.0        Not Verified  Dec-2018   \n",
+              "19      10+ years       MORTGAGE     75000.0        Not Verified  Dec-2018   \n",
+              "20       < 1 year       MORTGAGE     65000.0        Not Verified  Dec-2018   \n",
+              "21      10+ years       MORTGAGE     55000.0            Verified  Dec-2018   \n",
+              "22        4 years       MORTGAGE    102500.0        Not Verified  Dec-2018   \n",
+              "23        3 years           RENT     49700.0     Source Verified  Dec-2018   \n",
+              "24            NaN       MORTGAGE     47590.0            Verified  Dec-2018   \n",
+              "...           ...            ...         ...                 ...       ...   \n",
+              "128387    2 years           RENT     90000.0        Not Verified  Oct-2018   \n",
+              "128388  10+ years       MORTGAGE     97000.0     Source Verified  Oct-2018   \n",
+              "128389    6 years           RENT     70000.0        Not Verified  Oct-2018   \n",
+              "128390  10+ years           RENT     34000.0            Verified  Oct-2018   \n",
+              "128391        NaN       MORTGAGE     85000.0     Source Verified  Oct-2018   \n",
+              "128392  10+ years       MORTGAGE     35000.0            Verified  Oct-2018   \n",
+              "128393    7 years           RENT     74160.0     Source Verified  Oct-2018   \n",
+              "128394    9 years       MORTGAGE     82000.0        Not Verified  Oct-2018   \n",
+              "128395  10+ years       MORTGAGE     72000.0     Source Verified  Oct-2018   \n",
+              "128396  10+ years       MORTGAGE     60000.0        Not Verified  Oct-2018   \n",
+              "128397  10+ years       MORTGAGE     75000.0            Verified  Oct-2018   \n",
+              "128398    6 years           RENT    128000.0            Verified  Oct-2018   \n",
+              "128399  10+ years       MORTGAGE     35000.0     Source Verified  Oct-2018   \n",
+              "128400  10+ years       MORTGAGE     80000.0        Not Verified  Oct-2018   \n",
+              "128401  10+ years            OWN     45000.0        Not Verified  Oct-2018   \n",
+              "128402        NaN           RENT     25000.0            Verified  Oct-2018   \n",
+              "128403        NaN            OWN      9200.0     Source Verified  Oct-2018   \n",
+              "128404    3 years       MORTGAGE     46400.0     Source Verified  Oct-2018   \n",
+              "128405  10+ years       MORTGAGE     55000.0        Not Verified  Oct-2018   \n",
+              "128406        NaN           RENT     15600.0        Not Verified  Oct-2018   \n",
+              "128407  10+ years       MORTGAGE     75000.0     Source Verified  Oct-2018   \n",
+              "128408    5 years       MORTGAGE     38000.0        Not Verified  Oct-2018   \n",
+              "128409  10+ years       MORTGAGE     35360.0        Not Verified  Oct-2018   \n",
+              "128410        NaN           RENT     44400.0     Source Verified  Oct-2018   \n",
+              "128411    2 years           RENT     80000.0        Not Verified  Oct-2018   \n",
+              "\n",
+              "               loan_status pymnt_plan             purpose  \\\n",
+              "0                  Current          n  debt_consolidation   \n",
+              "1                  Current          n  debt_consolidation   \n",
+              "2       Late (31-120 days)          n  debt_consolidation   \n",
+              "3                  Current          n  debt_consolidation   \n",
+              "4                  Current          n  debt_consolidation   \n",
+              "5                  Current          n         credit_card   \n",
+              "6                  Current          n    home_improvement   \n",
+              "7                  Current          n  debt_consolidation   \n",
+              "8               Fully Paid          n  debt_consolidation   \n",
+              "9                  Current          n  debt_consolidation   \n",
+              "10                 Current          n  debt_consolidation   \n",
+              "11                 Current          n  debt_consolidation   \n",
+              "12                 Current          n         credit_card   \n",
+              "13                 Current          n  debt_consolidation   \n",
+              "14                 Current          n               other   \n",
+              "15                 Current          n         credit_card   \n",
+              "16                 Current          n                 car   \n",
+              "17                 Current          n  debt_consolidation   \n",
+              "18                 Current          n         credit_card   \n",
+              "19              Fully Paid          n  debt_consolidation   \n",
+              "20                 Current          n         credit_card   \n",
+              "21                 Current          n         credit_card   \n",
+              "22                 Current          n               house   \n",
+              "23                 Current          n            vacation   \n",
+              "24                 Current          n         credit_card   \n",
+              "...                    ...        ...                 ...   \n",
+              "128387             Current          n         credit_card   \n",
+              "128388             Current          n  debt_consolidation   \n",
+              "128389         Charged Off          n             medical   \n",
+              "128390  Late (31-120 days)          n  debt_consolidation   \n",
+              "128391          Fully Paid          n  debt_consolidation   \n",
+              "128392             Current          n    home_improvement   \n",
+              "128393             Current          n  debt_consolidation   \n",
+              "128394             Current          n               other   \n",
+              "128395             Current          n  debt_consolidation   \n",
+              "128396             Current          n  debt_consolidation   \n",
+              "128397          Fully Paid          n         credit_card   \n",
+              "128398             Current          n  debt_consolidation   \n",
+              "128399             Current          n  debt_consolidation   \n",
+              "128400             Current          n  debt_consolidation   \n",
+              "128401             Current          n    home_improvement   \n",
+              "128402             Current          n  debt_consolidation   \n",
+              "128403             Current          n  debt_consolidation   \n",
+              "128404          Fully Paid          n  debt_consolidation   \n",
+              "128405             Current          n               other   \n",
+              "128406             Current          n         credit_card   \n",
+              "128407         Charged Off          n  debt_consolidation   \n",
+              "128408             Current          n  debt_consolidation   \n",
+              "128409             Current          n  debt_consolidation   \n",
+              "128410             Current          n         credit_card   \n",
+              "128411             Current          n               other   \n",
+              "\n",
+              "                          title zip_code addr_state    dti  delinq_2yrs  \\\n",
+              "0            Debt consolidation    974xx         OR   6.15            2   \n",
+              "1            Debt consolidation    070xx         NJ  26.33            0   \n",
+              "2            Debt consolidation    490xx         MI  10.51            0   \n",
+              "3            Debt consolidation    672xx         KS   0.52            0   \n",
+              "4            Debt consolidation    357xx         AL  33.24            0   \n",
+              "5       Credit card refinancing    231xx         VA  22.21            0   \n",
+              "6              Home improvement    401xx         KY   0.84            0   \n",
+              "7            Debt consolidation    713xx         LA  26.52            0   \n",
+              "8            Debt consolidation    109xx         NY  18.24            0   \n",
+              "9            Debt consolidation    180xx         PA  19.23            0   \n",
+              "10           Debt consolidation    648xx         MO  20.67            0   \n",
+              "11           Debt consolidation    284xx         NC  21.91            0   \n",
+              "12      Credit card refinancing    290xx         SC  33.62            0   \n",
+              "13           Debt consolidation    756xx         TX  41.60            0   \n",
+              "14                        Other    191xx         PA  39.73            0   \n",
+              "15      Credit card refinancing    265xx         WV  23.01            1   \n",
+              "16                Car financing    078xx         NJ   9.09            0   \n",
+              "17           Debt consolidation    453xx         OH   6.26            0   \n",
+              "18      Credit card refinancing    720xx         AR  27.57            1   \n",
+              "19           Debt consolidation    741xx         OK  26.16            0   \n",
+              "20      Credit card refinancing    937xx         CA  10.62            0   \n",
+              "21      Credit card refinancing    611xx         IL  10.58            0   \n",
+              "22                  Home buying    436xx         OH  15.20            0   \n",
+              "23                     Vacation    310xx         GA  14.32            0   \n",
+              "24      Credit card refinancing    156xx         PA   9.53            0   \n",
+              "...                         ...      ...        ...    ...          ...   \n",
+              "128387  Credit card refinancing    076xx         NJ   1.64            0   \n",
+              "128388       Debt consolidation    604xx         IL  15.59            0   \n",
+              "128389         Medical expenses    912xx         CA  11.52            4   \n",
+              "128390       Debt consolidation    344xx         FL  74.09            0   \n",
+              "128391       Debt consolidation    301xx         GA  22.15            0   \n",
+              "128392         Home improvement    328xx         FL  39.51            0   \n",
+              "128393       Debt consolidation    600xx         IL  27.79            0   \n",
+              "128394                    Other    750xx         TX   1.35            0   \n",
+              "128395       Debt consolidation    481xx         MI  46.98            0   \n",
+              "128396       Debt consolidation    750xx         TX   9.72            0   \n",
+              "128397  Credit card refinancing    786xx         TX  24.82            0   \n",
+              "128398       Debt consolidation    937xx         CA  13.32            0   \n",
+              "128399       Debt consolidation    324xx         FL  31.76            2   \n",
+              "128400       Debt consolidation    117xx         NY  16.94            0   \n",
+              "128401         Home improvement    015xx         MA  22.13            0   \n",
+              "128402       Debt consolidation    640xx         MO  27.75            0   \n",
+              "128403       Debt consolidation    365xx         AL  23.50            0   \n",
+              "128404       Debt consolidation    338xx         FL  16.85            0   \n",
+              "128405                    Other    982xx         WA   2.18            0   \n",
+              "128406  Credit card refinancing    836xx         ID  15.31            0   \n",
+              "128407       Debt consolidation    352xx         AL  20.95            1   \n",
+              "128408       Debt consolidation    443xx         OH  13.16            3   \n",
+              "128409       Debt consolidation    381xx         TN  11.30            1   \n",
+              "128410  Credit card refinancing    980xx         WA  11.78            0   \n",
+              "128411                    Other    021xx         MA  17.72            1   \n",
+              "\n",
+              "       earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0              Jan-1996               0                    18.0  ...   \n",
+              "1              Sep-2006               4                    59.0  ...   \n",
+              "2              Apr-2011               0                     NaN  ...   \n",
+              "3              Feb-1997               0                     NaN  ...   \n",
+              "4              Jan-1995               0                     NaN  ...   \n",
+              "5              Aug-2005               0                     NaN  ...   \n",
+              "6              Nov-2003               0                    69.0  ...   \n",
+              "7              Jun-1987               0                    71.0  ...   \n",
+              "8              Apr-2001               1                     NaN  ...   \n",
+              "9              Aug-2005               2                     NaN  ...   \n",
+              "10             Apr-2005               0                    37.0  ...   \n",
+              "11             Oct-2005               1                    52.0  ...   \n",
+              "12             Sep-2010               1                     NaN  ...   \n",
+              "13             Oct-1999               0                     NaN  ...   \n",
+              "14             May-2007               0                     NaN  ...   \n",
+              "15             Sep-2003               0                    16.0  ...   \n",
+              "16             Oct-2004               1                    24.0  ...   \n",
+              "17             Oct-2010               0                     NaN  ...   \n",
+              "18             Jul-2005               0                     8.0  ...   \n",
+              "19             Feb-2001               1                     NaN  ...   \n",
+              "20             Dec-2004               1                    30.0  ...   \n",
+              "21             Oct-2001               0                     NaN  ...   \n",
+              "22             Dec-2002               0                    38.0  ...   \n",
+              "23             Nov-2006               1                    43.0  ...   \n",
+              "24             Sep-1999               0                    62.0  ...   \n",
+              "...                 ...             ...                     ...  ...   \n",
+              "128387         Sep-2010               1                    53.0  ...   \n",
+              "128388         Jul-1999               1                    64.0  ...   \n",
+              "128389         Dec-1993               0                    17.0  ...   \n",
+              "128390         Jun-2006               0                     NaN  ...   \n",
+              "128391         Apr-1997               2                    54.0  ...   \n",
+              "128392         Mar-2004               0                    70.0  ...   \n",
+              "128393         Jun-2006               0                    38.0  ...   \n",
+              "128394         Feb-2005               0                    33.0  ...   \n",
+              "128395         Jun-1999               0                    26.0  ...   \n",
+              "128396         Apr-1999               1                    43.0  ...   \n",
+              "128397         Apr-1991               2                     NaN  ...   \n",
+              "128398         Nov-2007               1                    46.0  ...   \n",
+              "128399         Jun-2003               0                    15.0  ...   \n",
+              "128400         Oct-2005               0                     NaN  ...   \n",
+              "128401         Dec-2003               0                    41.0  ...   \n",
+              "128402         Oct-2001               0                     NaN  ...   \n",
+              "128403         Apr-2015               1                     NaN  ...   \n",
+              "128404         Nov-2003               0                    29.0  ...   \n",
+              "128405         Apr-1987               0                     NaN  ...   \n",
+              "128406         Aug-2012               0                     NaN  ...   \n",
+              "128407         Aug-1985               2                    22.0  ...   \n",
+              "128408         Jul-1982               0                     6.0  ...   \n",
+              "128409         Jun-2006               0                    21.0  ...   \n",
+              "128410         Oct-2008               2                    40.0  ...   \n",
+              "128411         Sep-2006               0                    14.0  ...   \n",
+              "\n",
+              "        sec_app_chargeoff_within_12_mths  sec_app_collections_12_mths_ex_med  \\\n",
+              "0                                    NaN                                 NaN   \n",
+              "1                                    NaN                                 NaN   \n",
+              "2                                    NaN                                 NaN   \n",
+              "3                                    NaN                                 NaN   \n",
+              "4                                    NaN                                 NaN   \n",
+              "5                                    NaN                                 NaN   \n",
+              "6                                    NaN                                 NaN   \n",
+              "7                                    NaN                                 NaN   \n",
+              "8                                    NaN                                 NaN   \n",
+              "9                                    NaN                                 NaN   \n",
+              "10                                   NaN                                 NaN   \n",
+              "11                                   NaN                                 NaN   \n",
+              "12                                   NaN                                 NaN   \n",
+              "13                                   0.0                                 0.0   \n",
+              "14                                   NaN                                 NaN   \n",
+              "15                                   NaN                                 NaN   \n",
+              "16                                   0.0                                 0.0   \n",
+              "17                                   0.0                                 0.0   \n",
+              "18                                   NaN                                 NaN   \n",
+              "19                                   NaN                                 NaN   \n",
+              "20                                   NaN                                 NaN   \n",
+              "21                                   NaN                                 NaN   \n",
+              "22                                   NaN                                 NaN   \n",
+              "23                                   NaN                                 NaN   \n",
+              "24                                   0.0                                 0.0   \n",
+              "...                                  ...                                 ...   \n",
+              "128387                               0.0                                 0.0   \n",
+              "128388                               NaN                                 NaN   \n",
+              "128389                               0.0                                 0.0   \n",
+              "128390                               0.0                                 1.0   \n",
+              "128391                               0.0                                 0.0   \n",
+              "128392                               NaN                                 NaN   \n",
+              "128393                               0.0                                 0.0   \n",
+              "128394                               0.0                                 0.0   \n",
+              "128395                               0.0                                 0.0   \n",
+              "128396                               NaN                                 NaN   \n",
+              "128397                               NaN                                 NaN   \n",
+              "128398                               NaN                                 NaN   \n",
+              "128399                               NaN                                 NaN   \n",
+              "128400                               0.0                                 0.0   \n",
+              "128401                               NaN                                 NaN   \n",
+              "128402                               NaN                                 NaN   \n",
+              "128403                               NaN                                 NaN   \n",
+              "128404                               NaN                                 NaN   \n",
+              "128405                               NaN                                 NaN   \n",
+              "128406                               NaN                                 NaN   \n",
+              "128407                               NaN                                 NaN   \n",
+              "128408                               NaN                                 NaN   \n",
+              "128409                               NaN                                 NaN   \n",
+              "128410                               NaN                                 NaN   \n",
+              "128411                               NaN                                 NaN   \n",
+              "\n",
+              "        sec_app_mths_since_last_major_derog  hardship_flag hardship_type  \\\n",
+              "0                                       NaN              N           NaN   \n",
+              "1                                       NaN              N           NaN   \n",
+              "2                                       NaN              N           NaN   \n",
+              "3                                       NaN              N           NaN   \n",
+              "4                                       NaN              N           NaN   \n",
+              "5                                       NaN              N           NaN   \n",
+              "6                                       NaN              N           NaN   \n",
+              "7                                       NaN              N           NaN   \n",
+              "8                                       NaN              N           NaN   \n",
+              "9                                       NaN              N           NaN   \n",
+              "10                                      NaN              N           NaN   \n",
+              "11                                      NaN              N           NaN   \n",
+              "12                                      NaN              N           NaN   \n",
+              "13                                      NaN              N           NaN   \n",
+              "14                                      NaN              N           NaN   \n",
+              "15                                      NaN              N           NaN   \n",
+              "16                                     46.0              N           NaN   \n",
+              "17                                      NaN              N           NaN   \n",
+              "18                                      NaN              N           NaN   \n",
+              "19                                      NaN              N           NaN   \n",
+              "20                                      NaN              N           NaN   \n",
+              "21                                      NaN              N           NaN   \n",
+              "22                                      NaN              N           NaN   \n",
+              "23                                      NaN              N           NaN   \n",
+              "24                                      NaN              N           NaN   \n",
+              "...                                     ...            ...           ...   \n",
+              "128387                                  NaN              N           NaN   \n",
+              "128388                                  NaN              N           NaN   \n",
+              "128389                                  NaN              N           NaN   \n",
+              "128390                                 75.0              N           NaN   \n",
+              "128391                                  NaN              N           NaN   \n",
+              "128392                                  NaN              N           NaN   \n",
+              "128393                                 58.0              N           NaN   \n",
+              "128394                                 13.0              N           NaN   \n",
+              "128395                                  NaN              N           NaN   \n",
+              "128396                                  NaN              N           NaN   \n",
+              "128397                                  NaN              N           NaN   \n",
+              "128398                                  NaN              N           NaN   \n",
+              "128399                                  NaN              N           NaN   \n",
+              "128400                                  NaN              N           NaN   \n",
+              "128401                                  NaN              N           NaN   \n",
+              "128402                                  NaN              N           NaN   \n",
+              "128403                                  NaN              N           NaN   \n",
+              "128404                                  NaN              N           NaN   \n",
+              "128405                                  NaN              N           NaN   \n",
+              "128406                                  NaN              N           NaN   \n",
+              "128407                                  NaN              N           NaN   \n",
+              "128408                                  NaN              N           NaN   \n",
+              "128409                                  NaN              N           NaN   \n",
+              "128410                                  NaN              N           NaN   \n",
+              "128411                                  NaN              N           NaN   \n",
+              "\n",
+              "        hardship_reason hardship_status  deferral_term  hardship_amount  \\\n",
+              "0                   NaN             NaN            NaN              NaN   \n",
+              "1                   NaN             NaN            NaN              NaN   \n",
+              "2                   NaN             NaN            NaN              NaN   \n",
+              "3                   NaN             NaN            NaN              NaN   \n",
+              "4                   NaN             NaN            NaN              NaN   \n",
+              "5                   NaN             NaN            NaN              NaN   \n",
+              "6                   NaN             NaN            NaN              NaN   \n",
+              "7                   NaN             NaN            NaN              NaN   \n",
+              "8                   NaN             NaN            NaN              NaN   \n",
+              "9                   NaN             NaN            NaN              NaN   \n",
+              "10                  NaN             NaN            NaN              NaN   \n",
+              "11                  NaN             NaN            NaN              NaN   \n",
+              "12                  NaN             NaN            NaN              NaN   \n",
+              "13                  NaN             NaN            NaN              NaN   \n",
+              "14                  NaN             NaN            NaN              NaN   \n",
+              "15                  NaN             NaN            NaN              NaN   \n",
+              "16                  NaN             NaN            NaN              NaN   \n",
+              "17                  NaN             NaN            NaN              NaN   \n",
+              "18                  NaN             NaN            NaN              NaN   \n",
+              "19                  NaN             NaN            NaN              NaN   \n",
+              "20                  NaN             NaN            NaN              NaN   \n",
+              "21                  NaN             NaN            NaN              NaN   \n",
+              "22                  NaN             NaN            NaN              NaN   \n",
+              "23                  NaN             NaN            NaN              NaN   \n",
+              "24                  NaN             NaN            NaN              NaN   \n",
+              "...                 ...             ...            ...              ...   \n",
+              "128387              NaN             NaN            NaN              NaN   \n",
+              "128388              NaN             NaN            NaN              NaN   \n",
+              "128389              NaN             NaN            NaN              NaN   \n",
+              "128390              NaN             NaN            NaN              NaN   \n",
+              "128391              NaN             NaN            NaN              NaN   \n",
+              "128392              NaN             NaN            NaN              NaN   \n",
+              "128393              NaN             NaN            NaN              NaN   \n",
+              "128394              NaN             NaN            NaN              NaN   \n",
+              "128395              NaN             NaN            NaN              NaN   \n",
+              "128396              NaN             NaN            NaN              NaN   \n",
+              "128397              NaN             NaN            NaN              NaN   \n",
+              "128398              NaN             NaN            NaN              NaN   \n",
+              "128399              NaN             NaN            NaN              NaN   \n",
+              "128400              NaN             NaN            NaN              NaN   \n",
+              "128401              NaN             NaN            NaN              NaN   \n",
+              "128402              NaN             NaN            NaN              NaN   \n",
+              "128403              NaN             NaN            NaN              NaN   \n",
+              "128404              NaN             NaN            NaN              NaN   \n",
+              "128405              NaN             NaN            NaN              NaN   \n",
+              "128406              NaN             NaN            NaN              NaN   \n",
+              "128407              NaN             NaN            NaN              NaN   \n",
+              "128408              NaN             NaN            NaN              NaN   \n",
+              "128409              NaN             NaN            NaN              NaN   \n",
+              "128410              NaN             NaN            NaN              NaN   \n",
+              "128411              NaN             NaN            NaN              NaN   \n",
+              "\n",
+              "        hardship_start_date  hardship_end_date  payment_plan_start_date  \\\n",
+              "0                       NaN                NaN                      NaN   \n",
+              "1                       NaN                NaN                      NaN   \n",
+              "2                       NaN                NaN                      NaN   \n",
+              "3                       NaN                NaN                      NaN   \n",
+              "4                       NaN                NaN                      NaN   \n",
+              "5                       NaN                NaN                      NaN   \n",
+              "6                       NaN                NaN                      NaN   \n",
+              "7                       NaN                NaN                      NaN   \n",
+              "8                       NaN                NaN                      NaN   \n",
+              "9                       NaN                NaN                      NaN   \n",
+              "10                      NaN                NaN                      NaN   \n",
+              "11                      NaN                NaN                      NaN   \n",
+              "12                      NaN                NaN                      NaN   \n",
+              "13                      NaN                NaN                      NaN   \n",
+              "14                      NaN                NaN                      NaN   \n",
+              "15                      NaN                NaN                      NaN   \n",
+              "16                      NaN                NaN                      NaN   \n",
+              "17                      NaN                NaN                      NaN   \n",
+              "18                      NaN                NaN                      NaN   \n",
+              "19                      NaN                NaN                      NaN   \n",
+              "20                      NaN                NaN                      NaN   \n",
+              "21                      NaN                NaN                      NaN   \n",
+              "22                      NaN                NaN                      NaN   \n",
+              "23                      NaN                NaN                      NaN   \n",
+              "24                      NaN                NaN                      NaN   \n",
+              "...                     ...                ...                      ...   \n",
+              "128387                  NaN                NaN                      NaN   \n",
+              "128388                  NaN                NaN                      NaN   \n",
+              "128389                  NaN                NaN                      NaN   \n",
+              "128390                  NaN                NaN                      NaN   \n",
+              "128391                  NaN                NaN                      NaN   \n",
+              "128392                  NaN                NaN                      NaN   \n",
+              "128393                  NaN                NaN                      NaN   \n",
+              "128394                  NaN                NaN                      NaN   \n",
+              "128395                  NaN                NaN                      NaN   \n",
+              "128396                  NaN                NaN                      NaN   \n",
+              "128397                  NaN                NaN                      NaN   \n",
+              "128398                  NaN                NaN                      NaN   \n",
+              "128399                  NaN                NaN                      NaN   \n",
+              "128400                  NaN                NaN                      NaN   \n",
+              "128401                  NaN                NaN                      NaN   \n",
+              "128402                  NaN                NaN                      NaN   \n",
+              "128403                  NaN                NaN                      NaN   \n",
+              "128404                  NaN                NaN                      NaN   \n",
+              "128405                  NaN                NaN                      NaN   \n",
+              "128406                  NaN                NaN                      NaN   \n",
+              "128407                  NaN                NaN                      NaN   \n",
+              "128408                  NaN                NaN                      NaN   \n",
+              "128409                  NaN                NaN                      NaN   \n",
+              "128410                  NaN                NaN                      NaN   \n",
+              "128411                  NaN                NaN                      NaN   \n",
+              "\n",
+              "        hardship_length  hardship_dpd  hardship_loan_status  \\\n",
+              "0                   NaN           NaN                   NaN   \n",
+              "1                   NaN           NaN                   NaN   \n",
+              "2                   NaN           NaN                   NaN   \n",
+              "3                   NaN           NaN                   NaN   \n",
+              "4                   NaN           NaN                   NaN   \n",
+              "5                   NaN           NaN                   NaN   \n",
+              "6                   NaN           NaN                   NaN   \n",
+              "7                   NaN           NaN                   NaN   \n",
+              "8                   NaN           NaN                   NaN   \n",
+              "9                   NaN           NaN                   NaN   \n",
+              "10                  NaN           NaN                   NaN   \n",
+              "11                  NaN           NaN                   NaN   \n",
+              "12                  NaN           NaN                   NaN   \n",
+              "13                  NaN           NaN                   NaN   \n",
+              "14                  NaN           NaN                   NaN   \n",
+              "15                  NaN           NaN                   NaN   \n",
+              "16                  NaN           NaN                   NaN   \n",
+              "17                  NaN           NaN                   NaN   \n",
+              "18                  NaN           NaN                   NaN   \n",
+              "19                  NaN           NaN                   NaN   \n",
+              "20                  NaN           NaN                   NaN   \n",
+              "21                  NaN           NaN                   NaN   \n",
+              "22                  NaN           NaN                   NaN   \n",
+              "23                  NaN           NaN                   NaN   \n",
+              "24                  NaN           NaN                   NaN   \n",
+              "...                 ...           ...                   ...   \n",
+              "128387              NaN           NaN                   NaN   \n",
+              "128388              NaN           NaN                   NaN   \n",
+              "128389              NaN           NaN                   NaN   \n",
+              "128390              NaN           NaN                   NaN   \n",
+              "128391              NaN           NaN                   NaN   \n",
+              "128392              NaN           NaN                   NaN   \n",
+              "128393              NaN           NaN                   NaN   \n",
+              "128394              NaN           NaN                   NaN   \n",
+              "128395              NaN           NaN                   NaN   \n",
+              "128396              NaN           NaN                   NaN   \n",
+              "128397              NaN           NaN                   NaN   \n",
+              "128398              NaN           NaN                   NaN   \n",
+              "128399              NaN           NaN                   NaN   \n",
+              "128400              NaN           NaN                   NaN   \n",
+              "128401              NaN           NaN                   NaN   \n",
+              "128402              NaN           NaN                   NaN   \n",
+              "128403              NaN           NaN                   NaN   \n",
+              "128404              NaN           NaN                   NaN   \n",
+              "128405              NaN           NaN                   NaN   \n",
+              "128406              NaN           NaN                   NaN   \n",
+              "128407              NaN           NaN                   NaN   \n",
+              "128408              NaN           NaN                   NaN   \n",
+              "128409              NaN           NaN                   NaN   \n",
+              "128410              NaN           NaN                   NaN   \n",
+              "128411              NaN           NaN                   NaN   \n",
+              "\n",
+              "        orig_projected_additional_accrued_interest  \\\n",
+              "0                                              NaN   \n",
+              "1                                              NaN   \n",
+              "2                                              NaN   \n",
+              "3                                              NaN   \n",
+              "4                                              NaN   \n",
+              "5                                              NaN   \n",
+              "6                                              NaN   \n",
+              "7                                              NaN   \n",
+              "8                                              NaN   \n",
+              "9                                              NaN   \n",
+              "10                                             NaN   \n",
+              "11                                             NaN   \n",
+              "12                                             NaN   \n",
+              "13                                             NaN   \n",
+              "14                                             NaN   \n",
+              "15                                             NaN   \n",
+              "16                                             NaN   \n",
+              "17                                             NaN   \n",
+              "18                                             NaN   \n",
+              "19                                             NaN   \n",
+              "20                                             NaN   \n",
+              "21                                             NaN   \n",
+              "22                                             NaN   \n",
+              "23                                             NaN   \n",
+              "24                                             NaN   \n",
+              "...                                            ...   \n",
+              "128387                                         NaN   \n",
+              "128388                                         NaN   \n",
+              "128389                                         NaN   \n",
+              "128390                                         NaN   \n",
+              "128391                                         NaN   \n",
+              "128392                                         NaN   \n",
+              "128393                                         NaN   \n",
+              "128394                                         NaN   \n",
+              "128395                                         NaN   \n",
+              "128396                                         NaN   \n",
+              "128397                                         NaN   \n",
+              "128398                                         NaN   \n",
+              "128399                                         NaN   \n",
+              "128400                                         NaN   \n",
+              "128401                                         NaN   \n",
+              "128402                                         NaN   \n",
+              "128403                                         NaN   \n",
+              "128404                                         NaN   \n",
+              "128405                                         NaN   \n",
+              "128406                                         NaN   \n",
+              "128407                                         NaN   \n",
+              "128408                                         NaN   \n",
+              "128409                                         NaN   \n",
+              "128410                                         NaN   \n",
+              "128411                                         NaN   \n",
+              "\n",
+              "       hardship_payoff_balance_amount  hardship_last_payment_amount  \\\n",
+              "0                                 NaN                           NaN   \n",
+              "1                                 NaN                           NaN   \n",
+              "2                                 NaN                           NaN   \n",
+              "3                                 NaN                           NaN   \n",
+              "4                                 NaN                           NaN   \n",
+              "5                                 NaN                           NaN   \n",
+              "6                                 NaN                           NaN   \n",
+              "7                                 NaN                           NaN   \n",
+              "8                                 NaN                           NaN   \n",
+              "9                                 NaN                           NaN   \n",
+              "10                                NaN                           NaN   \n",
+              "11                                NaN                           NaN   \n",
+              "12                                NaN                           NaN   \n",
+              "13                                NaN                           NaN   \n",
+              "14                                NaN                           NaN   \n",
+              "15                                NaN                           NaN   \n",
+              "16                                NaN                           NaN   \n",
+              "17                                NaN                           NaN   \n",
+              "18                                NaN                           NaN   \n",
+              "19                                NaN                           NaN   \n",
+              "20                                NaN                           NaN   \n",
+              "21                                NaN                           NaN   \n",
+              "22                                NaN                           NaN   \n",
+              "23                                NaN                           NaN   \n",
+              "24                                NaN                           NaN   \n",
+              "...                               ...                           ...   \n",
+              "128387                            NaN                           NaN   \n",
+              "128388                            NaN                           NaN   \n",
+              "128389                            NaN                           NaN   \n",
+              "128390                            NaN                           NaN   \n",
+              "128391                            NaN                           NaN   \n",
+              "128392                            NaN                           NaN   \n",
+              "128393                            NaN                           NaN   \n",
+              "128394                            NaN                           NaN   \n",
+              "128395                            NaN                           NaN   \n",
+              "128396                            NaN                           NaN   \n",
+              "128397                            NaN                           NaN   \n",
+              "128398                            NaN                           NaN   \n",
+              "128399                            NaN                           NaN   \n",
+              "128400                            NaN                           NaN   \n",
+              "128401                            NaN                           NaN   \n",
+              "128402                            NaN                           NaN   \n",
+              "128403                            NaN                           NaN   \n",
+              "128404                            NaN                           NaN   \n",
+              "128405                            NaN                           NaN   \n",
+              "128406                            NaN                           NaN   \n",
+              "128407                            NaN                           NaN   \n",
+              "128408                            NaN                           NaN   \n",
+              "128409                            NaN                           NaN   \n",
+              "128410                            NaN                           NaN   \n",
+              "128411                            NaN                           NaN   \n",
+              "\n",
+              "       debt_settlement_flag debt_settlement_flag_date  settlement_status  \\\n",
+              "0                         N                       NaN                NaN   \n",
+              "1                         N                       NaN                NaN   \n",
+              "2                         N                       NaN                NaN   \n",
+              "3                         N                       NaN                NaN   \n",
+              "4                         N                       NaN                NaN   \n",
+              "5                         N                       NaN                NaN   \n",
+              "6                         N                       NaN                NaN   \n",
+              "7                         N                       NaN                NaN   \n",
+              "8                         N                       NaN                NaN   \n",
+              "9                         N                       NaN                NaN   \n",
+              "10                        N                       NaN                NaN   \n",
+              "11                        N                       NaN                NaN   \n",
+              "12                        N                       NaN                NaN   \n",
+              "13                        N                       NaN                NaN   \n",
+              "14                        N                       NaN                NaN   \n",
+              "15                        N                       NaN                NaN   \n",
+              "16                        N                       NaN                NaN   \n",
+              "17                        N                       NaN                NaN   \n",
+              "18                        N                       NaN                NaN   \n",
+              "19                        N                       NaN                NaN   \n",
+              "20                        N                       NaN                NaN   \n",
+              "21                        N                       NaN                NaN   \n",
+              "22                        N                       NaN                NaN   \n",
+              "23                        N                       NaN                NaN   \n",
+              "24                        N                       NaN                NaN   \n",
+              "...                     ...                       ...                ...   \n",
+              "128387                    N                       NaN                NaN   \n",
+              "128388                    N                       NaN                NaN   \n",
+              "128389                    N                       NaN                NaN   \n",
+              "128390                    N                       NaN                NaN   \n",
+              "128391                    N                       NaN                NaN   \n",
+              "128392                    N                       NaN                NaN   \n",
+              "128393                    N                       NaN                NaN   \n",
+              "128394                    N                       NaN                NaN   \n",
+              "128395                    N                       NaN                NaN   \n",
+              "128396                    N                       NaN                NaN   \n",
+              "128397                    N                       NaN                NaN   \n",
+              "128398                    N                       NaN                NaN   \n",
+              "128399                    N                       NaN                NaN   \n",
+              "128400                    N                       NaN                NaN   \n",
+              "128401                    N                       NaN                NaN   \n",
+              "128402                    N                       NaN                NaN   \n",
+              "128403                    N                       NaN                NaN   \n",
+              "128404                    N                       NaN                NaN   \n",
+              "128405                    N                       NaN                NaN   \n",
+              "128406                    N                       NaN                NaN   \n",
+              "128407                    N                       NaN                NaN   \n",
+              "128408                    N                       NaN                NaN   \n",
+              "128409                    N                       NaN                NaN   \n",
+              "128410                    N                       NaN                NaN   \n",
+              "128411                    N                       NaN                NaN   \n",
+              "\n",
+              "        settlement_date  settlement_amount settlement_percentage  \\\n",
+              "0                   NaN                NaN                   NaN   \n",
+              "1                   NaN                NaN                   NaN   \n",
+              "2                   NaN                NaN                   NaN   \n",
+              "3                   NaN                NaN                   NaN   \n",
+              "4                   NaN                NaN                   NaN   \n",
+              "5                   NaN                NaN                   NaN   \n",
+              "6                   NaN                NaN                   NaN   \n",
+              "7                   NaN                NaN                   NaN   \n",
+              "8                   NaN                NaN                   NaN   \n",
+              "9                   NaN                NaN                   NaN   \n",
+              "10                  NaN                NaN                   NaN   \n",
+              "11                  NaN                NaN                   NaN   \n",
+              "12                  NaN                NaN                   NaN   \n",
+              "13                  NaN                NaN                   NaN   \n",
+              "14                  NaN                NaN                   NaN   \n",
+              "15                  NaN                NaN                   NaN   \n",
+              "16                  NaN                NaN                   NaN   \n",
+              "17                  NaN                NaN                   NaN   \n",
+              "18                  NaN                NaN                   NaN   \n",
+              "19                  NaN                NaN                   NaN   \n",
+              "20                  NaN                NaN                   NaN   \n",
+              "21                  NaN                NaN                   NaN   \n",
+              "22                  NaN                NaN                   NaN   \n",
+              "23                  NaN                NaN                   NaN   \n",
+              "24                  NaN                NaN                   NaN   \n",
+              "...                 ...                ...                   ...   \n",
+              "128387              NaN                NaN                   NaN   \n",
+              "128388              NaN                NaN                   NaN   \n",
+              "128389              NaN                NaN                   NaN   \n",
+              "128390              NaN                NaN                   NaN   \n",
+              "128391              NaN                NaN                   NaN   \n",
+              "128392              NaN                NaN                   NaN   \n",
+              "128393              NaN                NaN                   NaN   \n",
+              "128394              NaN                NaN                   NaN   \n",
+              "128395              NaN                NaN                   NaN   \n",
+              "128396              NaN                NaN                   NaN   \n",
+              "128397              NaN                NaN                   NaN   \n",
+              "128398              NaN                NaN                   NaN   \n",
+              "128399              NaN                NaN                   NaN   \n",
+              "128400              NaN                NaN                   NaN   \n",
+              "128401              NaN                NaN                   NaN   \n",
+              "128402              NaN                NaN                   NaN   \n",
+              "128403              NaN                NaN                   NaN   \n",
+              "128404              NaN                NaN                   NaN   \n",
+              "128405              NaN                NaN                   NaN   \n",
+              "128406              NaN                NaN                   NaN   \n",
+              "128407              NaN                NaN                   NaN   \n",
+              "128408              NaN                NaN                   NaN   \n",
+              "128409              NaN                NaN                   NaN   \n",
+              "128410              NaN                NaN                   NaN   \n",
+              "128411              NaN                NaN                   NaN   \n",
+              "\n",
+              "        settlement_term  \n",
+              "0                   NaN  \n",
+              "1                   NaN  \n",
+              "2                   NaN  \n",
+              "3                   NaN  \n",
+              "4                   NaN  \n",
+              "5                   NaN  \n",
+              "6                   NaN  \n",
+              "7                   NaN  \n",
+              "8                   NaN  \n",
+              "9                   NaN  \n",
+              "10                  NaN  \n",
+              "11                  NaN  \n",
+              "12                  NaN  \n",
+              "13                  NaN  \n",
+              "14                  NaN  \n",
+              "15                  NaN  \n",
+              "16                  NaN  \n",
+              "17                  NaN  \n",
+              "18                  NaN  \n",
+              "19                  NaN  \n",
+              "20                  NaN  \n",
+              "21                  NaN  \n",
+              "22                  NaN  \n",
+              "23                  NaN  \n",
+              "24                  NaN  \n",
+              "...                 ...  \n",
+              "128387              NaN  \n",
+              "128388              NaN  \n",
+              "128389              NaN  \n",
+              "128390              NaN  \n",
+              "128391              NaN  \n",
+              "128392              NaN  \n",
+              "128393              NaN  \n",
+              "128394              NaN  \n",
+              "128395              NaN  \n",
+              "128396              NaN  \n",
+              "128397              NaN  \n",
+              "128398              NaN  \n",
+              "128399              NaN  \n",
+              "128400              NaN  \n",
+              "128401              NaN  \n",
+              "128402              NaN  \n",
+              "128403              NaN  \n",
+              "128404              NaN  \n",
+              "128405              NaN  \n",
+              "128406              NaN  \n",
+              "128407              NaN  \n",
+              "128408              NaN  \n",
+              "128409              NaN  \n",
+              "128410              NaN  \n",
+              "128411              NaN  \n",
+              "\n",
+              "[128412 rows x 140 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 25
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "yv81fT38b7Y5",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df = df.drop(columns=['id', 'member_id', 'desc', 'url'])"
       ],
       "execution_count": 0,
       "outputs": []
     },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "SPVq6Db9cEI2",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 225
+        },
+        "outputId": "7081c67c-3a7d-41b3-9557-7157e826a425"
+      },
+      "source": [
+        "hardship_cols = [col for col in df.columns if col.startswith('hardship_')]\n",
+        "hardship_cols"
+      ],
+      "execution_count": 28,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "['hardship_flag',\n",
+              " 'hardship_type',\n",
+              " 'hardship_reason',\n",
+              " 'hardship_status',\n",
+              " 'hardship_amount',\n",
+              " 'hardship_start_date',\n",
+              " 'hardship_end_date',\n",
+              " 'hardship_length',\n",
+              " 'hardship_dpd',\n",
+              " 'hardship_loan_status',\n",
+              " 'hardship_payoff_balance_amount',\n",
+              " 'hardship_last_payment_amount']"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 28
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "ZlgwkmgOcWJb",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df = df.drop(columns=hardship_cols)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "SDveWAFlccJz",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 209
+        },
+        "outputId": "23191a28-76e9-4810-90ef-c6cc30622bb2"
+      },
+      "source": [
+        "df.describe(exclude='number')"
+      ],
+      "execution_count": 30,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>revol_util</th>\n",
+              "      <th>initial_list_status</th>\n",
+              "      <th>last_pymnt_d</th>\n",
+              "      <th>next_pymnt_d</th>\n",
+              "      <th>last_credit_pull_d</th>\n",
+              "      <th>application_type</th>\n",
+              "      <th>verification_status_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>107465</td>\n",
+              "      <td>116708</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128256</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128253</td>\n",
+              "      <td>112289</td>\n",
+              "      <td>128411</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>14848</td>\n",
+              "      <td>16782</td>\n",
+              "      <td>27</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>111</td>\n",
+              "      <td>111</td>\n",
+              "      <td>111</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>unique</th>\n",
+              "      <td>2</td>\n",
+              "      <td>46</td>\n",
+              "      <td>7</td>\n",
+              "      <td>35</td>\n",
+              "      <td>43892</td>\n",
+              "      <td>11</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>3</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>12</td>\n",
+              "      <td>12</td>\n",
+              "      <td>880</td>\n",
+              "      <td>50</td>\n",
+              "      <td>644</td>\n",
+              "      <td>1074</td>\n",
+              "      <td>2</td>\n",
+              "      <td>12</td>\n",
+              "      <td>3</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>573</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>6</td>\n",
+              "      <td>3</td>\n",
+              "      <td>7</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>top</th>\n",
+              "      <td>36 months</td>\n",
+              "      <td>13.56%</td>\n",
+              "      <td>A</td>\n",
+              "      <td>A4</td>\n",
+              "      <td>Teacher</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>112xx</td>\n",
+              "      <td>CA</td>\n",
+              "      <td>Aug-2006</td>\n",
+              "      <td>0%</td>\n",
+              "      <td>w</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>Sep-2019</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>Individual</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Aug-2006</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>N</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>ACTIVE</td>\n",
+              "      <td>Jul-2019</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>freq</th>\n",
+              "      <td>88179</td>\n",
+              "      <td>6974</td>\n",
+              "      <td>38011</td>\n",
+              "      <td>9770</td>\n",
+              "      <td>2090</td>\n",
+              "      <td>38826</td>\n",
+              "      <td>63490</td>\n",
+              "      <td>58350</td>\n",
+              "      <td>46305</td>\n",
+              "      <td>108584</td>\n",
+              "      <td>128398</td>\n",
+              "      <td>70603</td>\n",
+              "      <td>70603</td>\n",
+              "      <td>1370</td>\n",
+              "      <td>17879</td>\n",
+              "      <td>1130</td>\n",
+              "      <td>1132</td>\n",
+              "      <td>114498</td>\n",
+              "      <td>105424</td>\n",
+              "      <td>112228</td>\n",
+              "      <td>117910</td>\n",
+              "      <td>111630</td>\n",
+              "      <td>6360</td>\n",
+              "      <td>155</td>\n",
+              "      <td>15</td>\n",
+              "      <td>128301</td>\n",
+              "      <td>48</td>\n",
+              "      <td>99</td>\n",
+              "      <td>43</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "              term int_rate   grade sub_grade emp_title emp_length  \\\n",
+              "count       128412   128412  128412    128412    107465     116708   \n",
+              "unique           2       46       7        35     43892         11   \n",
+              "top      36 months   13.56%       A        A4   Teacher  10+ years   \n",
+              "freq         88179     6974   38011      9770      2090      38826   \n",
+              "\n",
+              "       home_ownership verification_status   issue_d loan_status pymnt_plan  \\\n",
+              "count          128412              128412    128412      128412     128412   \n",
+              "unique              4                   3         3           7          2   \n",
+              "top          MORTGAGE        Not Verified  Oct-2018     Current          n   \n",
+              "freq            63490               58350     46305      108584     128398   \n",
+              "\n",
+              "                   purpose               title zip_code addr_state  \\\n",
+              "count               128412              128412   128412     128412   \n",
+              "unique                  12                  12      880         50   \n",
+              "top     debt_consolidation  Debt consolidation    112xx         CA   \n",
+              "freq                 70603               70603     1370      17879   \n",
+              "\n",
+              "       earliest_cr_line revol_util initial_list_status last_pymnt_d  \\\n",
+              "count            128412     128256              128412       128253   \n",
+              "unique              644       1074                   2           12   \n",
+              "top            Aug-2006         0%                   w     Aug-2019   \n",
+              "freq               1130       1132              114498       105424   \n",
+              "\n",
+              "       next_pymnt_d last_credit_pull_d application_type  \\\n",
+              "count        112289             128411           128412   \n",
+              "unique            3                 12                2   \n",
+              "top        Sep-2019           Aug-2019       Individual   \n",
+              "freq         112228             117910           111630   \n",
+              "\n",
+              "       verification_status_joint sec_app_earliest_cr_line  \\\n",
+              "count                      14848                    16782   \n",
+              "unique                         3                      573   \n",
+              "top                 Not Verified                 Aug-2006   \n",
+              "freq                        6360                      155   \n",
+              "\n",
+              "       payment_plan_start_date debt_settlement_flag debt_settlement_flag_date  \\\n",
+              "count                       27               128412                       111   \n",
+              "unique                       3                    2                         6   \n",
+              "top                   Aug-2019                    N                  Aug-2019   \n",
+              "freq                        15               128301                        48   \n",
+              "\n",
+              "       settlement_status settlement_date  \n",
+              "count                111             111  \n",
+              "unique                 3               7  \n",
+              "top               ACTIVE        Jul-2019  \n",
+              "freq                  99              43  "
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 30
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0RqeHyLPi3_6",
+        "colab_type": "text"
+      },
+      "source": [
+        "### Convert int_rate"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "u0ltBe6Bcn2r",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "cac8571d-db52-400f-fe55-19c541d08a04"
+      },
+      "source": [
+        "df['int_rate']"
+      ],
+      "execution_count": 31,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0          10.33%\n",
+              "1          23.40%\n",
+              "2          17.97%\n",
+              "3          20.89%\n",
+              "4          23.40%\n",
+              "5          11.80%\n",
+              "6          12.98%\n",
+              "7          18.94%\n",
+              "8          13.56%\n",
+              "9          13.56%\n",
+              "10         19.92%\n",
+              "11         17.97%\n",
+              "12         26.31%\n",
+              "13         14.47%\n",
+              "14         23.40%\n",
+              "15         23.40%\n",
+              "16         20.89%\n",
+              "17         16.91%\n",
+              "18         20.89%\n",
+              "19         14.47%\n",
+              "20         13.56%\n",
+              "21         14.47%\n",
+              "22         12.98%\n",
+              "23         23.40%\n",
+              "24         11.80%\n",
+              "           ...   \n",
+              "128387     11.55%\n",
+              "128388      8.46%\n",
+              "128389     11.55%\n",
+              "128390     19.92%\n",
+              "128391      6.67%\n",
+              "128392     26.31%\n",
+              "128393     16.91%\n",
+              "128394      6.11%\n",
+              "128395     11.55%\n",
+              "128396     15.02%\n",
+              "128397     15.02%\n",
+              "128398     18.94%\n",
+              "128399     15.02%\n",
+              "128400     15.02%\n",
+              "128401     11.55%\n",
+              "128402     22.35%\n",
+              "128403     16.14%\n",
+              "128404     16.14%\n",
+              "128405      7.84%\n",
+              "128406     13.56%\n",
+              "128407     15.02%\n",
+              "128408     15.02%\n",
+              "128409     13.56%\n",
+              "128410     11.06%\n",
+              "128411     16.91%\n",
+              "Name: int_rate, Length: 128412, dtype: object"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 31
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "V8S1bRoJctDS",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "e8aa8541-07b6-4639-8d2c-35529a7a66d5"
+      },
+      "source": [
+        "a = '16.91%'\n",
+        "a[:-1]"
+      ],
+      "execution_count": 33,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'16.91'"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 33
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "7xjf05Fvc0_W",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "72429144-2e21-477f-c2eb-840d54ed5f0e"
+      },
+      "source": [
+        "a.strip('%')"
+      ],
+      "execution_count": 34,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'16.91'"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 34
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "0Trv-zQ9c_EL",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "ccf77eb0-5a64-432b-9993-e3e99f1d7818"
+      },
+      "source": [
+        "b = '%16%.91%'\n",
+        "b.strip('%')"
+      ],
+      "execution_count": 35,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'16%.91'"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 35
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "f7v3ad5UdIFu",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "6d55587f-4124-4522-8276-1980bfcfb00d"
+      },
+      "source": [
+        "b.replace('%', '')"
+      ],
+      "execution_count": 36,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'16.91'"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 36
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "SZC5XLX2dO5Y",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "77ee51c1-3eda-497a-efa2-5c5c91f8b57b"
+      },
+      "source": [
+        "float(b.replace('%', ''))"
+      ],
+      "execution_count": 37,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "16.91"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 37
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "VbIAMc9ldT7o",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "def remove_percent_to_float(x):\n",
+        "  return float(x[:-1])"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "bDRlhcvZdsq8",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['int_rate'] = df['int_rate'].apply(remove_percent_to_float)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "a1m37Nxed33c",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "36de8416-f5c5-4bf4-9527-4daed7d2d67b"
+      },
+      "source": [
+        "df.head()"
+      ],
+      "execution_count": 41,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>tot_hi_cred_lim</th>\n",
+              "      <th>total_bal_ex_mort</th>\n",
+              "      <th>total_bc_limit</th>\n",
+              "      <th>total_il_high_credit_limit</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>10.33</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Jan-1996</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>367828</td>\n",
+              "      <td>61364</td>\n",
+              "      <td>20900</td>\n",
+              "      <td>54912</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-2006</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>98655</td>\n",
+              "      <td>66926</td>\n",
+              "      <td>21900</td>\n",
+              "      <td>71555</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>17.97</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>Administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2011</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>136927</td>\n",
+              "      <td>11749</td>\n",
+              "      <td>13800</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>20.89</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>Operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Feb-1997</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>7500</td>\n",
+              "      <td>976</td>\n",
+              "      <td>3300</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>Manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jan-1995</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>199744</td>\n",
+              "      <td>31078</td>\n",
+              "      <td>2300</td>\n",
+              "      <td>32206</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 128 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   loan_amnt  funded_amnt  funded_amnt_inv        term  int_rate  installment  \\\n",
+              "0      10000        10000          10000.0   36 months     10.33       324.23   \n",
+              "1       4000         4000           4000.0   36 months     23.40       155.68   \n",
+              "2       5000         5000           5000.0   36 months     17.97       180.69   \n",
+              "3      23000        23000          23000.0   60 months     20.89       620.81   \n",
+              "4       8000         8000           8000.0   36 months     23.40       311.35   \n",
+              "\n",
+              "  grade sub_grade       emp_title emp_length home_ownership  annual_inc  \\\n",
+              "0     B        B1             NaN   < 1 year       MORTGAGE    280000.0   \n",
+              "1     E        E1        Security    3 years           RENT     90000.0   \n",
+              "2     D        D1  Administrative    6 years       MORTGAGE     59280.0   \n",
+              "3     D        D4        Operator    5 years           RENT     68107.0   \n",
+              "4     E        E1         Manager  10+ years            OWN     43000.0   \n",
+              "\n",
+              "  verification_status   issue_d         loan_status pymnt_plan  \\\n",
+              "0        Not Verified  Dec-2018             Current          n   \n",
+              "1     Source Verified  Dec-2018             Current          n   \n",
+              "2     Source Verified  Dec-2018  Late (31-120 days)          n   \n",
+              "3     Source Verified  Dec-2018             Current          n   \n",
+              "4     Source Verified  Dec-2018             Current          n   \n",
+              "\n",
+              "              purpose               title zip_code addr_state    dti  \\\n",
+              "0  debt_consolidation  Debt consolidation    974xx         OR   6.15   \n",
+              "1  debt_consolidation  Debt consolidation    070xx         NJ  26.33   \n",
+              "2  debt_consolidation  Debt consolidation    490xx         MI  10.51   \n",
+              "3  debt_consolidation  Debt consolidation    672xx         KS   0.52   \n",
+              "4  debt_consolidation  Debt consolidation    357xx         AL  33.24   \n",
+              "\n",
+              "   delinq_2yrs earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0            2         Jan-1996               0                    18.0  ...   \n",
+              "1            0         Sep-2006               4                    59.0  ...   \n",
+              "2            0         Apr-2011               0                     NaN  ...   \n",
+              "3            0         Feb-1997               0                     NaN  ...   \n",
+              "4            0         Jan-1995               0                     NaN  ...   \n",
+              "\n",
+              "   tot_hi_cred_lim  total_bal_ex_mort  total_bc_limit  \\\n",
+              "0           367828              61364           20900   \n",
+              "1            98655              66926           21900   \n",
+              "2           136927              11749           13800   \n",
+              "3             7500                976            3300   \n",
+              "4           199744              31078            2300   \n",
+              "\n",
+              "   total_il_high_credit_limit revol_bal_joint  sec_app_earliest_cr_line  \\\n",
+              "0                       54912             NaN                       NaN   \n",
+              "1                       71555             NaN                       NaN   \n",
+              "2                       10000             NaN                       NaN   \n",
+              "3                           0             NaN                       NaN   \n",
+              "4                       32206             NaN                       NaN   \n",
+              "\n",
+              "  sec_app_inq_last_6mths  sec_app_mort_acc  sec_app_open_acc  \\\n",
+              "0                    NaN               NaN               NaN   \n",
+              "1                    NaN               NaN               NaN   \n",
+              "2                    NaN               NaN               NaN   \n",
+              "3                    NaN               NaN               NaN   \n",
+              "4                    NaN               NaN               NaN   \n",
+              "\n",
+              "   sec_app_revol_util  sec_app_open_act_il  sec_app_num_rev_accts  \\\n",
+              "0                 NaN                  NaN                    NaN   \n",
+              "1                 NaN                  NaN                    NaN   \n",
+              "2                 NaN                  NaN                    NaN   \n",
+              "3                 NaN                  NaN                    NaN   \n",
+              "4                 NaN                  NaN                    NaN   \n",
+              "\n",
+              "   sec_app_chargeoff_within_12_mths  sec_app_collections_12_mths_ex_med  \\\n",
+              "0                               NaN                                 NaN   \n",
+              "1                               NaN                                 NaN   \n",
+              "2                               NaN                                 NaN   \n",
+              "3                               NaN                                 NaN   \n",
+              "4                               NaN                                 NaN   \n",
+              "\n",
+              "   sec_app_mths_since_last_major_derog  deferral_term payment_plan_start_date  \\\n",
+              "0                                  NaN            NaN                     NaN   \n",
+              "1                                  NaN            NaN                     NaN   \n",
+              "2                                  NaN            NaN                     NaN   \n",
+              "3                                  NaN            NaN                     NaN   \n",
+              "4                                  NaN            NaN                     NaN   \n",
+              "\n",
+              "   orig_projected_additional_accrued_interest debt_settlement_flag  \\\n",
+              "0                                         NaN                    N   \n",
+              "1                                         NaN                    N   \n",
+              "2                                         NaN                    N   \n",
+              "3                                         NaN                    N   \n",
+              "4                                         NaN                    N   \n",
+              "\n",
+              "  debt_settlement_flag_date  settlement_status  settlement_date  \\\n",
+              "0                       NaN                NaN              NaN   \n",
+              "1                       NaN                NaN              NaN   \n",
+              "2                       NaN                NaN              NaN   \n",
+              "3                       NaN                NaN              NaN   \n",
+              "4                       NaN                NaN              NaN   \n",
+              "\n",
+              "   settlement_amount settlement_percentage  settlement_term  \n",
+              "0                NaN                   NaN              NaN  \n",
+              "1                NaN                   NaN              NaN  \n",
+              "2                NaN                   NaN              NaN  \n",
+              "3                NaN                   NaN              NaN  \n",
+              "4                NaN                   NaN              NaN  \n",
+              "\n",
+              "[5 rows x 128 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 41
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "AS8TDraed7VM",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 381
+        },
+        "outputId": "d1f0550d-dbc4-4e87-cab6-483cd0258af9"
+      },
+      "source": [
+        "df['emp_title'].value_counts(dropna=False).head(20)"
+      ],
+      "execution_count": 42,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "NaN                   20947\n",
+              "Teacher                2090\n",
+              "Manager                1773\n",
+              "Registered Nurse        952\n",
+              "Driver                  924\n",
+              "RN                      726\n",
+              "Supervisor              697\n",
+              "Sales                   580\n",
+              "Project Manager         526\n",
+              "General Manager         523\n",
+              "Office Manager          521\n",
+              "Owner                   420\n",
+              "Director                402\n",
+              "Truck Driver            387\n",
+              "Operations Manager      387\n",
+              "Nurse                   326\n",
+              "Engineer                325\n",
+              "Sales Manager           304\n",
+              "manager                 301\n",
+              "Supervisor              270\n",
+              "Name: emp_title, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 42
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "GYyPQ_XMeM_D",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 209
+        },
+        "outputId": "fa5c7b10-a1be-46b4-e9b7-fc87e82a4617"
+      },
+      "source": [
+        "df.describe(exclude='number')"
+      ],
+      "execution_count": 43,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>term</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>revol_util</th>\n",
+              "      <th>initial_list_status</th>\n",
+              "      <th>last_pymnt_d</th>\n",
+              "      <th>next_pymnt_d</th>\n",
+              "      <th>last_credit_pull_d</th>\n",
+              "      <th>application_type</th>\n",
+              "      <th>verification_status_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>107465</td>\n",
+              "      <td>116708</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128256</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>128253</td>\n",
+              "      <td>112289</td>\n",
+              "      <td>128411</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>14848</td>\n",
+              "      <td>16782</td>\n",
+              "      <td>27</td>\n",
+              "      <td>128412</td>\n",
+              "      <td>111</td>\n",
+              "      <td>111</td>\n",
+              "      <td>111</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>unique</th>\n",
+              "      <td>2</td>\n",
+              "      <td>7</td>\n",
+              "      <td>35</td>\n",
+              "      <td>43892</td>\n",
+              "      <td>11</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>3</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>12</td>\n",
+              "      <td>12</td>\n",
+              "      <td>880</td>\n",
+              "      <td>50</td>\n",
+              "      <td>644</td>\n",
+              "      <td>1074</td>\n",
+              "      <td>2</td>\n",
+              "      <td>12</td>\n",
+              "      <td>3</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>573</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>6</td>\n",
+              "      <td>3</td>\n",
+              "      <td>7</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>top</th>\n",
+              "      <td>36 months</td>\n",
+              "      <td>A</td>\n",
+              "      <td>A4</td>\n",
+              "      <td>Teacher</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Oct-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>112xx</td>\n",
+              "      <td>CA</td>\n",
+              "      <td>Aug-2006</td>\n",
+              "      <td>0%</td>\n",
+              "      <td>w</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>Sep-2019</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>Individual</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Aug-2006</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>N</td>\n",
+              "      <td>Aug-2019</td>\n",
+              "      <td>ACTIVE</td>\n",
+              "      <td>Jul-2019</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>freq</th>\n",
+              "      <td>88179</td>\n",
+              "      <td>38011</td>\n",
+              "      <td>9770</td>\n",
+              "      <td>2090</td>\n",
+              "      <td>38826</td>\n",
+              "      <td>63490</td>\n",
+              "      <td>58350</td>\n",
+              "      <td>46305</td>\n",
+              "      <td>108584</td>\n",
+              "      <td>128398</td>\n",
+              "      <td>70603</td>\n",
+              "      <td>70603</td>\n",
+              "      <td>1370</td>\n",
+              "      <td>17879</td>\n",
+              "      <td>1130</td>\n",
+              "      <td>1132</td>\n",
+              "      <td>114498</td>\n",
+              "      <td>105424</td>\n",
+              "      <td>112228</td>\n",
+              "      <td>117910</td>\n",
+              "      <td>111630</td>\n",
+              "      <td>6360</td>\n",
+              "      <td>155</td>\n",
+              "      <td>15</td>\n",
+              "      <td>128301</td>\n",
+              "      <td>48</td>\n",
+              "      <td>99</td>\n",
+              "      <td>43</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "              term   grade sub_grade emp_title emp_length home_ownership  \\\n",
+              "count       128412  128412    128412    107465     116708         128412   \n",
+              "unique           2       7        35     43892         11              4   \n",
+              "top      36 months       A        A4   Teacher  10+ years       MORTGAGE   \n",
+              "freq         88179   38011      9770      2090      38826          63490   \n",
+              "\n",
+              "       verification_status   issue_d loan_status pymnt_plan  \\\n",
+              "count               128412    128412      128412     128412   \n",
+              "unique                   3         3           7          2   \n",
+              "top           Not Verified  Oct-2018     Current          n   \n",
+              "freq                 58350     46305      108584     128398   \n",
+              "\n",
+              "                   purpose               title zip_code addr_state  \\\n",
+              "count               128412              128412   128412     128412   \n",
+              "unique                  12                  12      880         50   \n",
+              "top     debt_consolidation  Debt consolidation    112xx         CA   \n",
+              "freq                 70603               70603     1370      17879   \n",
+              "\n",
+              "       earliest_cr_line revol_util initial_list_status last_pymnt_d  \\\n",
+              "count            128412     128256              128412       128253   \n",
+              "unique              644       1074                   2           12   \n",
+              "top            Aug-2006         0%                   w     Aug-2019   \n",
+              "freq               1130       1132              114498       105424   \n",
+              "\n",
+              "       next_pymnt_d last_credit_pull_d application_type  \\\n",
+              "count        112289             128411           128412   \n",
+              "unique            3                 12                2   \n",
+              "top        Sep-2019           Aug-2019       Individual   \n",
+              "freq         112228             117910           111630   \n",
+              "\n",
+              "       verification_status_joint sec_app_earliest_cr_line  \\\n",
+              "count                      14848                    16782   \n",
+              "unique                         3                      573   \n",
+              "top                 Not Verified                 Aug-2006   \n",
+              "freq                        6360                      155   \n",
+              "\n",
+              "       payment_plan_start_date debt_settlement_flag debt_settlement_flag_date  \\\n",
+              "count                       27               128412                       111   \n",
+              "unique                       3                    2                         6   \n",
+              "top                   Aug-2019                    N                  Aug-2019   \n",
+              "freq                        15               128301                        48   \n",
+              "\n",
+              "       settlement_status settlement_date  \n",
+              "count                111             111  \n",
+              "unique                 3               7  \n",
+              "top               ACTIVE        Jul-2019  \n",
+              "freq                  99              43  "
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 43
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "wDBdnMkveTfU",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "def clean_title(title):\n",
+        "  if isinstance(title, str):\n",
+        "    return title.strip().lower()\n",
+        "  else:\n",
+        "    return 'unknown'"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "2LIgq2npemA_",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['emp_title'] = df['emp_title'].apply(clean_title)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "JAf3gWOney1k",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 381
+        },
+        "outputId": "cebba66a-bd8b-4005-ab33-3ea3442c68ba"
+      },
+      "source": [
+        "df['emp_title'].value_counts(dropna=False).head(20)"
+      ],
+      "execution_count": 46,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "unknown               20947\n",
+              "teacher                2557\n",
+              "manager                2395\n",
+              "registered nurse       1418\n",
+              "driver                 1258\n",
+              "supervisor             1160\n",
+              "truck driver            920\n",
+              "rn                      834\n",
+              "office manager          805\n",
+              "sales                   803\n",
+              "general manager         791\n",
+              "project manager         720\n",
+              "owner                   625\n",
+              "director                523\n",
+              "operations manager      518\n",
+              "sales manager           500\n",
+              "police officer          440\n",
+              "nurse                   425\n",
+              "technician              420\n",
+              "engineer                412\n",
+              "Name: emp_title, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 46
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "4sfFFyRwe8to",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "a67605e8-a6da-423b-efdd-b891b988a9b2"
+      },
+      "source": [
+        "type(np.NaN)"
+      ],
+      "execution_count": 47,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "float"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 47
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "ZKdSDW1kfV0T",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['emp_title_manager'] = df['emp_title'].str.contains('manager')"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Xz7NnN-BfhRC",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 156
+        },
+        "outputId": "648b6593-440e-4e88-a0a9-74f184d93053"
+      },
+      "source": [
+        "df.columns"
+      ],
+      "execution_count": 49,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Index(['loan_amnt', 'funded_amnt', 'funded_amnt_inv', 'term', 'int_rate',\n",
+              "       'installment', 'grade', 'sub_grade', 'emp_title', 'emp_length',\n",
+              "       ...\n",
+              "       'payment_plan_start_date', 'orig_projected_additional_accrued_interest',\n",
+              "       'debt_settlement_flag', 'debt_settlement_flag_date',\n",
+              "       'settlement_status', 'settlement_date', 'settlement_amount',\n",
+              "       'settlement_percentage', 'settlement_term', 'emp_title_manager'],\n",
+              "      dtype='object', length=129)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 49
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "LDPZWsvFfjn0",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "9dc8228f-1470-497a-d269-4ccf6f24b2f4"
+      },
+      "source": [
+        "df.head()"
+      ],
+      "execution_count": 50,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>total_bal_ex_mort</th>\n",
+              "      <th>total_bc_limit</th>\n",
+              "      <th>total_il_high_credit_limit</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "      <th>emp_title_manager</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>10.33</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>unknown</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Jan-1996</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>61364</td>\n",
+              "      <td>20900</td>\n",
+              "      <td>54912</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-2006</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>66926</td>\n",
+              "      <td>21900</td>\n",
+              "      <td>71555</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>17.97</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2011</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>11749</td>\n",
+              "      <td>13800</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>20.89</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Feb-1997</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>976</td>\n",
+              "      <td>3300</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>Dec-2018</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jan-1995</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>31078</td>\n",
+              "      <td>2300</td>\n",
+              "      <td>32206</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>True</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 129 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   loan_amnt  funded_amnt  funded_amnt_inv        term  int_rate  installment  \\\n",
+              "0      10000        10000          10000.0   36 months     10.33       324.23   \n",
+              "1       4000         4000           4000.0   36 months     23.40       155.68   \n",
+              "2       5000         5000           5000.0   36 months     17.97       180.69   \n",
+              "3      23000        23000          23000.0   60 months     20.89       620.81   \n",
+              "4       8000         8000           8000.0   36 months     23.40       311.35   \n",
+              "\n",
+              "  grade sub_grade       emp_title emp_length home_ownership  annual_inc  \\\n",
+              "0     B        B1         unknown   < 1 year       MORTGAGE    280000.0   \n",
+              "1     E        E1        security    3 years           RENT     90000.0   \n",
+              "2     D        D1  administrative    6 years       MORTGAGE     59280.0   \n",
+              "3     D        D4        operator    5 years           RENT     68107.0   \n",
+              "4     E        E1         manager  10+ years            OWN     43000.0   \n",
+              "\n",
+              "  verification_status   issue_d         loan_status pymnt_plan  \\\n",
+              "0        Not Verified  Dec-2018             Current          n   \n",
+              "1     Source Verified  Dec-2018             Current          n   \n",
+              "2     Source Verified  Dec-2018  Late (31-120 days)          n   \n",
+              "3     Source Verified  Dec-2018             Current          n   \n",
+              "4     Source Verified  Dec-2018             Current          n   \n",
+              "\n",
+              "              purpose               title zip_code addr_state    dti  \\\n",
+              "0  debt_consolidation  Debt consolidation    974xx         OR   6.15   \n",
+              "1  debt_consolidation  Debt consolidation    070xx         NJ  26.33   \n",
+              "2  debt_consolidation  Debt consolidation    490xx         MI  10.51   \n",
+              "3  debt_consolidation  Debt consolidation    672xx         KS   0.52   \n",
+              "4  debt_consolidation  Debt consolidation    357xx         AL  33.24   \n",
+              "\n",
+              "   delinq_2yrs earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0            2         Jan-1996               0                    18.0  ...   \n",
+              "1            0         Sep-2006               4                    59.0  ...   \n",
+              "2            0         Apr-2011               0                     NaN  ...   \n",
+              "3            0         Feb-1997               0                     NaN  ...   \n",
+              "4            0         Jan-1995               0                     NaN  ...   \n",
+              "\n",
+              "   total_bal_ex_mort  total_bc_limit  total_il_high_credit_limit  \\\n",
+              "0              61364           20900                       54912   \n",
+              "1              66926           21900                       71555   \n",
+              "2              11749           13800                       10000   \n",
+              "3                976            3300                           0   \n",
+              "4              31078            2300                       32206   \n",
+              "\n",
+              "   revol_bal_joint sec_app_earliest_cr_line  sec_app_inq_last_6mths  \\\n",
+              "0              NaN                      NaN                     NaN   \n",
+              "1              NaN                      NaN                     NaN   \n",
+              "2              NaN                      NaN                     NaN   \n",
+              "3              NaN                      NaN                     NaN   \n",
+              "4              NaN                      NaN                     NaN   \n",
+              "\n",
+              "  sec_app_mort_acc  sec_app_open_acc  sec_app_revol_util  sec_app_open_act_il  \\\n",
+              "0              NaN               NaN                 NaN                  NaN   \n",
+              "1              NaN               NaN                 NaN                  NaN   \n",
+              "2              NaN               NaN                 NaN                  NaN   \n",
+              "3              NaN               NaN                 NaN                  NaN   \n",
+              "4              NaN               NaN                 NaN                  NaN   \n",
+              "\n",
+              "   sec_app_num_rev_accts  sec_app_chargeoff_within_12_mths  \\\n",
+              "0                    NaN                               NaN   \n",
+              "1                    NaN                               NaN   \n",
+              "2                    NaN                               NaN   \n",
+              "3                    NaN                               NaN   \n",
+              "4                    NaN                               NaN   \n",
+              "\n",
+              "   sec_app_collections_12_mths_ex_med  sec_app_mths_since_last_major_derog  \\\n",
+              "0                                 NaN                                  NaN   \n",
+              "1                                 NaN                                  NaN   \n",
+              "2                                 NaN                                  NaN   \n",
+              "3                                 NaN                                  NaN   \n",
+              "4                                 NaN                                  NaN   \n",
+              "\n",
+              "   deferral_term  payment_plan_start_date  \\\n",
+              "0            NaN                      NaN   \n",
+              "1            NaN                      NaN   \n",
+              "2            NaN                      NaN   \n",
+              "3            NaN                      NaN   \n",
+              "4            NaN                      NaN   \n",
+              "\n",
+              "  orig_projected_additional_accrued_interest  debt_settlement_flag  \\\n",
+              "0                                        NaN                     N   \n",
+              "1                                        NaN                     N   \n",
+              "2                                        NaN                     N   \n",
+              "3                                        NaN                     N   \n",
+              "4                                        NaN                     N   \n",
+              "\n",
+              "  debt_settlement_flag_date settlement_status  settlement_date  \\\n",
+              "0                       NaN               NaN              NaN   \n",
+              "1                       NaN               NaN              NaN   \n",
+              "2                       NaN               NaN              NaN   \n",
+              "3                       NaN               NaN              NaN   \n",
+              "4                       NaN               NaN              NaN   \n",
+              "\n",
+              "   settlement_amount  settlement_percentage settlement_term  emp_title_manager  \n",
+              "0                NaN                    NaN             NaN              False  \n",
+              "1                NaN                    NaN             NaN              False  \n",
+              "2                NaN                    NaN             NaN              False  \n",
+              "3                NaN                    NaN             NaN              False  \n",
+              "4                NaN                    NaN             NaN               True  \n",
+              "\n",
+              "[5 rows x 129 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 50
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "rt0pyxfmfpM0",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "mask = df['emp_title_manager'] == True\n",
+        "managers = df[mask]\n",
+        "plebians = df[~mask]"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "9wtJE03Sf5KM",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "8e0e42dd-83f7-49dc-b75f-62a8bb65f00a"
+      },
+      "source": [
+        "managers.shape[0]"
+      ],
+      "execution_count": 53,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "17885"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 53
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "oF_QVFQmf-Dk",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "be193d41-5a4f-4816-9de9-a7ce9cfe7033"
+      },
+      "source": [
+        "plebians.shape[0]"
+      ],
+      "execution_count": 54,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "110527"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 54
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "oiPoEAQbgCbX",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "assert managers.shape[0] + plebians.shape[0] == df.shape[0]"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "pvcVN9EYgPKt",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "145a0714-ab47-4a2c-c646-5711503cb40f"
+      },
+      "source": [
+        "df['issue_d']"
+      ],
+      "execution_count": 56,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0         Dec-2018\n",
+              "1         Dec-2018\n",
+              "2         Dec-2018\n",
+              "3         Dec-2018\n",
+              "4         Dec-2018\n",
+              "5         Dec-2018\n",
+              "6         Dec-2018\n",
+              "7         Dec-2018\n",
+              "8         Dec-2018\n",
+              "9         Dec-2018\n",
+              "10        Dec-2018\n",
+              "11        Dec-2018\n",
+              "12        Dec-2018\n",
+              "13        Dec-2018\n",
+              "14        Dec-2018\n",
+              "15        Dec-2018\n",
+              "16        Dec-2018\n",
+              "17        Dec-2018\n",
+              "18        Dec-2018\n",
+              "19        Dec-2018\n",
+              "20        Dec-2018\n",
+              "21        Dec-2018\n",
+              "22        Dec-2018\n",
+              "23        Dec-2018\n",
+              "24        Dec-2018\n",
+              "            ...   \n",
+              "128387    Oct-2018\n",
+              "128388    Oct-2018\n",
+              "128389    Oct-2018\n",
+              "128390    Oct-2018\n",
+              "128391    Oct-2018\n",
+              "128392    Oct-2018\n",
+              "128393    Oct-2018\n",
+              "128394    Oct-2018\n",
+              "128395    Oct-2018\n",
+              "128396    Oct-2018\n",
+              "128397    Oct-2018\n",
+              "128398    Oct-2018\n",
+              "128399    Oct-2018\n",
+              "128400    Oct-2018\n",
+              "128401    Oct-2018\n",
+              "128402    Oct-2018\n",
+              "128403    Oct-2018\n",
+              "128404    Oct-2018\n",
+              "128405    Oct-2018\n",
+              "128406    Oct-2018\n",
+              "128407    Oct-2018\n",
+              "128408    Oct-2018\n",
+              "128409    Oct-2018\n",
+              "128410    Oct-2018\n",
+              "128411    Oct-2018\n",
+              "Name: issue_d, Length: 128412, dtype: object"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 56
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "pYR0clWtgXP_",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['issue_d'] = pd.to_datetime(df['issue_d'], infer_datetime_format=True)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "46QgvRZ3gmhv",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "d0d3d813-6f43-4bdd-f6fd-2fbe2cf343bb"
+      },
+      "source": [
+        "df['issue_d']"
+      ],
+      "execution_count": 58,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0        2018-12-01\n",
+              "1        2018-12-01\n",
+              "2        2018-12-01\n",
+              "3        2018-12-01\n",
+              "4        2018-12-01\n",
+              "5        2018-12-01\n",
+              "6        2018-12-01\n",
+              "7        2018-12-01\n",
+              "8        2018-12-01\n",
+              "9        2018-12-01\n",
+              "10       2018-12-01\n",
+              "11       2018-12-01\n",
+              "12       2018-12-01\n",
+              "13       2018-12-01\n",
+              "14       2018-12-01\n",
+              "15       2018-12-01\n",
+              "16       2018-12-01\n",
+              "17       2018-12-01\n",
+              "18       2018-12-01\n",
+              "19       2018-12-01\n",
+              "20       2018-12-01\n",
+              "21       2018-12-01\n",
+              "22       2018-12-01\n",
+              "23       2018-12-01\n",
+              "24       2018-12-01\n",
+              "            ...    \n",
+              "128387   2018-10-01\n",
+              "128388   2018-10-01\n",
+              "128389   2018-10-01\n",
+              "128390   2018-10-01\n",
+              "128391   2018-10-01\n",
+              "128392   2018-10-01\n",
+              "128393   2018-10-01\n",
+              "128394   2018-10-01\n",
+              "128395   2018-10-01\n",
+              "128396   2018-10-01\n",
+              "128397   2018-10-01\n",
+              "128398   2018-10-01\n",
+              "128399   2018-10-01\n",
+              "128400   2018-10-01\n",
+              "128401   2018-10-01\n",
+              "128402   2018-10-01\n",
+              "128403   2018-10-01\n",
+              "128404   2018-10-01\n",
+              "128405   2018-10-01\n",
+              "128406   2018-10-01\n",
+              "128407   2018-10-01\n",
+              "128408   2018-10-01\n",
+              "128409   2018-10-01\n",
+              "128410   2018-10-01\n",
+              "128411   2018-10-01\n",
+              "Name: issue_d, Length: 128412, dtype: datetime64[ns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 58
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "zTcwxmasgrJo",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "a172c89b-a6c5-4585-d317-db5ac0619d08"
+      },
+      "source": [
+        "df['issue_d'].dt.weekday"
+      ],
+      "execution_count": 59,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0         5\n",
+              "1         5\n",
+              "2         5\n",
+              "3         5\n",
+              "4         5\n",
+              "5         5\n",
+              "6         5\n",
+              "7         5\n",
+              "8         5\n",
+              "9         5\n",
+              "10        5\n",
+              "11        5\n",
+              "12        5\n",
+              "13        5\n",
+              "14        5\n",
+              "15        5\n",
+              "16        5\n",
+              "17        5\n",
+              "18        5\n",
+              "19        5\n",
+              "20        5\n",
+              "21        5\n",
+              "22        5\n",
+              "23        5\n",
+              "24        5\n",
+              "         ..\n",
+              "128387    0\n",
+              "128388    0\n",
+              "128389    0\n",
+              "128390    0\n",
+              "128391    0\n",
+              "128392    0\n",
+              "128393    0\n",
+              "128394    0\n",
+              "128395    0\n",
+              "128396    0\n",
+              "128397    0\n",
+              "128398    0\n",
+              "128399    0\n",
+              "128400    0\n",
+              "128401    0\n",
+              "128402    0\n",
+              "128403    0\n",
+              "128404    0\n",
+              "128405    0\n",
+              "128406    0\n",
+              "128407    0\n",
+              "128408    0\n",
+              "128409    0\n",
+              "128410    0\n",
+              "128411    0\n",
+              "Name: issue_d, Length: 128412, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 59
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "sNflWlELgx4N",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['issue_year'] = df['issue_d'].dt.year\n",
+        "df['issue_month'] = df['issue_d'].dt.month"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "E_xKDjhWhE9c",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "61d5fbb0-1585-48a5-f06e-645255cb2175"
+      },
+      "source": [
+        "df.head()"
+      ],
+      "execution_count": 61,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>total_il_high_credit_limit</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "      <th>emp_title_manager</th>\n",
+              "      <th>issue_year</th>\n",
+              "      <th>issue_month</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>10.33</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>unknown</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Jan-1996</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>54912</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Sep-2006</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>71555</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>17.97</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Apr-2011</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>20.89</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Feb-1997</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Jan-1995</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>32206</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>True</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 131 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   loan_amnt  funded_amnt  funded_amnt_inv        term  int_rate  installment  \\\n",
+              "0      10000        10000          10000.0   36 months     10.33       324.23   \n",
+              "1       4000         4000           4000.0   36 months     23.40       155.68   \n",
+              "2       5000         5000           5000.0   36 months     17.97       180.69   \n",
+              "3      23000        23000          23000.0   60 months     20.89       620.81   \n",
+              "4       8000         8000           8000.0   36 months     23.40       311.35   \n",
+              "\n",
+              "  grade sub_grade       emp_title emp_length home_ownership  annual_inc  \\\n",
+              "0     B        B1         unknown   < 1 year       MORTGAGE    280000.0   \n",
+              "1     E        E1        security    3 years           RENT     90000.0   \n",
+              "2     D        D1  administrative    6 years       MORTGAGE     59280.0   \n",
+              "3     D        D4        operator    5 years           RENT     68107.0   \n",
+              "4     E        E1         manager  10+ years            OWN     43000.0   \n",
+              "\n",
+              "  verification_status    issue_d         loan_status pymnt_plan  \\\n",
+              "0        Not Verified 2018-12-01             Current          n   \n",
+              "1     Source Verified 2018-12-01             Current          n   \n",
+              "2     Source Verified 2018-12-01  Late (31-120 days)          n   \n",
+              "3     Source Verified 2018-12-01             Current          n   \n",
+              "4     Source Verified 2018-12-01             Current          n   \n",
+              "\n",
+              "              purpose               title zip_code addr_state    dti  \\\n",
+              "0  debt_consolidation  Debt consolidation    974xx         OR   6.15   \n",
+              "1  debt_consolidation  Debt consolidation    070xx         NJ  26.33   \n",
+              "2  debt_consolidation  Debt consolidation    490xx         MI  10.51   \n",
+              "3  debt_consolidation  Debt consolidation    672xx         KS   0.52   \n",
+              "4  debt_consolidation  Debt consolidation    357xx         AL  33.24   \n",
+              "\n",
+              "   delinq_2yrs earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0            2         Jan-1996               0                    18.0  ...   \n",
+              "1            0         Sep-2006               4                    59.0  ...   \n",
+              "2            0         Apr-2011               0                     NaN  ...   \n",
+              "3            0         Feb-1997               0                     NaN  ...   \n",
+              "4            0         Jan-1995               0                     NaN  ...   \n",
+              "\n",
+              "   total_il_high_credit_limit  revol_bal_joint  sec_app_earliest_cr_line  \\\n",
+              "0                       54912              NaN                       NaN   \n",
+              "1                       71555              NaN                       NaN   \n",
+              "2                       10000              NaN                       NaN   \n",
+              "3                           0              NaN                       NaN   \n",
+              "4                       32206              NaN                       NaN   \n",
+              "\n",
+              "   sec_app_inq_last_6mths sec_app_mort_acc  sec_app_open_acc  \\\n",
+              "0                     NaN              NaN               NaN   \n",
+              "1                     NaN              NaN               NaN   \n",
+              "2                     NaN              NaN               NaN   \n",
+              "3                     NaN              NaN               NaN   \n",
+              "4                     NaN              NaN               NaN   \n",
+              "\n",
+              "  sec_app_revol_util  sec_app_open_act_il  sec_app_num_rev_accts  \\\n",
+              "0                NaN                  NaN                    NaN   \n",
+              "1                NaN                  NaN                    NaN   \n",
+              "2                NaN                  NaN                    NaN   \n",
+              "3                NaN                  NaN                    NaN   \n",
+              "4                NaN                  NaN                    NaN   \n",
+              "\n",
+              "   sec_app_chargeoff_within_12_mths  sec_app_collections_12_mths_ex_med  \\\n",
+              "0                               NaN                                 NaN   \n",
+              "1                               NaN                                 NaN   \n",
+              "2                               NaN                                 NaN   \n",
+              "3                               NaN                                 NaN   \n",
+              "4                               NaN                                 NaN   \n",
+              "\n",
+              "   sec_app_mths_since_last_major_derog  deferral_term  \\\n",
+              "0                                  NaN            NaN   \n",
+              "1                                  NaN            NaN   \n",
+              "2                                  NaN            NaN   \n",
+              "3                                  NaN            NaN   \n",
+              "4                                  NaN            NaN   \n",
+              "\n",
+              "   payment_plan_start_date  orig_projected_additional_accrued_interest  \\\n",
+              "0                      NaN                                         NaN   \n",
+              "1                      NaN                                         NaN   \n",
+              "2                      NaN                                         NaN   \n",
+              "3                      NaN                                         NaN   \n",
+              "4                      NaN                                         NaN   \n",
+              "\n",
+              "   debt_settlement_flag debt_settlement_flag_date  settlement_status  \\\n",
+              "0                     N                       NaN                NaN   \n",
+              "1                     N                       NaN                NaN   \n",
+              "2                     N                       NaN                NaN   \n",
+              "3                     N                       NaN                NaN   \n",
+              "4                     N                       NaN                NaN   \n",
+              "\n",
+              "  settlement_date settlement_amount  settlement_percentage  settlement_term  \\\n",
+              "0             NaN               NaN                    NaN              NaN   \n",
+              "1             NaN               NaN                    NaN              NaN   \n",
+              "2             NaN               NaN                    NaN              NaN   \n",
+              "3             NaN               NaN                    NaN              NaN   \n",
+              "4             NaN               NaN                    NaN              NaN   \n",
+              "\n",
+              "   emp_title_manager issue_year  issue_month  \n",
+              "0              False       2018           12  \n",
+              "1              False       2018           12  \n",
+              "2              False       2018           12  \n",
+              "3              False       2018           12  \n",
+              "4               True       2018           12  \n",
+              "\n",
+              "[5 rows x 131 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 61
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "kFpUDsOThKlt",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['earliest_cr_line'] = pd.to_datetime(df['earliest_cr_line'], infer_datetime_format=True)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "fGrcT_DahZO9",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "1ff66bd4-6df2-4f21-c4ee-37b9587f65f7"
+      },
+      "source": [
+        "df['days_from_cr_line_to_loan'] = (df['issue_d'] - df['earliest_cr_line']).dt.days\n",
+        "df.head()"
+      ],
+      "execution_count": 64,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "      <th>emp_title_manager</th>\n",
+              "      <th>issue_year</th>\n",
+              "      <th>issue_month</th>\n",
+              "      <th>days_from_cr_line_to_loan</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>10.33</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>unknown</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1996-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8370</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2006-09-01</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>4474</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>17.97</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2011-04-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2801</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60 months</td>\n",
+              "      <td>20.89</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1997-02-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>7973</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36 months</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1995-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>True</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8735</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 132 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   loan_amnt  funded_amnt  funded_amnt_inv        term  int_rate  installment  \\\n",
+              "0      10000        10000          10000.0   36 months     10.33       324.23   \n",
+              "1       4000         4000           4000.0   36 months     23.40       155.68   \n",
+              "2       5000         5000           5000.0   36 months     17.97       180.69   \n",
+              "3      23000        23000          23000.0   60 months     20.89       620.81   \n",
+              "4       8000         8000           8000.0   36 months     23.40       311.35   \n",
+              "\n",
+              "  grade sub_grade       emp_title emp_length home_ownership  annual_inc  \\\n",
+              "0     B        B1         unknown   < 1 year       MORTGAGE    280000.0   \n",
+              "1     E        E1        security    3 years           RENT     90000.0   \n",
+              "2     D        D1  administrative    6 years       MORTGAGE     59280.0   \n",
+              "3     D        D4        operator    5 years           RENT     68107.0   \n",
+              "4     E        E1         manager  10+ years            OWN     43000.0   \n",
+              "\n",
+              "  verification_status    issue_d         loan_status pymnt_plan  \\\n",
+              "0        Not Verified 2018-12-01             Current          n   \n",
+              "1     Source Verified 2018-12-01             Current          n   \n",
+              "2     Source Verified 2018-12-01  Late (31-120 days)          n   \n",
+              "3     Source Verified 2018-12-01             Current          n   \n",
+              "4     Source Verified 2018-12-01             Current          n   \n",
+              "\n",
+              "              purpose               title zip_code addr_state    dti  \\\n",
+              "0  debt_consolidation  Debt consolidation    974xx         OR   6.15   \n",
+              "1  debt_consolidation  Debt consolidation    070xx         NJ  26.33   \n",
+              "2  debt_consolidation  Debt consolidation    490xx         MI  10.51   \n",
+              "3  debt_consolidation  Debt consolidation    672xx         KS   0.52   \n",
+              "4  debt_consolidation  Debt consolidation    357xx         AL  33.24   \n",
+              "\n",
+              "   delinq_2yrs earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0            2       1996-01-01               0                    18.0  ...   \n",
+              "1            0       2006-09-01               4                    59.0  ...   \n",
+              "2            0       2011-04-01               0                     NaN  ...   \n",
+              "3            0       1997-02-01               0                     NaN  ...   \n",
+              "4            0       1995-01-01               0                     NaN  ...   \n",
+              "\n",
+              "   revol_bal_joint  sec_app_earliest_cr_line  sec_app_inq_last_6mths  \\\n",
+              "0              NaN                       NaN                     NaN   \n",
+              "1              NaN                       NaN                     NaN   \n",
+              "2              NaN                       NaN                     NaN   \n",
+              "3              NaN                       NaN                     NaN   \n",
+              "4              NaN                       NaN                     NaN   \n",
+              "\n",
+              "   sec_app_mort_acc sec_app_open_acc  sec_app_revol_util sec_app_open_act_il  \\\n",
+              "0               NaN              NaN                 NaN                 NaN   \n",
+              "1               NaN              NaN                 NaN                 NaN   \n",
+              "2               NaN              NaN                 NaN                 NaN   \n",
+              "3               NaN              NaN                 NaN                 NaN   \n",
+              "4               NaN              NaN                 NaN                 NaN   \n",
+              "\n",
+              "   sec_app_num_rev_accts  sec_app_chargeoff_within_12_mths  \\\n",
+              "0                    NaN                               NaN   \n",
+              "1                    NaN                               NaN   \n",
+              "2                    NaN                               NaN   \n",
+              "3                    NaN                               NaN   \n",
+              "4                    NaN                               NaN   \n",
+              "\n",
+              "   sec_app_collections_12_mths_ex_med  sec_app_mths_since_last_major_derog  \\\n",
+              "0                                 NaN                                  NaN   \n",
+              "1                                 NaN                                  NaN   \n",
+              "2                                 NaN                                  NaN   \n",
+              "3                                 NaN                                  NaN   \n",
+              "4                                 NaN                                  NaN   \n",
+              "\n",
+              "   deferral_term  payment_plan_start_date  \\\n",
+              "0            NaN                      NaN   \n",
+              "1            NaN                      NaN   \n",
+              "2            NaN                      NaN   \n",
+              "3            NaN                      NaN   \n",
+              "4            NaN                      NaN   \n",
+              "\n",
+              "   orig_projected_additional_accrued_interest  debt_settlement_flag  \\\n",
+              "0                                         NaN                     N   \n",
+              "1                                         NaN                     N   \n",
+              "2                                         NaN                     N   \n",
+              "3                                         NaN                     N   \n",
+              "4                                         NaN                     N   \n",
+              "\n",
+              "   debt_settlement_flag_date settlement_status  settlement_date  \\\n",
+              "0                        NaN               NaN              NaN   \n",
+              "1                        NaN               NaN              NaN   \n",
+              "2                        NaN               NaN              NaN   \n",
+              "3                        NaN               NaN              NaN   \n",
+              "4                        NaN               NaN              NaN   \n",
+              "\n",
+              "  settlement_amount settlement_percentage  settlement_term  emp_title_manager  \\\n",
+              "0               NaN                   NaN              NaN              False   \n",
+              "1               NaN                   NaN              NaN              False   \n",
+              "2               NaN                   NaN              NaN              False   \n",
+              "3               NaN                   NaN              NaN              False   \n",
+              "4               NaN                   NaN              NaN               True   \n",
+              "\n",
+              "   issue_year issue_month  days_from_cr_line_to_loan  \n",
+              "0        2018          12                       8370  \n",
+              "1        2018          12                       4474  \n",
+              "2        2018          12                       2801  \n",
+              "3        2018          12                       7973  \n",
+              "4        2018          12                       8735  \n",
+              "\n",
+              "[5 rows x 132 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 64
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "79yzKETEkhUr",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Convert 'Term' To Int"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "7iWacFyZhvDq",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 69
+        },
+        "outputId": "2f37253f-ccf0-44f8-ebc2-9af80d64891d"
+      },
+      "source": [
+        "df['term'].value_counts()"
+      ],
+      "execution_count": 65,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              " 36 months    88179\n",
+              " 60 months    40233\n",
+              "Name: term, dtype: int64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 65
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "UUWqXQcXkSbA",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df = df.rename(columns={'term': 'term_(months)'})"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "RpDos6Rvkr9g",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "def remove_months(x):\n",
+        "  return int(x[:-7])"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "_IpjDIwwlZn0",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df.head()"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "9Umx8ZhslC2K",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['term_(months)'] = df['term_(months)'].apply(remove_months)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "sUSufef9ntwW",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "d1ada732-2ef9-4cf2-f05a-516a95702efb"
+      },
+      "source": [
+        "df.head()"
+      ],
+      "execution_count": 78,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term_(months)</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>revol_bal_joint</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "      <th>emp_title_manager</th>\n",
+              "      <th>issue_year</th>\n",
+              "      <th>issue_month</th>\n",
+              "      <th>days_from_cr_line_to_loan</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>10.33</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>unknown</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1996-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8370</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2006-09-01</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>4474</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>17.97</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2011-04-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2801</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>20.89</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1997-02-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>7973</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1995-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>True</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8735</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 132 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   loan_amnt  funded_amnt  funded_amnt_inv  term_(months)  int_rate  \\\n",
+              "0      10000        10000          10000.0             36     10.33   \n",
+              "1       4000         4000           4000.0             36     23.40   \n",
+              "2       5000         5000           5000.0             36     17.97   \n",
+              "3      23000        23000          23000.0             60     20.89   \n",
+              "4       8000         8000           8000.0             36     23.40   \n",
+              "\n",
+              "   installment grade sub_grade       emp_title emp_length home_ownership  \\\n",
+              "0       324.23     B        B1         unknown   < 1 year       MORTGAGE   \n",
+              "1       155.68     E        E1        security    3 years           RENT   \n",
+              "2       180.69     D        D1  administrative    6 years       MORTGAGE   \n",
+              "3       620.81     D        D4        operator    5 years           RENT   \n",
+              "4       311.35     E        E1         manager  10+ years            OWN   \n",
+              "\n",
+              "   annual_inc verification_status    issue_d         loan_status pymnt_plan  \\\n",
+              "0    280000.0        Not Verified 2018-12-01             Current          n   \n",
+              "1     90000.0     Source Verified 2018-12-01             Current          n   \n",
+              "2     59280.0     Source Verified 2018-12-01  Late (31-120 days)          n   \n",
+              "3     68107.0     Source Verified 2018-12-01             Current          n   \n",
+              "4     43000.0     Source Verified 2018-12-01             Current          n   \n",
+              "\n",
+              "              purpose               title zip_code addr_state    dti  \\\n",
+              "0  debt_consolidation  Debt consolidation    974xx         OR   6.15   \n",
+              "1  debt_consolidation  Debt consolidation    070xx         NJ  26.33   \n",
+              "2  debt_consolidation  Debt consolidation    490xx         MI  10.51   \n",
+              "3  debt_consolidation  Debt consolidation    672xx         KS   0.52   \n",
+              "4  debt_consolidation  Debt consolidation    357xx         AL  33.24   \n",
+              "\n",
+              "   delinq_2yrs earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0            2       1996-01-01               0                    18.0  ...   \n",
+              "1            0       2006-09-01               4                    59.0  ...   \n",
+              "2            0       2011-04-01               0                     NaN  ...   \n",
+              "3            0       1997-02-01               0                     NaN  ...   \n",
+              "4            0       1995-01-01               0                     NaN  ...   \n",
+              "\n",
+              "   revol_bal_joint  sec_app_earliest_cr_line  sec_app_inq_last_6mths  \\\n",
+              "0              NaN                       NaN                     NaN   \n",
+              "1              NaN                       NaN                     NaN   \n",
+              "2              NaN                       NaN                     NaN   \n",
+              "3              NaN                       NaN                     NaN   \n",
+              "4              NaN                       NaN                     NaN   \n",
+              "\n",
+              "   sec_app_mort_acc sec_app_open_acc  sec_app_revol_util sec_app_open_act_il  \\\n",
+              "0               NaN              NaN                 NaN                 NaN   \n",
+              "1               NaN              NaN                 NaN                 NaN   \n",
+              "2               NaN              NaN                 NaN                 NaN   \n",
+              "3               NaN              NaN                 NaN                 NaN   \n",
+              "4               NaN              NaN                 NaN                 NaN   \n",
+              "\n",
+              "   sec_app_num_rev_accts  sec_app_chargeoff_within_12_mths  \\\n",
+              "0                    NaN                               NaN   \n",
+              "1                    NaN                               NaN   \n",
+              "2                    NaN                               NaN   \n",
+              "3                    NaN                               NaN   \n",
+              "4                    NaN                               NaN   \n",
+              "\n",
+              "   sec_app_collections_12_mths_ex_med  sec_app_mths_since_last_major_derog  \\\n",
+              "0                                 NaN                                  NaN   \n",
+              "1                                 NaN                                  NaN   \n",
+              "2                                 NaN                                  NaN   \n",
+              "3                                 NaN                                  NaN   \n",
+              "4                                 NaN                                  NaN   \n",
+              "\n",
+              "   deferral_term  payment_plan_start_date  \\\n",
+              "0            NaN                      NaN   \n",
+              "1            NaN                      NaN   \n",
+              "2            NaN                      NaN   \n",
+              "3            NaN                      NaN   \n",
+              "4            NaN                      NaN   \n",
+              "\n",
+              "   orig_projected_additional_accrued_interest  debt_settlement_flag  \\\n",
+              "0                                         NaN                     N   \n",
+              "1                                         NaN                     N   \n",
+              "2                                         NaN                     N   \n",
+              "3                                         NaN                     N   \n",
+              "4                                         NaN                     N   \n",
+              "\n",
+              "   debt_settlement_flag_date settlement_status  settlement_date  \\\n",
+              "0                        NaN               NaN              NaN   \n",
+              "1                        NaN               NaN              NaN   \n",
+              "2                        NaN               NaN              NaN   \n",
+              "3                        NaN               NaN              NaN   \n",
+              "4                        NaN               NaN              NaN   \n",
+              "\n",
+              "  settlement_amount settlement_percentage  settlement_term  emp_title_manager  \\\n",
+              "0               NaN                   NaN              NaN              False   \n",
+              "1               NaN                   NaN              NaN              False   \n",
+              "2               NaN                   NaN              NaN              False   \n",
+              "3               NaN                   NaN              NaN              False   \n",
+              "4               NaN                   NaN              NaN               True   \n",
+              "\n",
+              "   issue_year issue_month  days_from_cr_line_to_loan  \n",
+              "0        2018          12                       8370  \n",
+              "1        2018          12                       4474  \n",
+              "2        2018          12                       2801  \n",
+              "3        2018          12                       7973  \n",
+              "4        2018          12                       8735  \n",
+              "\n",
+              "[5 rows x 132 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 78
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "LTXPJocSnwc7",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "db41f68e-f6b0-448c-d1e8-6f08d0212113"
+      },
+      "source": [
+        "df['term_(months)'].dtype"
+      ],
+      "execution_count": 80,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "dtype('int64')"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 80
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lIHxJH4WoAbL",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Loan Status Is Great"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Y0t7__BQoaC1",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "68663254-b22b-4e5d-ab39-400e36ddeba1"
+      },
+      "source": [
+        "df['loan_status']"
+      ],
+      "execution_count": 82,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0                    Current\n",
+              "1                    Current\n",
+              "2         Late (31-120 days)\n",
+              "3                    Current\n",
+              "4                    Current\n",
+              "5                    Current\n",
+              "6                    Current\n",
+              "7                    Current\n",
+              "8                 Fully Paid\n",
+              "9                    Current\n",
+              "10                   Current\n",
+              "11                   Current\n",
+              "12                   Current\n",
+              "13                   Current\n",
+              "14                   Current\n",
+              "15                   Current\n",
+              "16                   Current\n",
+              "17                   Current\n",
+              "18                   Current\n",
+              "19                Fully Paid\n",
+              "20                   Current\n",
+              "21                   Current\n",
+              "22                   Current\n",
+              "23                   Current\n",
+              "24                   Current\n",
+              "                 ...        \n",
+              "128387               Current\n",
+              "128388               Current\n",
+              "128389           Charged Off\n",
+              "128390    Late (31-120 days)\n",
+              "128391            Fully Paid\n",
+              "128392               Current\n",
+              "128393               Current\n",
+              "128394               Current\n",
+              "128395               Current\n",
+              "128396               Current\n",
+              "128397            Fully Paid\n",
+              "128398               Current\n",
+              "128399               Current\n",
+              "128400               Current\n",
+              "128401               Current\n",
+              "128402               Current\n",
+              "128403               Current\n",
+              "128404            Fully Paid\n",
+              "128405               Current\n",
+              "128406               Current\n",
+              "128407           Charged Off\n",
+              "128408               Current\n",
+              "128409               Current\n",
+              "128410               Current\n",
+              "128411               Current\n",
+              "Name: loan_status, Length: 128412, dtype: object"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 82
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "a3VPrROIoGLE",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "082bdf11-cbcb-4c7f-ad87-5ef77b891194"
+      },
+      "source": [
+        "loan_status_great = df['loan_status'].str.contains('Current') | df['loan_status'].str.contains('Fully Paid')\n",
+        "loan_status_great"
+      ],
+      "execution_count": 85,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0          True\n",
+              "1          True\n",
+              "2         False\n",
+              "3          True\n",
+              "4          True\n",
+              "5          True\n",
+              "6          True\n",
+              "7          True\n",
+              "8          True\n",
+              "9          True\n",
+              "10         True\n",
+              "11         True\n",
+              "12         True\n",
+              "13         True\n",
+              "14         True\n",
+              "15         True\n",
+              "16         True\n",
+              "17         True\n",
+              "18         True\n",
+              "19         True\n",
+              "20         True\n",
+              "21         True\n",
+              "22         True\n",
+              "23         True\n",
+              "24         True\n",
+              "          ...  \n",
+              "128387     True\n",
+              "128388     True\n",
+              "128389    False\n",
+              "128390    False\n",
+              "128391     True\n",
+              "128392     True\n",
+              "128393     True\n",
+              "128394     True\n",
+              "128395     True\n",
+              "128396     True\n",
+              "128397     True\n",
+              "128398     True\n",
+              "128399     True\n",
+              "128400     True\n",
+              "128401     True\n",
+              "128402     True\n",
+              "128403     True\n",
+              "128404     True\n",
+              "128405     True\n",
+              "128406     True\n",
+              "128407    False\n",
+              "128408     True\n",
+              "128409     True\n",
+              "128410     True\n",
+              "128411     True\n",
+              "Name: loan_status, Length: 128412, dtype: bool"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 85
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "8Hc_zJn2pGdN",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "def bool_int_convert(x):\n",
+        "  return int(x)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "OTEwPmifpnw5",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['loan_status_is_great'] = loan_status_great"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "WLM0ZxY4pxbk",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "df['loan_status_is_great'] = df['loan_status_is_great'].apply(bool_int_convert)"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "DxMS-s7lpt1-",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "c889cec4-b0b3-4022-fd01-10279d2b6009"
+      },
+      "source": [
+        "df.head()"
+      ],
+      "execution_count": 91,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term_(months)</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>sec_app_earliest_cr_line</th>\n",
+              "      <th>sec_app_inq_last_6mths</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "      <th>emp_title_manager</th>\n",
+              "      <th>issue_year</th>\n",
+              "      <th>issue_month</th>\n",
+              "      <th>days_from_cr_line_to_loan</th>\n",
+              "      <th>loan_status_is_great</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>10.33</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>unknown</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1996-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8370</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2006-09-01</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>4474</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>17.97</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2011-04-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2801</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>20.89</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1997-02-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>7973</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1995-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>True</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8735</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 133 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   loan_amnt  funded_amnt  funded_amnt_inv  term_(months)  int_rate  \\\n",
+              "0      10000        10000          10000.0             36     10.33   \n",
+              "1       4000         4000           4000.0             36     23.40   \n",
+              "2       5000         5000           5000.0             36     17.97   \n",
+              "3      23000        23000          23000.0             60     20.89   \n",
+              "4       8000         8000           8000.0             36     23.40   \n",
+              "\n",
+              "   installment grade sub_grade       emp_title emp_length home_ownership  \\\n",
+              "0       324.23     B        B1         unknown   < 1 year       MORTGAGE   \n",
+              "1       155.68     E        E1        security    3 years           RENT   \n",
+              "2       180.69     D        D1  administrative    6 years       MORTGAGE   \n",
+              "3       620.81     D        D4        operator    5 years           RENT   \n",
+              "4       311.35     E        E1         manager  10+ years            OWN   \n",
+              "\n",
+              "   annual_inc verification_status    issue_d         loan_status pymnt_plan  \\\n",
+              "0    280000.0        Not Verified 2018-12-01             Current          n   \n",
+              "1     90000.0     Source Verified 2018-12-01             Current          n   \n",
+              "2     59280.0     Source Verified 2018-12-01  Late (31-120 days)          n   \n",
+              "3     68107.0     Source Verified 2018-12-01             Current          n   \n",
+              "4     43000.0     Source Verified 2018-12-01             Current          n   \n",
+              "\n",
+              "              purpose               title zip_code addr_state    dti  \\\n",
+              "0  debt_consolidation  Debt consolidation    974xx         OR   6.15   \n",
+              "1  debt_consolidation  Debt consolidation    070xx         NJ  26.33   \n",
+              "2  debt_consolidation  Debt consolidation    490xx         MI  10.51   \n",
+              "3  debt_consolidation  Debt consolidation    672xx         KS   0.52   \n",
+              "4  debt_consolidation  Debt consolidation    357xx         AL  33.24   \n",
+              "\n",
+              "   delinq_2yrs earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0            2       1996-01-01               0                    18.0  ...   \n",
+              "1            0       2006-09-01               4                    59.0  ...   \n",
+              "2            0       2011-04-01               0                     NaN  ...   \n",
+              "3            0       1997-02-01               0                     NaN  ...   \n",
+              "4            0       1995-01-01               0                     NaN  ...   \n",
+              "\n",
+              "   sec_app_earliest_cr_line  sec_app_inq_last_6mths  sec_app_mort_acc  \\\n",
+              "0                       NaN                     NaN               NaN   \n",
+              "1                       NaN                     NaN               NaN   \n",
+              "2                       NaN                     NaN               NaN   \n",
+              "3                       NaN                     NaN               NaN   \n",
+              "4                       NaN                     NaN               NaN   \n",
+              "\n",
+              "   sec_app_open_acc sec_app_revol_util  sec_app_open_act_il  \\\n",
+              "0               NaN                NaN                  NaN   \n",
+              "1               NaN                NaN                  NaN   \n",
+              "2               NaN                NaN                  NaN   \n",
+              "3               NaN                NaN                  NaN   \n",
+              "4               NaN                NaN                  NaN   \n",
+              "\n",
+              "  sec_app_num_rev_accts  sec_app_chargeoff_within_12_mths  \\\n",
+              "0                   NaN                               NaN   \n",
+              "1                   NaN                               NaN   \n",
+              "2                   NaN                               NaN   \n",
+              "3                   NaN                               NaN   \n",
+              "4                   NaN                               NaN   \n",
+              "\n",
+              "   sec_app_collections_12_mths_ex_med  sec_app_mths_since_last_major_derog  \\\n",
+              "0                                 NaN                                  NaN   \n",
+              "1                                 NaN                                  NaN   \n",
+              "2                                 NaN                                  NaN   \n",
+              "3                                 NaN                                  NaN   \n",
+              "4                                 NaN                                  NaN   \n",
+              "\n",
+              "   deferral_term  payment_plan_start_date  \\\n",
+              "0            NaN                      NaN   \n",
+              "1            NaN                      NaN   \n",
+              "2            NaN                      NaN   \n",
+              "3            NaN                      NaN   \n",
+              "4            NaN                      NaN   \n",
+              "\n",
+              "   orig_projected_additional_accrued_interest  debt_settlement_flag  \\\n",
+              "0                                         NaN                     N   \n",
+              "1                                         NaN                     N   \n",
+              "2                                         NaN                     N   \n",
+              "3                                         NaN                     N   \n",
+              "4                                         NaN                     N   \n",
+              "\n",
+              "   debt_settlement_flag_date  settlement_status settlement_date  \\\n",
+              "0                        NaN                NaN             NaN   \n",
+              "1                        NaN                NaN             NaN   \n",
+              "2                        NaN                NaN             NaN   \n",
+              "3                        NaN                NaN             NaN   \n",
+              "4                        NaN                NaN             NaN   \n",
+              "\n",
+              "   settlement_amount settlement_percentage settlement_term  emp_title_manager  \\\n",
+              "0                NaN                   NaN             NaN              False   \n",
+              "1                NaN                   NaN             NaN              False   \n",
+              "2                NaN                   NaN             NaN              False   \n",
+              "3                NaN                   NaN             NaN              False   \n",
+              "4                NaN                   NaN             NaN               True   \n",
+              "\n",
+              "   issue_year  issue_month days_from_cr_line_to_loan  loan_status_is_great  \n",
+              "0        2018           12                      8370                     1  \n",
+              "1        2018           12                      4474                     1  \n",
+              "2        2018           12                      2801                     0  \n",
+              "3        2018           12                      7973                     1  \n",
+              "4        2018           12                      8735                     1  \n",
+              "\n",
+              "[5 rows x 133 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 91
+        }
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -141,4 +12358,4 @@
       "outputs": []
     }
   ]
-}
+}
\ No newline at end of file

From 670dbc3f5e8c4c4e4d71e14441d770d06fcf5bc9 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Thu, 12 Sep 2019 23:55:36 -0400
Subject: [PATCH 7/9] Ben Whitman Assignment 4

---
 .../LS_DS_114_Make_Features_Assignment.ipynb  | 739 +++++++++++++++++-
 1 file changed, 738 insertions(+), 1 deletion(-)

diff --git a/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb b/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb
index bb58d3e2..e04e9f27 100644
--- a/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb
+++ b/module4-makefeatures/LS_DS_114_Make_Features_Assignment.ipynb
@@ -7,7 +7,12 @@
       "version": "0.3.2",
       "provenance": [],
       "collapsed_sections": [
-        "e9240Lt4h6rI"
+        "e9240Lt4h6rI",
+        "0ZGBxJ_DXlLh",
+        "9Fv_aNMniGBK",
+        "Um4OaTU1iKIC",
+        "79yzKETEkhUr",
+        "lIHxJH4WoAbL"
       ],
       "include_colab_link": true
     },
@@ -12286,6 +12291,738 @@
         }
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "yi4XEv5Zq5bG",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Last Payment Month & Year"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Jt9SjgghrDYL",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "d4d73832-cd78-4b0b-af16-10c0473361b8"
+      },
+      "source": [
+        "df['last_pymnt_d'] = pd.to_datetime(df['last_pymnt_d'], infer_datetime_format=True)\n",
+        "df['last_pymnt_d']"
+      ],
+      "execution_count": 101,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0        2019-07-01\n",
+              "1        2019-07-01\n",
+              "2        2019-06-01\n",
+              "3        2019-07-01\n",
+              "4        2019-07-01\n",
+              "5        2019-07-01\n",
+              "6        2019-08-01\n",
+              "7        2019-07-01\n",
+              "8        2019-05-01\n",
+              "9        2019-07-01\n",
+              "10       2019-07-01\n",
+              "11       2019-07-01\n",
+              "12       2019-07-01\n",
+              "13       2019-07-01\n",
+              "14       2019-07-01\n",
+              "15       2019-08-01\n",
+              "16       2019-08-01\n",
+              "17       2019-07-01\n",
+              "18       2019-07-01\n",
+              "19       2019-04-01\n",
+              "20       2019-07-01\n",
+              "21       2019-07-01\n",
+              "22       2019-07-01\n",
+              "23       2019-07-01\n",
+              "24       2019-07-01\n",
+              "            ...    \n",
+              "128387   2019-08-01\n",
+              "128388   2019-08-01\n",
+              "128389   2019-03-01\n",
+              "128390   2019-06-01\n",
+              "128391   2019-01-01\n",
+              "128392   2019-08-01\n",
+              "128393   2019-08-01\n",
+              "128394   2019-08-01\n",
+              "128395   2019-08-01\n",
+              "128396   2019-08-01\n",
+              "128397   2019-08-01\n",
+              "128398   2019-08-01\n",
+              "128399   2019-08-01\n",
+              "128400   2019-08-01\n",
+              "128401   2019-08-01\n",
+              "128402   2019-08-01\n",
+              "128403   2019-08-01\n",
+              "128404   2019-04-01\n",
+              "128405   2019-08-01\n",
+              "128406   2019-08-01\n",
+              "128407   2018-12-01\n",
+              "128408   2019-08-01\n",
+              "128409   2019-08-01\n",
+              "128410   2019-08-01\n",
+              "128411   2019-08-01\n",
+              "Name: last_pymnt_d, Length: 128412, dtype: datetime64[ns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 101
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "gMDooDLWvwDG",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "ecf59d54-8e1e-4a49-e383-96426d9134bf"
+      },
+      "source": [
+        "df['last_pymnt_d_month'] = df['last_pymnt_d'].dt.month\n",
+        "df['last_pymnt_d_month']"
+      ],
+      "execution_count": 103,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0          7.0\n",
+              "1          7.0\n",
+              "2          6.0\n",
+              "3          7.0\n",
+              "4          7.0\n",
+              "5          7.0\n",
+              "6          8.0\n",
+              "7          7.0\n",
+              "8          5.0\n",
+              "9          7.0\n",
+              "10         7.0\n",
+              "11         7.0\n",
+              "12         7.0\n",
+              "13         7.0\n",
+              "14         7.0\n",
+              "15         8.0\n",
+              "16         8.0\n",
+              "17         7.0\n",
+              "18         7.0\n",
+              "19         4.0\n",
+              "20         7.0\n",
+              "21         7.0\n",
+              "22         7.0\n",
+              "23         7.0\n",
+              "24         7.0\n",
+              "          ... \n",
+              "128387     8.0\n",
+              "128388     8.0\n",
+              "128389     3.0\n",
+              "128390     6.0\n",
+              "128391     1.0\n",
+              "128392     8.0\n",
+              "128393     8.0\n",
+              "128394     8.0\n",
+              "128395     8.0\n",
+              "128396     8.0\n",
+              "128397     8.0\n",
+              "128398     8.0\n",
+              "128399     8.0\n",
+              "128400     8.0\n",
+              "128401     8.0\n",
+              "128402     8.0\n",
+              "128403     8.0\n",
+              "128404     4.0\n",
+              "128405     8.0\n",
+              "128406     8.0\n",
+              "128407    12.0\n",
+              "128408     8.0\n",
+              "128409     8.0\n",
+              "128410     8.0\n",
+              "128411     8.0\n",
+              "Name: last_pymnt_d_month, Length: 128412, dtype: float64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 103
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "SJOQp4TPwH9w",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 919
+        },
+        "outputId": "920eee93-b5f8-4062-d880-f18ad28d1a06"
+      },
+      "source": [
+        "df['last_pymnt_d_year'] = df['last_pymnt_d'].dt.year\n",
+        "df['last_pymnt_d_year']"
+      ],
+      "execution_count": 104,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0         2019.0\n",
+              "1         2019.0\n",
+              "2         2019.0\n",
+              "3         2019.0\n",
+              "4         2019.0\n",
+              "5         2019.0\n",
+              "6         2019.0\n",
+              "7         2019.0\n",
+              "8         2019.0\n",
+              "9         2019.0\n",
+              "10        2019.0\n",
+              "11        2019.0\n",
+              "12        2019.0\n",
+              "13        2019.0\n",
+              "14        2019.0\n",
+              "15        2019.0\n",
+              "16        2019.0\n",
+              "17        2019.0\n",
+              "18        2019.0\n",
+              "19        2019.0\n",
+              "20        2019.0\n",
+              "21        2019.0\n",
+              "22        2019.0\n",
+              "23        2019.0\n",
+              "24        2019.0\n",
+              "           ...  \n",
+              "128387    2019.0\n",
+              "128388    2019.0\n",
+              "128389    2019.0\n",
+              "128390    2019.0\n",
+              "128391    2019.0\n",
+              "128392    2019.0\n",
+              "128393    2019.0\n",
+              "128394    2019.0\n",
+              "128395    2019.0\n",
+              "128396    2019.0\n",
+              "128397    2019.0\n",
+              "128398    2019.0\n",
+              "128399    2019.0\n",
+              "128400    2019.0\n",
+              "128401    2019.0\n",
+              "128402    2019.0\n",
+              "128403    2019.0\n",
+              "128404    2019.0\n",
+              "128405    2019.0\n",
+              "128406    2019.0\n",
+              "128407    2018.0\n",
+              "128408    2019.0\n",
+              "128409    2019.0\n",
+              "128410    2019.0\n",
+              "128411    2019.0\n",
+              "Name: last_pymnt_d_year, Length: 128412, dtype: float64"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 104
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "MhLpn3TpwY9U",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 338
+        },
+        "outputId": "2976f00a-10fe-4614-9d99-7f49a1a0b77d"
+      },
+      "source": [
+        "df.head()"
+      ],
+      "execution_count": 105,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>loan_amnt</th>\n",
+              "      <th>funded_amnt</th>\n",
+              "      <th>funded_amnt_inv</th>\n",
+              "      <th>term_(months)</th>\n",
+              "      <th>int_rate</th>\n",
+              "      <th>installment</th>\n",
+              "      <th>grade</th>\n",
+              "      <th>sub_grade</th>\n",
+              "      <th>emp_title</th>\n",
+              "      <th>emp_length</th>\n",
+              "      <th>home_ownership</th>\n",
+              "      <th>annual_inc</th>\n",
+              "      <th>verification_status</th>\n",
+              "      <th>issue_d</th>\n",
+              "      <th>loan_status</th>\n",
+              "      <th>pymnt_plan</th>\n",
+              "      <th>purpose</th>\n",
+              "      <th>title</th>\n",
+              "      <th>zip_code</th>\n",
+              "      <th>addr_state</th>\n",
+              "      <th>dti</th>\n",
+              "      <th>delinq_2yrs</th>\n",
+              "      <th>earliest_cr_line</th>\n",
+              "      <th>inq_last_6mths</th>\n",
+              "      <th>mths_since_last_delinq</th>\n",
+              "      <th>...</th>\n",
+              "      <th>sec_app_mort_acc</th>\n",
+              "      <th>sec_app_open_acc</th>\n",
+              "      <th>sec_app_revol_util</th>\n",
+              "      <th>sec_app_open_act_il</th>\n",
+              "      <th>sec_app_num_rev_accts</th>\n",
+              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
+              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
+              "      <th>sec_app_mths_since_last_major_derog</th>\n",
+              "      <th>deferral_term</th>\n",
+              "      <th>payment_plan_start_date</th>\n",
+              "      <th>orig_projected_additional_accrued_interest</th>\n",
+              "      <th>debt_settlement_flag</th>\n",
+              "      <th>debt_settlement_flag_date</th>\n",
+              "      <th>settlement_status</th>\n",
+              "      <th>settlement_date</th>\n",
+              "      <th>settlement_amount</th>\n",
+              "      <th>settlement_percentage</th>\n",
+              "      <th>settlement_term</th>\n",
+              "      <th>emp_title_manager</th>\n",
+              "      <th>issue_year</th>\n",
+              "      <th>issue_month</th>\n",
+              "      <th>days_from_cr_line_to_loan</th>\n",
+              "      <th>loan_status_is_great</th>\n",
+              "      <th>last_pymnt_d_month</th>\n",
+              "      <th>last_pymnt_d_year</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000</td>\n",
+              "      <td>10000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>10.33</td>\n",
+              "      <td>324.23</td>\n",
+              "      <td>B</td>\n",
+              "      <td>B1</td>\n",
+              "      <td>unknown</td>\n",
+              "      <td>&lt; 1 year</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>280000.0</td>\n",
+              "      <td>Not Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>974xx</td>\n",
+              "      <td>OR</td>\n",
+              "      <td>6.15</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1996-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>18.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8370</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7.0</td>\n",
+              "      <td>2019.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000</td>\n",
+              "      <td>4000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>155.68</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>security</td>\n",
+              "      <td>3 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>90000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>070xx</td>\n",
+              "      <td>NJ</td>\n",
+              "      <td>26.33</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2006-09-01</td>\n",
+              "      <td>4</td>\n",
+              "      <td>59.0</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>4474</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7.0</td>\n",
+              "      <td>2019.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000</td>\n",
+              "      <td>5000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>17.97</td>\n",
+              "      <td>180.69</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D1</td>\n",
+              "      <td>administrative</td>\n",
+              "      <td>6 years</td>\n",
+              "      <td>MORTGAGE</td>\n",
+              "      <td>59280.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Late (31-120 days)</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>490xx</td>\n",
+              "      <td>MI</td>\n",
+              "      <td>10.51</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2011-04-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>2801</td>\n",
+              "      <td>0</td>\n",
+              "      <td>6.0</td>\n",
+              "      <td>2019.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000</td>\n",
+              "      <td>23000.0</td>\n",
+              "      <td>60</td>\n",
+              "      <td>20.89</td>\n",
+              "      <td>620.81</td>\n",
+              "      <td>D</td>\n",
+              "      <td>D4</td>\n",
+              "      <td>operator</td>\n",
+              "      <td>5 years</td>\n",
+              "      <td>RENT</td>\n",
+              "      <td>68107.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>672xx</td>\n",
+              "      <td>KS</td>\n",
+              "      <td>0.52</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1997-02-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>False</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>7973</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7.0</td>\n",
+              "      <td>2019.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000</td>\n",
+              "      <td>8000.0</td>\n",
+              "      <td>36</td>\n",
+              "      <td>23.40</td>\n",
+              "      <td>311.35</td>\n",
+              "      <td>E</td>\n",
+              "      <td>E1</td>\n",
+              "      <td>manager</td>\n",
+              "      <td>10+ years</td>\n",
+              "      <td>OWN</td>\n",
+              "      <td>43000.0</td>\n",
+              "      <td>Source Verified</td>\n",
+              "      <td>2018-12-01</td>\n",
+              "      <td>Current</td>\n",
+              "      <td>n</td>\n",
+              "      <td>debt_consolidation</td>\n",
+              "      <td>Debt consolidation</td>\n",
+              "      <td>357xx</td>\n",
+              "      <td>AL</td>\n",
+              "      <td>33.24</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1995-01-01</td>\n",
+              "      <td>0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>...</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>N</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>True</td>\n",
+              "      <td>2018</td>\n",
+              "      <td>12</td>\n",
+              "      <td>8735</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7.0</td>\n",
+              "      <td>2019.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>5 rows × 135 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   loan_amnt  funded_amnt  funded_amnt_inv  term_(months)  int_rate  \\\n",
+              "0      10000        10000          10000.0             36     10.33   \n",
+              "1       4000         4000           4000.0             36     23.40   \n",
+              "2       5000         5000           5000.0             36     17.97   \n",
+              "3      23000        23000          23000.0             60     20.89   \n",
+              "4       8000         8000           8000.0             36     23.40   \n",
+              "\n",
+              "   installment grade sub_grade       emp_title emp_length home_ownership  \\\n",
+              "0       324.23     B        B1         unknown   < 1 year       MORTGAGE   \n",
+              "1       155.68     E        E1        security    3 years           RENT   \n",
+              "2       180.69     D        D1  administrative    6 years       MORTGAGE   \n",
+              "3       620.81     D        D4        operator    5 years           RENT   \n",
+              "4       311.35     E        E1         manager  10+ years            OWN   \n",
+              "\n",
+              "   annual_inc verification_status    issue_d         loan_status pymnt_plan  \\\n",
+              "0    280000.0        Not Verified 2018-12-01             Current          n   \n",
+              "1     90000.0     Source Verified 2018-12-01             Current          n   \n",
+              "2     59280.0     Source Verified 2018-12-01  Late (31-120 days)          n   \n",
+              "3     68107.0     Source Verified 2018-12-01             Current          n   \n",
+              "4     43000.0     Source Verified 2018-12-01             Current          n   \n",
+              "\n",
+              "              purpose               title zip_code addr_state    dti  \\\n",
+              "0  debt_consolidation  Debt consolidation    974xx         OR   6.15   \n",
+              "1  debt_consolidation  Debt consolidation    070xx         NJ  26.33   \n",
+              "2  debt_consolidation  Debt consolidation    490xx         MI  10.51   \n",
+              "3  debt_consolidation  Debt consolidation    672xx         KS   0.52   \n",
+              "4  debt_consolidation  Debt consolidation    357xx         AL  33.24   \n",
+              "\n",
+              "   delinq_2yrs earliest_cr_line  inq_last_6mths  mths_since_last_delinq  ...  \\\n",
+              "0            2       1996-01-01               0                    18.0  ...   \n",
+              "1            0       2006-09-01               4                    59.0  ...   \n",
+              "2            0       2011-04-01               0                     NaN  ...   \n",
+              "3            0       1997-02-01               0                     NaN  ...   \n",
+              "4            0       1995-01-01               0                     NaN  ...   \n",
+              "\n",
+              "   sec_app_mort_acc  sec_app_open_acc  sec_app_revol_util  \\\n",
+              "0               NaN               NaN                 NaN   \n",
+              "1               NaN               NaN                 NaN   \n",
+              "2               NaN               NaN                 NaN   \n",
+              "3               NaN               NaN                 NaN   \n",
+              "4               NaN               NaN                 NaN   \n",
+              "\n",
+              "   sec_app_open_act_il sec_app_num_rev_accts  \\\n",
+              "0                  NaN                   NaN   \n",
+              "1                  NaN                   NaN   \n",
+              "2                  NaN                   NaN   \n",
+              "3                  NaN                   NaN   \n",
+              "4                  NaN                   NaN   \n",
+              "\n",
+              "   sec_app_chargeoff_within_12_mths sec_app_collections_12_mths_ex_med  \\\n",
+              "0                               NaN                                NaN   \n",
+              "1                               NaN                                NaN   \n",
+              "2                               NaN                                NaN   \n",
+              "3                               NaN                                NaN   \n",
+              "4                               NaN                                NaN   \n",
+              "\n",
+              "   sec_app_mths_since_last_major_derog  deferral_term  \\\n",
+              "0                                  NaN            NaN   \n",
+              "1                                  NaN            NaN   \n",
+              "2                                  NaN            NaN   \n",
+              "3                                  NaN            NaN   \n",
+              "4                                  NaN            NaN   \n",
+              "\n",
+              "   payment_plan_start_date  orig_projected_additional_accrued_interest  \\\n",
+              "0                      NaN                                         NaN   \n",
+              "1                      NaN                                         NaN   \n",
+              "2                      NaN                                         NaN   \n",
+              "3                      NaN                                         NaN   \n",
+              "4                      NaN                                         NaN   \n",
+              "\n",
+              "   debt_settlement_flag  debt_settlement_flag_date  settlement_status  \\\n",
+              "0                     N                        NaN                NaN   \n",
+              "1                     N                        NaN                NaN   \n",
+              "2                     N                        NaN                NaN   \n",
+              "3                     N                        NaN                NaN   \n",
+              "4                     N                        NaN                NaN   \n",
+              "\n",
+              "   settlement_date  settlement_amount settlement_percentage  settlement_term  \\\n",
+              "0              NaN                NaN                   NaN              NaN   \n",
+              "1              NaN                NaN                   NaN              NaN   \n",
+              "2              NaN                NaN                   NaN              NaN   \n",
+              "3              NaN                NaN                   NaN              NaN   \n",
+              "4              NaN                NaN                   NaN              NaN   \n",
+              "\n",
+              "  emp_title_manager issue_year  issue_month  days_from_cr_line_to_loan  \\\n",
+              "0             False       2018           12                       8370   \n",
+              "1             False       2018           12                       4474   \n",
+              "2             False       2018           12                       2801   \n",
+              "3             False       2018           12                       7973   \n",
+              "4              True       2018           12                       8735   \n",
+              "\n",
+              "   loan_status_is_great last_pymnt_d_month  last_pymnt_d_year  \n",
+              "0                     1                7.0             2019.0  \n",
+              "1                     1                7.0             2019.0  \n",
+              "2                     0                6.0             2019.0  \n",
+              "3                     1                7.0             2019.0  \n",
+              "4                     1                7.0             2019.0  \n",
+              "\n",
+              "[5 rows x 135 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 105
+        }
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {

From 6de2f7dd54f3593022ad0e13a367b7635cdd237a Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Thu, 19 Sep 2019 17:20:28 -0400
Subject: [PATCH 8/9] Created using Colaboratory

---
 ...121_Join_and_Reshape_Data_Assignment.ipynb | 2478 +++++++++++++++++
 1 file changed, 2478 insertions(+)
 create mode 100644 module1-join-and-reshape-data/Ben_Whitman_LS_DS_121_Join_and_Reshape_Data_Assignment.ipynb

diff --git a/module1-join-and-reshape-data/Ben_Whitman_LS_DS_121_Join_and_Reshape_Data_Assignment.ipynb b/module1-join-and-reshape-data/Ben_Whitman_LS_DS_121_Join_and_Reshape_Data_Assignment.ipynb
new file mode 100644
index 00000000..b8d73bed
--- /dev/null
+++ b/module1-join-and-reshape-data/Ben_Whitman_LS_DS_121_Join_and_Reshape_Data_Assignment.ipynb
@@ -0,0 +1,2478 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Ben Whitman LS_DS_121_Join_and_Reshape_Data_Assignment.ipynb",
+      "provenance": [],
+      "collapsed_sections": [
+        "CKNMOyPGUbZN",
+        "Ta25gI9sUluO",
+        "5bDnQe7WUtpu",
+        "O9RyOaC-Uwzy"
+      ],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/b-whitman/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module1-join-and-reshape-data/Ben_Whitman_LS_DS_121_Join_and_Reshape_Data_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "pmU5YUal1eTZ"
+      },
+      "source": [
+        "_Lambda School Data Science_\n",
+        "\n",
+        "# Join and Reshape datasets\n",
+        "\n",
+        "Objectives\n",
+        "- concatenate data with pandas\n",
+        "- merge data with pandas\n",
+        "-  understand tidy data formatting\n",
+        "-  melt and pivot data with pandas\n",
+        "\n",
+        "Links\n",
+        "- [Pandas Cheat Sheet](https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf)\n",
+        "- [Tidy Data](https://en.wikipedia.org/wiki/Tidy_data)\n",
+        "  - Combine Data Sets: Standard Joins\n",
+        "  - Tidy Data\n",
+        "  - Reshaping Data\n",
+        "- Python Data Science Handbook\n",
+        "  - [Chapter 3.6](https://jakevdp.github.io/PythonDataScienceHandbook/03.06-concat-and-append.html), Combining Datasets: Concat and Append\n",
+        "  - [Chapter 3.7](https://jakevdp.github.io/PythonDataScienceHandbook/03.07-merge-and-join.html), Combining Datasets: Merge and Join\n",
+        "  - [Chapter 3.8](https://jakevdp.github.io/PythonDataScienceHandbook/03.08-aggregation-and-grouping.html), Aggregation and Grouping\n",
+        "  - [Chapter 3.9](https://jakevdp.github.io/PythonDataScienceHandbook/03.09-pivot-tables.html), Pivot Tables\n",
+        "  \n",
+        "Reference\n",
+        "- Pandas Documentation: [Reshaping and Pivot Tables](https://pandas.pydata.org/pandas-docs/stable/reshaping.html)\n",
+        "- Modern Pandas, Part 5: [Tidy Data](https://tomaugspurger.github.io/modern-5-tidy.html)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "5MsWLLW4Xg_i",
+        "colab_type": "code",
+        "outputId": "e362a67c-e9ac-441c-cf99-19e35b71cbc9",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 208
+        }
+      },
+      "source": [
+        "!wget https://s3.amazonaws.com/instacart-datasets/instacart_online_grocery_shopping_2017_05_01.tar.gz"
+      ],
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "--2019-09-19 19:50:12--  https://s3.amazonaws.com/instacart-datasets/instacart_online_grocery_shopping_2017_05_01.tar.gz\n",
+            "Resolving s3.amazonaws.com (s3.amazonaws.com)... 52.216.146.205\n",
+            "Connecting to s3.amazonaws.com (s3.amazonaws.com)|52.216.146.205|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 205548478 (196M) [application/x-gzip]\n",
+            "Saving to: ‘instacart_online_grocery_shopping_2017_05_01.tar.gz’\n",
+            "\n",
+            "instacart_online_gr 100%[===================>] 196.03M  73.0MB/s    in 2.7s    \n",
+            "\n",
+            "2019-09-19 19:50:15 (73.0 MB/s) - ‘instacart_online_grocery_shopping_2017_05_01.tar.gz’ saved [205548478/205548478]\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "gfr4_Ya0XkLI",
+        "colab_type": "code",
+        "outputId": "b575d60f-d0cf-46c7-e5d4-9276b0a5c2fa",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 243
+        }
+      },
+      "source": [
+        "!tar --gunzip --extract --verbose --file=instacart_online_grocery_shopping_2017_05_01.tar.gz"
+      ],
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "instacart_2017_05_01/\n",
+            "instacart_2017_05_01/._aisles.csv\n",
+            "instacart_2017_05_01/aisles.csv\n",
+            "instacart_2017_05_01/._departments.csv\n",
+            "instacart_2017_05_01/departments.csv\n",
+            "instacart_2017_05_01/._order_products__prior.csv\n",
+            "instacart_2017_05_01/order_products__prior.csv\n",
+            "instacart_2017_05_01/._order_products__train.csv\n",
+            "instacart_2017_05_01/order_products__train.csv\n",
+            "instacart_2017_05_01/._orders.csv\n",
+            "instacart_2017_05_01/orders.csv\n",
+            "instacart_2017_05_01/._products.csv\n",
+            "instacart_2017_05_01/products.csv\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "N4YyGPNdXrT0",
+        "colab_type": "code",
+        "outputId": "f8e799f4-1257-452c-a162-95094af402a8",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        }
+      },
+      "source": [
+        "%cd instacart_2017_05_01"
+      ],
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/content/instacart_2017_05_01\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "b26wmLUiXtlM",
+        "colab_type": "code",
+        "outputId": "59b5bbdc-bd67-42cb-9e51-5ec8d4ec329b",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 121
+        }
+      },
+      "source": [
+        "!ls -lh *.csv"
+      ],
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "-rw-r--r-- 1 502 staff 2.6K May  2  2017 aisles.csv\n",
+            "-rw-r--r-- 1 502 staff  270 May  2  2017 departments.csv\n",
+            "-rw-r--r-- 1 502 staff 551M May  2  2017 order_products__prior.csv\n",
+            "-rw-r--r-- 1 502 staff  24M May  2  2017 order_products__train.csv\n",
+            "-rw-r--r-- 1 502 staff 104M May  2  2017 orders.csv\n",
+            "-rw-r--r-- 1 502 staff 2.1M May  2  2017 products.csv\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "kAMtvSQWPUcj"
+      },
+      "source": [
+        "# Assignment\n",
+        "\n",
+        "## Join Data Practice\n",
+        "\n",
+        "These are the top 10 most frequently ordered products. How many times was each ordered? \n",
+        "\n",
+        "1. Banana\n",
+        "2. Bag of Organic Bananas\n",
+        "3. Organic Strawberries\n",
+        "4. Organic Baby Spinach \n",
+        "5. Organic Hass Avocado\n",
+        "6. Organic Avocado\n",
+        "7. Large Lemon \n",
+        "8. Strawberries\n",
+        "9. Limes \n",
+        "10. Organic Whole Milk\n",
+        "\n",
+        "First, write down which columns you need and which dataframes have them.\n",
+        "\n",
+        "Next, merge these into a single dataframe.\n",
+        "\n",
+        "Then, use pandas functions from the previous lesson to get the counts of the top 10 most frequently ordered products."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "HuqvrX8PGJt_",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import pandas as pd"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "u1FLpRrfHZNM",
+        "colab_type": "text"
+      },
+      "source": [
+        "I need to take product IDs from the \"order_products\" datasets and match them with their corresponding product names from the \"products\" dataset."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "AGQNg9XxIQPl",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "02ca6042-37fe-498d-f1f8-403fc2954fdd"
+      },
+      "source": [
+        "# Create order dataframes and concatenate\n",
+        "order_products__prior = pd.read_csv('order_products__prior.csv')\n",
+        "order_products__train = pd.read_csv('order_products__train.csv')\n",
+        "order_products = pd.concat([order_products__prior, order_products__train])\n",
+        "order_products.shape"
+      ],
+      "execution_count": 11,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(33819106, 4)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 11
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "YqoV-6NvK1E7",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 202
+        },
+        "outputId": "c16df073-9c99-43a3-e1bc-dfeb8c358f7a"
+      },
+      "source": [
+        "# Create product dataframe\n",
+        "products = pd.read_csv('products.csv')\n",
+        "products.head()"
+      ],
+      "execution_count": 16,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>product_id</th>\n",
+              "      <th>product_name</th>\n",
+              "      <th>aisle_id</th>\n",
+              "      <th>department_id</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1</td>\n",
+              "      <td>Chocolate Sandwich Cookies</td>\n",
+              "      <td>61</td>\n",
+              "      <td>19</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2</td>\n",
+              "      <td>All-Seasons Salt</td>\n",
+              "      <td>104</td>\n",
+              "      <td>13</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>3</td>\n",
+              "      <td>Robust Golden Unsweetened Oolong Tea</td>\n",
+              "      <td>94</td>\n",
+              "      <td>7</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>4</td>\n",
+              "      <td>Smart Ones Classic Favorites Mini Rigatoni Wit...</td>\n",
+              "      <td>38</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>5</td>\n",
+              "      <td>Green Chile Anytime Sauce</td>\n",
+              "      <td>5</td>\n",
+              "      <td>13</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   product_id  ... department_id\n",
+              "0           1  ...            19\n",
+              "1           2  ...            13\n",
+              "2           3  ...             7\n",
+              "3           4  ...             1\n",
+              "4           5  ...            13\n",
+              "\n",
+              "[5 rows x 4 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 16
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "vgu2JzlBJFd5",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 202
+        },
+        "outputId": "65509949-a53b-49b7-db9b-eb1478549dec"
+      },
+      "source": [
+        "order_products.head()"
+      ],
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>order_id</th>\n",
+              "      <th>product_id</th>\n",
+              "      <th>add_to_cart_order</th>\n",
+              "      <th>reordered</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>2</td>\n",
+              "      <td>33120</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>2</td>\n",
+              "      <td>28985</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2</td>\n",
+              "      <td>9327</td>\n",
+              "      <td>3</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>2</td>\n",
+              "      <td>45918</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>2</td>\n",
+              "      <td>30035</td>\n",
+              "      <td>5</td>\n",
+              "      <td>0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   order_id  product_id  add_to_cart_order  reordered\n",
+              "0         2       33120                  1          1\n",
+              "1         2       28985                  2          1\n",
+              "2         2        9327                  3          0\n",
+              "3         2       45918                  4          1\n",
+              "4         2       30035                  5          0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 12
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "_z66CVYyK-l7",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 202
+        },
+        "outputId": "a09af36a-f483-4e89-91d8-769033130e08"
+      },
+      "source": [
+        "# Merge product ID and product name columns into order dataframe\n",
+        "columns = ['product_id', 'product_name']\n",
+        "merged = pd.merge(order_products, products[columns])\n",
+        "merged.head()"
+      ],
+      "execution_count": 17,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>order_id</th>\n",
+              "      <th>product_id</th>\n",
+              "      <th>add_to_cart_order</th>\n",
+              "      <th>reordered</th>\n",
+              "      <th>product_name</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>2</td>\n",
+              "      <td>33120</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Organic Egg Whites</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>26</td>\n",
+              "      <td>33120</td>\n",
+              "      <td>5</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Organic Egg Whites</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>120</td>\n",
+              "      <td>33120</td>\n",
+              "      <td>13</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Organic Egg Whites</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>327</td>\n",
+              "      <td>33120</td>\n",
+              "      <td>5</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Organic Egg Whites</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>390</td>\n",
+              "      <td>33120</td>\n",
+              "      <td>28</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Organic Egg Whites</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   order_id  product_id  add_to_cart_order  reordered        product_name\n",
+              "0         2       33120                  1          1  Organic Egg Whites\n",
+              "1        26       33120                  5          0  Organic Egg Whites\n",
+              "2       120       33120                 13          0  Organic Egg Whites\n",
+              "3       327       33120                  5          1  Organic Egg Whites\n",
+              "4       390       33120                 28          1  Organic Egg Whites"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 17
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Q4cYjeHfLnqY",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 662
+        },
+        "outputId": "f6c15c93-3ade-42c4-9590-06d7fde63d02"
+      },
+      "source": [
+        "# Check to see what resulting dataframe looks like\n",
+        "merged.sample(20)"
+      ],
+      "execution_count": 20,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>order_id</th>\n",
+              "      <th>product_id</th>\n",
+              "      <th>add_to_cart_order</th>\n",
+              "      <th>reordered</th>\n",
+              "      <th>product_name</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>30805415</th>\n",
+              "      <td>3062093</td>\n",
+              "      <td>36056</td>\n",
+              "      <td>7</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Freezer Slider Bags</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17421331</th>\n",
+              "      <td>1923455</td>\n",
+              "      <td>17027</td>\n",
+              "      <td>24</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Avocado Roll</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>27332629</th>\n",
+              "      <td>1036970</td>\n",
+              "      <td>31970</td>\n",
+              "      <td>10</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Organic Basmati Rice</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6493980</th>\n",
+              "      <td>2634043</td>\n",
+              "      <td>16797</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Strawberries</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3252794</th>\n",
+              "      <td>2778101</td>\n",
+              "      <td>33198</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Sparkling Natural Mineral Water</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>29343373</th>\n",
+              "      <td>1556721</td>\n",
+              "      <td>12385</td>\n",
+              "      <td>5</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Vegetable Base, Organic</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5210701</th>\n",
+              "      <td>2081272</td>\n",
+              "      <td>47626</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Large Lemon</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25735968</th>\n",
+              "      <td>2522180</td>\n",
+              "      <td>37065</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Serrano Chile Peppers</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16420919</th>\n",
+              "      <td>2184423</td>\n",
+              "      <td>17224</td>\n",
+              "      <td>9</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Oats &amp; Honey Gluten Free Granola</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>17260407</th>\n",
+              "      <td>574624</td>\n",
+              "      <td>42327</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Free &amp; Gentle Fabric Softener Dryer Sheets</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16596762</th>\n",
+              "      <td>3214502</td>\n",
+              "      <td>28986</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Mild Italian Chicken Sausage</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10331555</th>\n",
+              "      <td>3018400</td>\n",
+              "      <td>37158</td>\n",
+              "      <td>11</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Chicken &amp; Maple Breakfast Sausage</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>16084891</th>\n",
+              "      <td>1200234</td>\n",
+              "      <td>38293</td>\n",
+              "      <td>10</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Ground Turkey Breast</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>20842689</th>\n",
+              "      <td>946265</td>\n",
+              "      <td>17630</td>\n",
+              "      <td>8</td>\n",
+              "      <td>1</td>\n",
+              "      <td>YoKids Squeeze! Organic Strawberry Flavor Yogurt</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2525616</th>\n",
+              "      <td>2184944</td>\n",
+              "      <td>47766</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Organic Avocado</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14324008</th>\n",
+              "      <td>3272655</td>\n",
+              "      <td>36082</td>\n",
+              "      <td>7</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Organic Mango</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>32992672</th>\n",
+              "      <td>277751</td>\n",
+              "      <td>22576</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Cheez Whiz Original Cheese Dip</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2895963</th>\n",
+              "      <td>2748553</td>\n",
+              "      <td>21137</td>\n",
+              "      <td>7</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Organic Strawberries</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>27696855</th>\n",
+              "      <td>1506135</td>\n",
+              "      <td>42803</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Organic Apple Slices</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>18648950</th>\n",
+              "      <td>2665247</td>\n",
+              "      <td>33827</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0</td>\n",
+              "      <td>Fat Free French Vanilla Creamer</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "          order_id  ...                                      product_name\n",
+              "30805415   3062093  ...                               Freezer Slider Bags\n",
+              "17421331   1923455  ...                                      Avocado Roll\n",
+              "27332629   1036970  ...                              Organic Basmati Rice\n",
+              "6493980    2634043  ...                                      Strawberries\n",
+              "3252794    2778101  ...                   Sparkling Natural Mineral Water\n",
+              "29343373   1556721  ...                           Vegetable Base, Organic\n",
+              "5210701    2081272  ...                                       Large Lemon\n",
+              "25735968   2522180  ...                             Serrano Chile Peppers\n",
+              "16420919   2184423  ...                  Oats & Honey Gluten Free Granola\n",
+              "17260407    574624  ...        Free & Gentle Fabric Softener Dryer Sheets\n",
+              "16596762   3214502  ...                      Mild Italian Chicken Sausage\n",
+              "10331555   3018400  ...                 Chicken & Maple Breakfast Sausage\n",
+              "16084891   1200234  ...                              Ground Turkey Breast\n",
+              "20842689    946265  ...  YoKids Squeeze! Organic Strawberry Flavor Yogurt\n",
+              "2525616    2184944  ...                                   Organic Avocado\n",
+              "14324008   3272655  ...                                     Organic Mango\n",
+              "32992672    277751  ...                    Cheez Whiz Original Cheese Dip\n",
+              "2895963    2748553  ...                              Organic Strawberries\n",
+              "27696855   1506135  ...                              Organic Apple Slices\n",
+              "18648950   2665247  ...                   Fat Free French Vanilla Creamer\n",
+              "\n",
+              "[20 rows x 5 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 20
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Ipy20cxeMJfz",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# List top ten items\n",
+        "top_ten = pd.Series(['Banana',\n",
+        "'Bag of Organic Bananas',\n",
+        "'Organic Strawberries',\n",
+        "'Organic Baby Spinach',\n",
+        "'Organic Hass Avocado',\n",
+        "'Organic Avocado',\n",
+        "'Large Lemon',\n",
+        "'Strawberries',\n",
+        "'Limes',\n",
+        "'Organic Whole Milk'])"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "VC2dDmulOUyi",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "87ac3d24-e503-4dba-c002-419510d4a51e"
+      },
+      "source": [
+        "# Test counter on one item\n",
+        "merged['product_name'].str.count('Banana').sum()"
+      ],
+      "execution_count": 34,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "1068742"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 34
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "0ap6GX4SMnmA",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# Create function to count all ten of the top ten items\n",
+        "def product_count(x):\n",
+        "  print(x, \":\", merged['product_name'].str.count(x).sum())"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "sZrEp3tzNTx-",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 381
+        },
+        "outputId": "6cb4212b-caf9-43b5-90fb-8a8d6cbc48e4"
+      },
+      "source": [
+        "# So, a couple things: My method of counting takes a long time.\n",
+        "# Might be because of size of dataset? But there could be a faster way.\n",
+        "# Also: I'm not sure why my function spits out 'None' counts for 0-9 at the bottom.\n",
+        "# But it would be cool if it didn't!\n",
+        "top_ten.apply(product_count)"
+      ],
+      "execution_count": 36,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Banana : 1068742\n",
+            "Bag of Organic Bananas : 394930\n",
+            "Organic Strawberries : 282921\n",
+            "Organic Baby Spinach : 270087\n",
+            "Organic Hass Avocado : 223133\n",
+            "Organic Avocado : 190961\n",
+            "Large Lemon : 163643\n",
+            "Strawberries : 508891\n",
+            "Limes : 155846\n",
+            "Organic Whole Milk : 191561\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0    None\n",
+              "1    None\n",
+              "2    None\n",
+              "3    None\n",
+              "4    None\n",
+              "5    None\n",
+              "6    None\n",
+              "7    None\n",
+              "8    None\n",
+              "9    None\n",
+              "dtype: object"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 36
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "RsiWi4DuXPLP",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Reshape Data Section\n",
+        "\n",
+        "- Replicate the lesson code\n",
+        "- Complete the code cells we skipped near the beginning of the notebook\n",
+        "- Table 2 --> Tidy\n",
+        "- Tidy --> Table 2\n",
+        "- Load seaborn's `flights` dataset by running the cell below. Then create a pivot table showing the number of passengers by month and year. Use year for the index and month for the columns. You've done it right if you get 112 passengers for January 1949 and 432 passengers for December 1960."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CKNMOyPGUbZN",
+        "colab_type": "text"
+      },
+      "source": [
+        "### Lesson Code"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "SIv-gjQMRi_C",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "%matplotlib inline\n",
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "import seaborn as sns"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "ukwmwYO-Rx5y",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "table1 = pd.DataFrame(\n",
+        "    [[np.nan, 2],\n",
+        "     [16,    11],\n",
+        "     [3,      1]],\n",
+        "     index=['John Smith', 'Jane Doe', 'Mary Johnson'],\n",
+        "     columns=['treatmenta', 'treatmentb'])\n",
+        "\n",
+        "table2 = table1.T"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "cWrF9EnRSmPZ",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 141
+        },
+        "outputId": "08b04b8e-c08d-4a21-eab5-c388e7f02c87"
+      },
+      "source": [
+        "table1"
+      ],
+      "execution_count": 39,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>treatmenta</th>\n",
+              "      <th>treatmentb</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>John Smith</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>2</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Jane Doe</th>\n",
+              "      <td>16.0</td>\n",
+              "      <td>11</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Mary Johnson</th>\n",
+              "      <td>3.0</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "              treatmenta  treatmentb\n",
+              "John Smith           NaN           2\n",
+              "Jane Doe            16.0          11\n",
+              "Mary Johnson         3.0           1"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 39
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "cICxjIF3Sxud",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 110
+        },
+        "outputId": "57c7d16e-782f-4c49-e3b3-612a778c782b"
+      },
+      "source": [
+        "table2"
+      ],
+      "execution_count": 40,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>John Smith</th>\n",
+              "      <th>Jane Doe</th>\n",
+              "      <th>Mary Johnson</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>treatmenta</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>treatmentb</th>\n",
+              "      <td>2.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            John Smith  Jane Doe  Mary Johnson\n",
+              "treatmenta         NaN      16.0           3.0\n",
+              "treatmentb         2.0      11.0           1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 40
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "MGiDCXuGTATm",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "0aa1405f-b455-4da2-bf7f-cbadd2712f9f"
+      },
+      "source": [
+        "table1.index"
+      ],
+      "execution_count": 41,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Index(['John Smith', 'Jane Doe', 'Mary Johnson'], dtype='object')"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 41
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "bbRl8pOQTEbh",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "table1 = table1.reset_index()"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Y-8TVJwjTJaw",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 141
+        },
+        "outputId": "cdb10ede-a81b-419d-f9ed-4c8f68998733"
+      },
+      "source": [
+        "table1"
+      ],
+      "execution_count": 43,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>index</th>\n",
+              "      <th>treatmenta</th>\n",
+              "      <th>treatmentb</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>2</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>11</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>3.0</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "          index  treatmenta  treatmentb\n",
+              "0    John Smith         NaN           2\n",
+              "1      Jane Doe        16.0          11\n",
+              "2  Mary Johnson         3.0           1"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 43
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "OLWERziKToUi",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 233
+        },
+        "outputId": "29a188b7-9d0a-45ac-c66c-e9f95f41d3bf"
+      },
+      "source": [
+        "tidy = table1.melt(id_vars='index')\n",
+        "tidy"
+      ],
+      "execution_count": 44,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>index</th>\n",
+              "      <th>variable</th>\n",
+              "      <th>value</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>16.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>2.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>11.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "          index    variable  value\n",
+              "0    John Smith  treatmenta    NaN\n",
+              "1      Jane Doe  treatmenta   16.0\n",
+              "2  Mary Johnson  treatmenta    3.0\n",
+              "3    John Smith  treatmentb    2.0\n",
+              "4      Jane Doe  treatmentb   11.0\n",
+              "5  Mary Johnson  treatmentb    1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 44
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "a0xTT8TXUGPS",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 233
+        },
+        "outputId": "5a29e525-f763-49fe-d851-aad47bfccfcf"
+      },
+      "source": [
+        "tidy.columns = ['name', 'trt', 'result']\n",
+        "tidy"
+      ],
+      "execution_count": 46,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>name</th>\n",
+              "      <th>trt</th>\n",
+              "      <th>result</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>16.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>2.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>11.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "           name         trt  result\n",
+              "0    John Smith  treatmenta     NaN\n",
+              "1      Jane Doe  treatmenta    16.0\n",
+              "2  Mary Johnson  treatmenta     3.0\n",
+              "3    John Smith  treatmentb     2.0\n",
+              "4      Jane Doe  treatmentb    11.0\n",
+              "5  Mary Johnson  treatmentb     1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 46
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Ta25gI9sUluO",
+        "colab_type": "text"
+      },
+      "source": [
+        "### Table2 --> Tidy"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "1qKc88WI0up-",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 110
+        },
+        "outputId": "39d1bbd1-4751-4e8c-f936-1d554e6a46e1"
+      },
+      "source": [
+        "table2"
+      ],
+      "execution_count": 47,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>John Smith</th>\n",
+              "      <th>Jane Doe</th>\n",
+              "      <th>Mary Johnson</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>treatmenta</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>treatmentb</th>\n",
+              "      <td>2.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "            John Smith  Jane Doe  Mary Johnson\n",
+              "treatmenta         NaN      16.0           3.0\n",
+              "treatmentb         2.0      11.0           1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 47
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "BgeG4xujU8Gh",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "table2 = table2.reset_index()"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "NCZzpX5cVNj0",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 110
+        },
+        "outputId": "eb45254a-113a-4a7b-9c49-b4f9ec030792"
+      },
+      "source": [
+        "table2"
+      ],
+      "execution_count": 52,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>index</th>\n",
+              "      <th>John Smith</th>\n",
+              "      <th>Jane Doe</th>\n",
+              "      <th>Mary Johnson</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>11.0</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "        index  John Smith  Jane Doe  Mary Johnson\n",
+              "0  treatmenta         NaN      16.0           3.0\n",
+              "1  treatmentb         2.0      11.0           1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 52
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "AeY5R5naVR67",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "tidy2 = table2.melt(id_vars='index')"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "ybubhiJ1VfGX",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 233
+        },
+        "outputId": "edc1212b-4263-4fea-fb1a-e08b1269cd09"
+      },
+      "source": [
+        "tidy2"
+      ],
+      "execution_count": 55,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>index</th>\n",
+              "      <th>variable</th>\n",
+              "      <th>value</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>2.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>16.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>11.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "        index      variable  value\n",
+              "0  treatmenta    John Smith    NaN\n",
+              "1  treatmentb    John Smith    2.0\n",
+              "2  treatmenta      Jane Doe   16.0\n",
+              "3  treatmentb      Jane Doe   11.0\n",
+              "4  treatmenta  Mary Johnson    3.0\n",
+              "5  treatmentb  Mary Johnson    1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 55
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "-UrWn6_AVnRD",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 233
+        },
+        "outputId": "3888fddf-5eb0-49d5-cfc1-93f71730d0ac"
+      },
+      "source": [
+        "tidy2.columns = ['trt', 'name', 'result']\n",
+        "tidy2"
+      ],
+      "execution_count": 56,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>trt</th>\n",
+              "      <th>name</th>\n",
+              "      <th>result</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>John Smith</td>\n",
+              "      <td>2.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>16.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>Jane Doe</td>\n",
+              "      <td>11.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>treatmenta</td>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>treatmentb</td>\n",
+              "      <td>Mary Johnson</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "          trt          name  result\n",
+              "0  treatmenta    John Smith     NaN\n",
+              "1  treatmentb    John Smith     2.0\n",
+              "2  treatmenta      Jane Doe    16.0\n",
+              "3  treatmentb      Jane Doe    11.0\n",
+              "4  treatmenta  Mary Johnson     3.0\n",
+              "5  treatmentb  Mary Johnson     1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 56
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "5bDnQe7WUtpu",
+        "colab_type": "text"
+      },
+      "source": [
+        "### Tidy --> Table2"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "W50sr3k9UwVA",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 141
+        },
+        "outputId": "dcae72f6-1f98-493b-fb68-7e15e332746f"
+      },
+      "source": [
+        "tidy2.pivot_table(index='trt', columns='name', values='result')"
+      ],
+      "execution_count": 57,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th>name</th>\n",
+              "      <th>Jane Doe</th>\n",
+              "      <th>John Smith</th>\n",
+              "      <th>Mary Johnson</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>trt</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>treatmenta</th>\n",
+              "      <td>16.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>treatmentb</th>\n",
+              "      <td>11.0</td>\n",
+              "      <td>2.0</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "name        Jane Doe  John Smith  Mary Johnson\n",
+              "trt                                           \n",
+              "treatmenta      16.0         NaN           3.0\n",
+              "treatmentb      11.0         2.0           1.0"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 57
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "O9RyOaC-Uwzy",
+        "colab_type": "text"
+      },
+      "source": [
+        "### Flights"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "fgxulJQq0uLw",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "flights = sns.load_dataset('flights')"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "7iHdPW_8WaK_",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 202
+        },
+        "outputId": "b24f2fa0-0596-4e4f-e0ba-96ceb383da9a"
+      },
+      "source": [
+        "flights.head()"
+      ],
+      "execution_count": 59,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>year</th>\n",
+              "      <th>month</th>\n",
+              "      <th>passengers</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1949</td>\n",
+              "      <td>January</td>\n",
+              "      <td>112</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>1949</td>\n",
+              "      <td>February</td>\n",
+              "      <td>118</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>1949</td>\n",
+              "      <td>March</td>\n",
+              "      <td>132</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>1949</td>\n",
+              "      <td>April</td>\n",
+              "      <td>129</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>1949</td>\n",
+              "      <td>May</td>\n",
+              "      <td>121</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   year     month  passengers\n",
+              "0  1949   January         112\n",
+              "1  1949  February         118\n",
+              "2  1949     March         132\n",
+              "3  1949     April         129\n",
+              "4  1949       May         121"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 59
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "uzKPSCqoW0Rk",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "f565cdbf-0b5c-4a5c-ffa5-380dfe025638"
+      },
+      "source": [
+        "flights.shape"
+      ],
+      "execution_count": 60,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(144, 3)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 60
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "CX2Z3oQaXGZ4",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 447
+        },
+        "outputId": "c16dd48f-51fe-4cc5-9c39-9357b3766e51"
+      },
+      "source": [
+        "flights.pivot_table(index='year', columns='month', values='passengers')"
+      ],
+      "execution_count": 61,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th>month</th>\n",
+              "      <th>January</th>\n",
+              "      <th>February</th>\n",
+              "      <th>March</th>\n",
+              "      <th>April</th>\n",
+              "      <th>May</th>\n",
+              "      <th>June</th>\n",
+              "      <th>July</th>\n",
+              "      <th>August</th>\n",
+              "      <th>September</th>\n",
+              "      <th>October</th>\n",
+              "      <th>November</th>\n",
+              "      <th>December</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>year</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1949</th>\n",
+              "      <td>112</td>\n",
+              "      <td>118</td>\n",
+              "      <td>132</td>\n",
+              "      <td>129</td>\n",
+              "      <td>121</td>\n",
+              "      <td>135</td>\n",
+              "      <td>148</td>\n",
+              "      <td>148</td>\n",
+              "      <td>136</td>\n",
+              "      <td>119</td>\n",
+              "      <td>104</td>\n",
+              "      <td>118</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1950</th>\n",
+              "      <td>115</td>\n",
+              "      <td>126</td>\n",
+              "      <td>141</td>\n",
+              "      <td>135</td>\n",
+              "      <td>125</td>\n",
+              "      <td>149</td>\n",
+              "      <td>170</td>\n",
+              "      <td>170</td>\n",
+              "      <td>158</td>\n",
+              "      <td>133</td>\n",
+              "      <td>114</td>\n",
+              "      <td>140</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1951</th>\n",
+              "      <td>145</td>\n",
+              "      <td>150</td>\n",
+              "      <td>178</td>\n",
+              "      <td>163</td>\n",
+              "      <td>172</td>\n",
+              "      <td>178</td>\n",
+              "      <td>199</td>\n",
+              "      <td>199</td>\n",
+              "      <td>184</td>\n",
+              "      <td>162</td>\n",
+              "      <td>146</td>\n",
+              "      <td>166</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1952</th>\n",
+              "      <td>171</td>\n",
+              "      <td>180</td>\n",
+              "      <td>193</td>\n",
+              "      <td>181</td>\n",
+              "      <td>183</td>\n",
+              "      <td>218</td>\n",
+              "      <td>230</td>\n",
+              "      <td>242</td>\n",
+              "      <td>209</td>\n",
+              "      <td>191</td>\n",
+              "      <td>172</td>\n",
+              "      <td>194</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1953</th>\n",
+              "      <td>196</td>\n",
+              "      <td>196</td>\n",
+              "      <td>236</td>\n",
+              "      <td>235</td>\n",
+              "      <td>229</td>\n",
+              "      <td>243</td>\n",
+              "      <td>264</td>\n",
+              "      <td>272</td>\n",
+              "      <td>237</td>\n",
+              "      <td>211</td>\n",
+              "      <td>180</td>\n",
+              "      <td>201</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1954</th>\n",
+              "      <td>204</td>\n",
+              "      <td>188</td>\n",
+              "      <td>235</td>\n",
+              "      <td>227</td>\n",
+              "      <td>234</td>\n",
+              "      <td>264</td>\n",
+              "      <td>302</td>\n",
+              "      <td>293</td>\n",
+              "      <td>259</td>\n",
+              "      <td>229</td>\n",
+              "      <td>203</td>\n",
+              "      <td>229</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1955</th>\n",
+              "      <td>242</td>\n",
+              "      <td>233</td>\n",
+              "      <td>267</td>\n",
+              "      <td>269</td>\n",
+              "      <td>270</td>\n",
+              "      <td>315</td>\n",
+              "      <td>364</td>\n",
+              "      <td>347</td>\n",
+              "      <td>312</td>\n",
+              "      <td>274</td>\n",
+              "      <td>237</td>\n",
+              "      <td>278</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1956</th>\n",
+              "      <td>284</td>\n",
+              "      <td>277</td>\n",
+              "      <td>317</td>\n",
+              "      <td>313</td>\n",
+              "      <td>318</td>\n",
+              "      <td>374</td>\n",
+              "      <td>413</td>\n",
+              "      <td>405</td>\n",
+              "      <td>355</td>\n",
+              "      <td>306</td>\n",
+              "      <td>271</td>\n",
+              "      <td>306</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1957</th>\n",
+              "      <td>315</td>\n",
+              "      <td>301</td>\n",
+              "      <td>356</td>\n",
+              "      <td>348</td>\n",
+              "      <td>355</td>\n",
+              "      <td>422</td>\n",
+              "      <td>465</td>\n",
+              "      <td>467</td>\n",
+              "      <td>404</td>\n",
+              "      <td>347</td>\n",
+              "      <td>305</td>\n",
+              "      <td>336</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1958</th>\n",
+              "      <td>340</td>\n",
+              "      <td>318</td>\n",
+              "      <td>362</td>\n",
+              "      <td>348</td>\n",
+              "      <td>363</td>\n",
+              "      <td>435</td>\n",
+              "      <td>491</td>\n",
+              "      <td>505</td>\n",
+              "      <td>404</td>\n",
+              "      <td>359</td>\n",
+              "      <td>310</td>\n",
+              "      <td>337</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1959</th>\n",
+              "      <td>360</td>\n",
+              "      <td>342</td>\n",
+              "      <td>406</td>\n",
+              "      <td>396</td>\n",
+              "      <td>420</td>\n",
+              "      <td>472</td>\n",
+              "      <td>548</td>\n",
+              "      <td>559</td>\n",
+              "      <td>463</td>\n",
+              "      <td>407</td>\n",
+              "      <td>362</td>\n",
+              "      <td>405</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1960</th>\n",
+              "      <td>417</td>\n",
+              "      <td>391</td>\n",
+              "      <td>419</td>\n",
+              "      <td>461</td>\n",
+              "      <td>472</td>\n",
+              "      <td>535</td>\n",
+              "      <td>622</td>\n",
+              "      <td>606</td>\n",
+              "      <td>508</td>\n",
+              "      <td>461</td>\n",
+              "      <td>390</td>\n",
+              "      <td>432</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "month  January  February  March  April  ...  September  October  November  December\n",
+              "year                                    ...                                        \n",
+              "1949       112       118    132    129  ...        136      119       104       118\n",
+              "1950       115       126    141    135  ...        158      133       114       140\n",
+              "1951       145       150    178    163  ...        184      162       146       166\n",
+              "1952       171       180    193    181  ...        209      191       172       194\n",
+              "1953       196       196    236    235  ...        237      211       180       201\n",
+              "1954       204       188    235    227  ...        259      229       203       229\n",
+              "1955       242       233    267    269  ...        312      274       237       278\n",
+              "1956       284       277    317    313  ...        355      306       271       306\n",
+              "1957       315       301    356    348  ...        404      347       305       336\n",
+              "1958       340       318    362    348  ...        404      359       310       337\n",
+              "1959       360       342    406    396  ...        463      407       362       405\n",
+              "1960       417       391    419    461  ...        508      461       390       432\n",
+              "\n",
+              "[12 rows x 12 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 61
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mnOuqL9K0dqh",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Join Data Stretch Challenge\n",
+        "\n",
+        "The [Instacart blog post](https://tech.instacart.com/3-million-instacart-orders-open-sourced-d40d29ead6f2) has a visualization of \"**Popular products** purchased earliest in the day (green) and latest in the day (red).\" \n",
+        "\n",
+        "The post says,\n",
+        "\n",
+        "> \"We can also see the time of day that users purchase specific products.\n",
+        "\n",
+        "> Healthier snacks and staples tend to be purchased earlier in the day, whereas ice cream (especially Half Baked and The Tonight Dough) are far more popular when customers are ordering in the evening.\n",
+        "\n",
+        "> **In fact, of the top 25 latest ordered products, the first 24 are ice cream! The last one, of course, is a frozen pizza.**\"\n",
+        "\n",
+        "Your challenge is to reproduce the list of the top 25 latest ordered popular products.\n",
+        "\n",
+        "We'll define \"popular products\" as products with more than 2,900 orders.\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "B-QNMrVkYap4",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "##### YOUR CODE HERE #####"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Ij8S60q0YXxo",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Reshape Data Stretch Challenge\n",
+        "\n",
+        "_Try whatever sounds most interesting to you!_\n",
+        "\n",
+        "- Replicate more of Instacart's visualization showing \"Hour of Day Ordered\" vs \"Percent of Orders by Product\"\n",
+        "- Replicate parts of the other visualization from [Instacart's blog post](https://tech.instacart.com/3-million-instacart-orders-open-sourced-d40d29ead6f2), showing \"Number of Purchases\" vs \"Percent Reorder Purchases\"\n",
+        "- Get the most recent order for each user in Instacart's dataset. This is a useful baseline when [predicting a user's next order](https://www.kaggle.com/c/instacart-market-basket-analysis)\n",
+        "- Replicate parts of the blog post linked at the top of this notebook: [Modern Pandas, Part 5: Tidy Data](https://tomaugspurger.github.io/modern-5-tidy.html)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "_d6IA2R0YXFY",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "##### YOUR CODE HERE #####"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file

From 5d0a0cdf8d71c834fcabec3fc434d15b6ed0e270 Mon Sep 17 00:00:00 2001
From: b-whitman <53320120+b-whitman@users.noreply.github.com>
Date: Wed, 9 Oct 2019 00:04:10 -0400
Subject: [PATCH 9/9] Created using Colaboratory

---
 ...ion_to_Bayesian_Inference_Assignment.ipynb | 1084 +++++++++++++++++
 1 file changed, 1084 insertions(+)
 create mode 100644 module3-introduction-to-bayesian-inference/Ben_Whitman_LS_DS_133_Introduction_to_Bayesian_Inference_Assignment.ipynb

diff --git a/module3-introduction-to-bayesian-inference/Ben_Whitman_LS_DS_133_Introduction_to_Bayesian_Inference_Assignment.ipynb b/module3-introduction-to-bayesian-inference/Ben_Whitman_LS_DS_133_Introduction_to_Bayesian_Inference_Assignment.ipynb
new file mode 100644
index 00000000..608ca2b4
--- /dev/null
+++ b/module3-introduction-to-bayesian-inference/Ben_Whitman_LS_DS_133_Introduction_to_Bayesian_Inference_Assignment.ipynb
@@ -0,0 +1,1084 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Ben_Whitman_LS_DS_133_Introduction_to_Bayesian_Inference_Assignment.ipynb",
+      "provenance": [],
+      "collapsed_sections": [],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/b-whitman/DS-Unit-1-Sprint-1-Dealing-With-Data/blob/master/module3-introduction-to-bayesian-inference/Ben_Whitman_LS_DS_133_Introduction_to_Bayesian_Inference_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "H7OLbevlbd_Z",
+        "colab_type": "text"
+      },
+      "source": [
+        "# Lambda School Data Science Module 133\n",
+        "\n",
+        "## Introduction to Bayesian Inference\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "P-DzzRk5bf0z",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Assignment - Code it up!\n",
+        "\n",
+        "Most of the above was pure math - now write Python code to reproduce the results! This is purposefully open ended - you'll have to think about how you should represent probabilities and events. You can and should look things up, and as a stretch goal - refactor your code into helpful reusable functions!\n",
+        "\n",
+        "Specific goals/targets:\n",
+        "\n",
+        "1. Write a function `def prob_drunk_given_positive(prob_drunk_prior, prob_positive, prob_positive_drunk)` that reproduces the example from lecture, and use it to calculate and visualize a range of situations\n",
+        "2. Explore `scipy.stats.bayes_mvs` - read its documentation, and experiment with it on data you've tested in other ways earlier this week\n",
+        "3. Create a visualization comparing the results of a Bayesian approach to a traditional/frequentist approach\n",
+        "4. In your own words, summarize the difference between Bayesian and Frequentist statistics\n",
+        "\n",
+        "If you're unsure where to start, check out [this blog post of Bayes theorem with Python](https://dataconomy.com/2015/02/introduction-to-bayes-theorem-with-python/) - you could and should create something similar!\n",
+        "\n",
+        "Stretch goals:\n",
+        "\n",
+        "- Apply a Bayesian technique to a problem you previously worked (in an assignment or project work) on from a frequentist (standard) perspective\n",
+        "- Check out [PyMC3](https://docs.pymc.io/) (note this goes beyond hypothesis tests into modeling) - read the guides and work through some examples\n",
+        "- Take PyMC3 further - see if you can build something with it!"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zCX4FVvPrm1F",
+        "colab_type": "text"
+      },
+      "source": [
+        "## 1) Using a function to apply Bayes"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "xpVhZyUnbf7o",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "def prob_drunk_given_positive(prob_drunk_prior, prob_positive, prob_positive_drunk):\n",
+        "  return (prob_positive_drunk*prob_drunk_prior) / prob_positive"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "eOglz53nOch8",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "efb1516f-4717-4415-c91b-a652a82556b8"
+      },
+      "source": [
+        "# Example from lecture\n",
+        "prob_drunk_given_positive(0.001, 0.08, 1)"
+      ],
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.0125"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 2
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "RNEYx0IoO-sP",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "62b28cc0-e2f4-43e6-f249-4ec3473f31bf"
+      },
+      "source": [
+        "# What if test gives half as many false positives?\n",
+        "prob_drunk_given_positive(0.001, 0.04, 1)\n",
+        "# Looks like that just doubles the rate, to 2.5%"
+      ],
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.025"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 3
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "7nS9h1CRQBGa",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "7d2aae4f-0585-45bb-b2a3-d809f60e0392"
+      },
+      "source": [
+        "# What if test gives 1% false positives?\n",
+        "prob_drunk_given_positive(0.001, 0.01, 1)\n",
+        "# Raises probability of true positive to 10%"
+      ],
+      "execution_count": 13,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.1"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 13
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "awElFbyNQ0Gv",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "66231334-18ad-48cb-f187-62a93a2addc2"
+      },
+      "source": [
+        "# To use another example from lecture, what if we conduct the test twice in a row?\n",
+        "# 0.08 * 0.08 = 0.0064\n",
+        "prob_drunk_given_positive(0.001, 0.0064, 1)\n",
+        "# Am I doing this right? Does it really only raise the probability to ~16%?\n",
+        "# Or am I failing to tease out something in the structure of Bayes' Theorem?"
+      ],
+      "execution_count": 16,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.15625"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 16
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "CoRfzsl2U33B",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "5d900edf-386c-4d7b-e6b1-428b75f4a6ad"
+      },
+      "source": [
+        "# Okay, what if we use the previous posterior as our new prior? (per the drug testing example)\n",
+        "prob_drunk_given_positive(0.0125, 0.08, 1)\n",
+        "# So that's pretty interesting- exactly the same result as just multiplying\n",
+        "# the probability of a positive...\n",
+        "# I still suspect I'm missing something. Shouldn't the math for rate of all positives\n",
+        "# change given the new prior?"
+      ],
+      "execution_count": 18,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.15625"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 18
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "jW0CHL6wb0XH",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "bd4082a2-1f3a-4928-e0f1-93663d4e688d"
+      },
+      "source": [
+        "# This gives a slightly different answer but I feel more confident about the math\n",
+        "two_tests = prob_drunk_given_positive(0.0125, (1*0.0125+0.08*0.9875), 1)\n",
+        "two_tests"
+      ],
+      "execution_count": 22,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.1366120218579235"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 22
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Kxeg7ktDcbUy",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "a427a083-27ac-4bfd-d435-63b659e18790"
+      },
+      "source": [
+        "# Three tests...\n",
+        "three_tests = prob_drunk_given_positive(two_tests, (1*two_tests+0.08*(1-two_tests)), 1)\n",
+        "three_tests"
+      ],
+      "execution_count": 24,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.6641870350690755"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 24
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "gN_UuYSzc2gc",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "c010718d-9267-412d-d590-d38e878f14c2"
+      },
+      "source": [
+        "# Four tests???\n",
+        "four_tests = prob_drunk_given_positive(three_tests, (1*three_tests+0.08*(1-three_tests)), 1)\n",
+        "four_tests"
+      ],
+      "execution_count": 26,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.9611244387033278"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 26
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "8Gdb3W--dEjP",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "37acaa2f-9ee2-47f8-c42a-9d918e7c80a0"
+      },
+      "source": [
+        "# Five tests...?!\n",
+        "five_tests = prob_drunk_given_positive(four_tests, (1*four_tests+0.08*(1-four_tests)), 1)\n",
+        "five_tests"
+      ],
+      "execution_count": 28,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.9967745968884046"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 28
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "mVlohdTWdRF7",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "b421cb67-a96e-41b2-d201-b8171c35e69f"
+      },
+      "source": [
+        "# Have we hit a limit?\n",
+        "six_tests = prob_drunk_given_positive(five_tests, (1*five_tests+0.08*(1-five_tests)), 1)\n",
+        "six_tests"
+      ],
+      "execution_count": 29,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "0.9997411997948845"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 29
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "zwcZ-Ki4fWI9",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# This function applies Bayes Theorem num_iter times to the breathalyzer problem\n",
+        "def prob_drunk_iter(prior, prob_positive, prob_positive_drunk, num_iter):\n",
+        "  posterior_list = []\n",
+        "  for i in range(num_iter):\n",
+        "    posterior = (prob_positive_drunk*prior) / prob_positive\n",
+        "    prior = posterior\n",
+        "    prob_positive = (1*prior+0.08*(1-prior))\n",
+        "    posterior_list.append(posterior)\n",
+        "  return posterior_list"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "S8tBDeJgi8Q8",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "5238806f-840e-47ca-9bc7-13217fa3fb45"
+      },
+      "source": [
+        "prob_drunk_five = prob_drunk_iter(0.001, 0.08, 1, 5)\n",
+        "plt.plot(prob_drunk_five)"
+      ],
+      "execution_count": 41,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[<matplotlib.lines.Line2D at 0x7f1a7bce0cc0>]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 41
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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M4oAO1L2xKiIiHvCn3JcAA82sn5klADOBRY2WWQT8X/3tGcC7wZhvFxER/zT7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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "cC920DifhdNY",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 191
+        },
+        "outputId": "277b74ef-0952-4758-fc9b-82946119969d"
+      },
+      "source": [
+        "prob_drunk_list = prob_drunk_iter(0.001, 0.08, 1, 10)\n",
+        "prob_drunk_list"
+      ],
+      "execution_count": 35,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[0.0125,\n",
+              " 0.1366120218579235,\n",
+              " 0.6641870350690755,\n",
+              " 0.9611244387033278,\n",
+              " 0.9967745968884046,\n",
+              " 0.9997411997948845,\n",
+              " 0.9999792910528694,\n",
+              " 0.9999983432526648,\n",
+              " 0.9999998674600111,\n",
+              " 0.9999999893967996]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 35
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "UMIEEKUchxbI",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "691713ad-233e-498f-b054-138ea10174b5"
+      },
+      "source": [
+        "import matplotlib.pyplot as plt\n",
+        "# Plot for 10 repetitions of test\n",
+        "plt.plot(prob_drunk_list)"
+      ],
+      "execution_count": 36,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[<matplotlib.lines.Line2D at 0x7f1a7e8c5a58>]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 36
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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qY+nCUrKyNCUjIiOjck8Rv9vURmd3VNduF5GEULmniOraCCcV5LKkYlLQUUQkBFTuKaCr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\nAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "eHB0wdFQiY0E",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 364
+        },
+        "outputId": "f752ec5e-2e9f-4d8a-fe69-325c8e1e879c"
+      },
+      "source": [
+        "prob_drunk_twenty = prob_drunk_iter(0.001, 0.08, 1, 20)\n",
+        "prob_drunk_twenty"
+      ],
+      "execution_count": 38,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[0.0125,\n",
+              " 0.1366120218579235,\n",
+              " 0.6641870350690755,\n",
+              " 0.9611244387033278,\n",
+              " 0.9967745968884046,\n",
+              " 0.9997411997948845,\n",
+              " 0.9999792910528694,\n",
+              " 0.9999983432526648,\n",
+              " 0.9999998674600111,\n",
+              " 0.9999999893967996,\n",
+              " 0.999999999151744,\n",
+              " 0.9999999999321395,\n",
+              " 0.9999999999945711,\n",
+              " 0.9999999999995657,\n",
+              " 0.9999999999999653,\n",
+              " 0.9999999999999972,\n",
+              " 0.9999999999999998,\n",
+              " 1.0,\n",
+              " 1.0,\n",
+              " 1.0]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 38
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "YSfIE8w1ikUo",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "outputId": "3f092b9c-9144-4e80-ff66-18218fbb4dea"
+      },
+      "source": [
+        "plt.plot(prob_drunk_twenty)\n",
+        "# Plot for 20 reps\n",
+        "# Seems to hit a limit around 5 reps"
+      ],
+      "execution_count": 39,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[<matplotlib.lines.Line2D at 0x7f1a7bcf37f0>]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 39
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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IxILCPXD4zCUGh12DqSISCwr3wI9vradwF5HoU7gHRm+KraUHRCQOFO6BZLqPBbPrWTCn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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "t4NO2icVkXD_",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import scipy.stats as stats\n",
+        "stats.bayes_mvs?"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "h3Rk428Sqg7S",
+        "colab_type": "text"
+      },
+      "source": [
+        "## 2) Scipy.Stats.bayes_mvs"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Rli4pX3wqlPv",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 208
+        },
+        "outputId": "2585cb0a-3a69-45e9-e2b4-a727f0987b9f"
+      },
+      "source": [
+        "!wget https://archive.ics.uci.edu/ml/machine-learning-databases/voting-records/house-votes-84.data"
+      ],
+      "execution_count": 44,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "--2019-10-09 03:57:22--  https://archive.ics.uci.edu/ml/machine-learning-databases/voting-records/house-votes-84.data\n",
+            "Resolving archive.ics.uci.edu (archive.ics.uci.edu)... 128.195.10.252\n",
+            "Connecting to archive.ics.uci.edu (archive.ics.uci.edu)|128.195.10.252|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 18171 (18K) [application/x-httpd-php]\n",
+            "Saving to: ‘house-votes-84.data’\n",
+            "\n",
+            "\rhouse-votes-84.data   0%[                    ]       0  --.-KB/s               \rhouse-votes-84.data 100%[===================>]  17.75K  --.-KB/s    in 0.03s   \n",
+            "\n",
+            "2019-10-09 03:57:22 (628 KB/s) - ‘house-votes-84.data’ saved [18171/18171]\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "ZsGi157sqtQM",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np"
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "GSfspPX5qrGZ",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 274
+        },
+        "outputId": "49c5ba70-56ea-4cde-cf0a-1dfe0e4f674e"
+      },
+      "source": [
+        "df_cols = ['party',\n",
+        "           'handicapped_infants',\n",
+        "           'water-project-cost-sharing',\n",
+        "           'adoption-of-the-budget-resolution',\n",
+        "           'physician-fee-freeze',\n",
+        "           'el-salvador-aid',\n",
+        "           'religious-groups-in-schools',\n",
+        "           'anti-satellite-test-ban',\n",
+        "           'aid-to-nicaraguan-contras',\n",
+        "           'mx-missile',\n",
+        "           'immigration',\n",
+        "           'synfuels-corporation-cutback',\n",
+        "           'education-spending',\n",
+        "           'superfund-right-to-sue',\n",
+        "           'crime',\n",
+        "           'duty-free-exports',\n",
+        "           'export-administration-act-south-africa']\n",
+        "df = pd.read_csv('house-votes-84.data', names=df_cols)\n",
+        "replace_dict = {'?': np.nan, 'y': 1, 'n': 0}\n",
+        "df = df.replace(replace_dict)\n",
+        "df.head()"
+      ],
+      "execution_count": 49,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>party</th>\n",
+              "      <th>handicapped_infants</th>\n",
+              "      <th>water-project-cost-sharing</th>\n",
+              "      <th>adoption-of-the-budget-resolution</th>\n",
+              "      <th>physician-fee-freeze</th>\n",
+              "      <th>el-salvador-aid</th>\n",
+              "      <th>religious-groups-in-schools</th>\n",
+              "      <th>anti-satellite-test-ban</th>\n",
+              "      <th>aid-to-nicaraguan-contras</th>\n",
+              "      <th>mx-missile</th>\n",
+              "      <th>immigration</th>\n",
+              "      <th>synfuels-corporation-cutback</th>\n",
+              "      <th>education-spending</th>\n",
+              "      <th>superfund-right-to-sue</th>\n",
+              "      <th>crime</th>\n",
+              "      <th>duty-free-exports</th>\n",
+              "      <th>export-administration-act-south-africa</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>republican</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>republican</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>democrat</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>democrat</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>democrat</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "        party  ...  export-administration-act-south-africa\n",
+              "0  republican  ...                                     1.0\n",
+              "1  republican  ...                                     NaN\n",
+              "2    democrat  ...                                     0.0\n",
+              "3    democrat  ...                                     1.0\n",
+              "4    democrat  ...                                     1.0\n",
+              "\n",
+              "[5 rows x 17 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 49
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "8yPZDLmVqzJX",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "322653e6-af67-4359-903e-f160c7b26612"
+      },
+      "source": [
+        "mean, var, std = stats.bayes_mvs(df['water-project-cost-sharing'].dropna())\n",
+        "mean"
+      ],
+      "execution_count": 52,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Mean(statistic=0.5038759689922481, minmax=(0.4619161006559928, 0.5458358373285033))"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 52
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "2ZEDTt3IrKBK",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "91c1379b-5824-4ae7-d12a-c7c9e76fcc51"
+      },
+      "source": [
+        "var"
+      ],
+      "execution_count": 53,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Variance(statistic=0.25193798449612403, minmax=(0.22352548228908597, 0.2833227081716581))"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 53
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "-qTyHxCrrLWv",
+        "colab_type": "code",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "outputId": "3c4db49c-94d6-4bf9-cf8b-08d0f3062c20"
+      },
+      "source": [
+        "std"
+      ],
+      "execution_count": 54,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Std_dev(statistic=0.5016075698129333, minmax=(0.4727848160517489, 0.5322806667272991))"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 54
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "t_m-wniFrOiQ",
+        "colab_type": "code",
+        "colab": {}
+      },
+      "source": [
+        "# I'm not sure if I've done this part correctly, and if I have I don't think I\n",
+        "# understand it..."
+      ],
+      "execution_count": 0,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "k5wwj6J7ruV_",
+        "colab_type": "text"
+      },
+      "source": [
+        "## 3) Comparing Bayesian approach to standard approach"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zAt6x_hZS5ye",
+        "colab_type": "text"
+      },
+      "source": [
+        "## 4) Bayesian and Frequentist Statistics\n",
+        "\n",
+        "The difference between Bayesian and Frequentist statistics lies in how they conceive of probability.\n",
+        "\n",
+        "Frequentist stats conceives of probability as a rate of occurrence.\n",
+        "\n",
+        "Bayesian stats conceives of probability as a degree of belief in an event."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "uWgWjp3PQ3Sq",
+        "colab_type": "text"
+      },
+      "source": [
+        "## Resources"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "QRgHqmYIQ9qn",
+        "colab_type": "text"
+      },
+      "source": [
+        "- [Worked example of Bayes rule calculation](https://en.wikipedia.org/wiki/Bayes'_theorem#Examples) (helpful as it fully breaks out the denominator)\n",
+        "- [Source code for mvsdist in scipy](https://github.com/scipy/scipy/blob/90534919e139d2a81c24bf08341734ff41a3db12/scipy/stats/morestats.py#L139)"
+      ]
+    }
+  ]
+}
\ No newline at end of file