diff --git a/consumer_complaints.ipynb b/consumer_complaints.ipynb
new file mode 100644
index 0000000..409ac99
--- /dev/null
+++ b/consumer_complaints.ipynb
@@ -0,0 +1,507 @@
+{
+ "metadata": {
+  "name": "",
+  "signature": "sha256:00fcce0da454887cc257170202385cd47eff1019aa8c85abea3cfce2b86511ac"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "import pandas as pd\n",
+      "import numpy as np\n",
+      "import matplotlib.pyplot as plt\n",
+      "import matplotlib.cm as cm\n",
+      "import seaborn as sb\n",
+      "from scipy.misc import imread"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 163
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "%matplotlib inline"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 110
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "cc_data = pd.read_csv(\"complaints_dec_2014.csv\")"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 111
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "complaints_by_product = cc_data[\"Product\"]\n",
+      "complaint_by_product_counts = complaints_by_product.value_counts()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 112
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "print(complaint_by_product_counts)\n",
+      "complaint_by_product_counts.plot(kind=\"bar\", color=\"green\")\n",
+      "plt.gcf().set_size_inches(10,8)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "Mortgage                   3002\n",
+        "Debt collection            2942\n",
+        "Credit reporting           2113\n",
+        "Bank account or service    1136\n",
+        "Credit card                1100\n",
+        "Consumer loan               578\n",
+        "Student loan                340\n",
+        "Payday loan                 141\n",
+        "Money transfers             107\n",
+        "Prepaid card                 70\n",
+        "Other financial service      14\n",
+        "dtype: int64\n"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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UgSFLkiSpAkOWJElSBbM25qSIeCxwXGY+JSJ2B74CXNN8+aOZeWZEvBo4GFgNHJ2Z50TE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\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10f3a6668>"
+       ]
+      }
+     ],
+     "prompt_number": 113
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "complaints_by_company = cc_data[\"Company\"]\n",
+      "complaint_by_company_counts = complaints_by_company.value_counts()[:10]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 114
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "print(complaint_by_company_counts)\n",
+      "complaint_by_company_counts.plot(kind=\"bar\", color=\"purple\")\n",
+      "plt.gcf().set_size_inches(10,8)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "Bank of America        766\n",
+        "Equifax                737\n",
+        "Experian               675\n",
+        "TransUnion             604\n",
+        "Wells Fargo            598\n",
+        "JPMorgan Chase         545\n",
+        "Ocwen                  408\n",
+        "Citibank               403\n",
+        "Nationstar Mortgage    357\n",
+        "Capital One            252\n",
+        "dtype: int64\n"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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0P0y9C/hL4LOU7upLtv/0ofN64Hczc23zxvdxYPIdGofPdZQ38Xt2XMdM2QP4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\ngg==\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10f3a6550>"
+       ]
+      }
+     ],
+     "prompt_number": 115
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "complaints_by_response = cc_data[\"Company response\"]\n",
+      "complaint_by_response_counts = complaints_by_response.value_counts()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 116
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "print(complaint_by_response_counts)\n",
+      "complaint_by_response_counts.plot(kind=\"bar\", color=\"orange\")\n",
+      "plt.gcf().set_size_inches(10,8)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "Closed with explanation            8185\n",
+        "Closed with non-monetary relief    1253\n",
+        "In progress                        1056\n",
+        "Closed with monetary relief         643\n",
+        "Closed                              239\n",
+        "Untimely response                   167\n",
+        "dtype: int64\n"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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IkiRJKsCQJUmSVIAhS5IkqQBDliRJUgGGLEmSpAIMWZIkSQUYsiRJkgowZEmSJBVgyJIk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\n1WlKOwrOUAAAAABJRU5ErkJggg==\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10f377a90>"
+       ]
+      }
+     ],
+     "prompt_number": 117
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "dates = cc_data[\"Date received\"]\n",
+      "list_dates = dates.unique()\n",
+      "date_time_list = pd.Series([pd.to_datetime(date, format=\"%m/%d/%Y\").dayofweek for date in list_dates])\n",
+      "list_of_days_in_month = np.unique(np.array(date_time_list), return_counts=True)[1]\n",
+      "date_complaints = pd.Series([pd.to_datetime(date, format=\"%m/%d/%Y\").dayofweek for date in dates])\n",
+      "count_of_complaints_by_day = np.unique(np.array(date_complaints), return_counts=True)[1]\n",
+      "mean_complaints_per_day = count_of_complaints_by_day / list_of_days_in_month"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 118
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "data_to_graph = pd.Series(mean_complaints_per_day)\n",
+      "data_to_graph.plot(kind=\"bar\", color=\"red\")\n",
+      "plt.xticks([0, 1, 2, 3, 4, 5, 6], [\"Monday\", \"Tuesday\", \"Wednesday\", \"Thursday\", \"Friday\", \"Saturday\", \"Sunday\"])\n",
+      "plt.gcf().set_size_inches(10,8)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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7V5KvT3JXkmu6+44kd1TVDUnOTPLh5ZcMALB5HDRMdfenk6SqtmcKVq9O8mNrdrktycOS\nnJzklgNsBwA4qh3qyFSq6tQkv5LkDd391qr692sePjnJp5LcmmT7mu3bk+w5WLunnHJStmw57vAr\nPoA9e7YtpZ0jaceObdm5c/uhd5yB/huj/zZO343Rf5vTg+33XaZV7btDTUD/35K8N8m/7O73LTb/\nflU9o7uvTnJ+kquSXJvkkqo6IcmJSR6faXL6/dqz5zOjtX/O7t23Z8fSWjsydu++PTfffNvcZRyQ\n/huj/zZO343Rf5vPzp3bH1S/7zJt9r47WNA71JGpizIN1/1gVf3gYtuFSV6/mGB+fZIrF2fzvT7J\nBzPNrbqou/cOVw4AsMkdas7UhZnC032de4B9L09y+XLKAgBYDRbtBAAYIEwBAAwQpgAABghTAAAD\nhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUA\nMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghT\nAAADhCkAgAHCFADAAGEKAGCAMAUAMECYAgAYIEwBAAwQpgAABghTAAADhCkAgAHCFADAAGEKAGCA\nMAUAMECYAgAYIEwBAAwQpgAABmyZuwAAmMPevXuza9dNS21zz55t2b379qW1d+qpp2Xr1q1La48j\nQ5gC4EFp166bcsvZZ+X0Jbe7Y0nt3JgkH7ouZ5zx2CW1yJEiTAHwoHV6ksfNXcRB7J67ANbFnCkA\ngAHCFADAAGEKAGCAMAUAMMAEdADgsC17aYlVXlZCmAIADtuRWFpiVZeVEKYAgA3ZzEtLPJDLSpgz\nBQAwQJgCABggTAEADBCmAAAGCFMAAAOEKQCAAcIUAMAAYQoAYIAwBQAwQJgCABggTAEADBCmAAAG\nCFMAAAO2rGenqvqHSV7b3c+sqr+f5Iokdyf5aJJXdPe+qnpZkguS3Jnk4u5+5xGqGQBg0zjkkamq\n+j+TXJbkhMWmH09yUXc/PckxSZ5fVY9I8sok5yQ5L8mlVbX1yJQMALB5rGeY74Yk35gpOCXJk7r7\nA4vb70ry7CRPTnJNd9/R3bcu/s6Zyy4WAGCzOWSY6u5fyTR0t98xa27fluRhSU5OcssBtgMAHNU2\nMgH97jW3T07yqSS3Jtm+Zvv2JHsG6gIAWAnrmoB+H79fVc/o7quTnJ/kqiTXJrmkqk5IcmKSx2ea\nnH6/TjnlpGzZctwG/vnPt2fPtqW0cyTt2LEtO3duP/SOM9B/Y/Tfxum7MfpvjP4bs9n774Hsu8MJ\nU/sWP78nyWWLCebXJ7lycTbf65N8MNPRrou6e+/BGtuz5zMbqfeAdu++PTuW1tqRsXv37bn55tvm\nLuOA9N8Y/bdx+m6M/huj/8Zs9v5bdt8dLJitK0x1959nOlMv3f3xJOceYJ/Lk1y+kQIBAFaVRTsB\nAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABh\nCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAM\nEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQA\nwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBM\nAQAMEKYAAAYIUwAAA4QpAIABwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIAB\nwhQAwABhCgBggDAFADBAmAIAGCBMAQAMEKYAAAYIUwAAA4QpAIABW5bZWFUdm+SNSc5M8r+SfGd3\nf2KZ/wYAwGay7CNT35Bka3efk+TfJHndktsHANhUlh2mvibJu5Oku383yVctuX0AgE1lqcN8SU5O\ncuua+3dV1bHdffd9dzzrrC87YAPXXffRA24/1P433mf7195Pgf/9frYfyf1vTPLif/K8HH/88Z/3\n2EZ/32Xuf8cdd+TuJMdnnv451P43JnnYfbY/kP2znv2flqn/7msz9OcdSY5dPP82w/NtrV/+5bd/\n3ms32Tyv3/3Pvc32fNu//9rXbrI5nm9r/Ww+/7WbbK7+vDGb5/l23/3XvnaT+Z9v97WZX79rPzeW\n9fv+xV/cdD//cnLMvn377vfBw1VVr0vyO939tsX9Xd196tL+AQCATWbZw3zXJHluklTVU5J8ZMnt\nAwBsKsse5nt7kq+rqmsW91+y5PYBADaVpQ7zAQA82Fi0EwBggDAFADBAmAIAGCBMAQAMEKbWqKo3\nVNVXzF3HKqqqrXPXAGxMVf16VX1DVR03dy2rpqoeMXcNzM/ZfGtU1flJXprk0Un+c5K3dPetB/9b\nJElVfSTTArSXd/eBl5XlflXVrye5PMmvdfddc9ezavTfmKp6fKb3vq9L8p4kP9vdfzpvVathsRTQ\nzZmef79xoCt+cP+q6sNJfjHJL3T37rnr2Shh6gCqameSn0jy/CRvS/LD3f2Jeava3BbfaJ+T5MVJ\ndiZ5S5K3dvftc9a1KnyYjdF/y1FVD0/yk0m+MckHkvxgd39o3qo2v6p6Yqb3vqcluSrT8+/PZi1q\nRVTVKUn++eLPrkx995vzVnX4hKk1quoJSb49yT9O8r4klyU5Lsmbu/tJc9a2Cqrq2CTnJXlZkjOS\n3J7kv3T3T85a2ArxYTZG/21MVT0303vfEzIdlb8i03vfe7r7zBlLWwlV9QVJXpDkm3PP9Wk/1t3f\nN19Vq2XxhegHkzwryZ8neW13/8qsRR2GZa+AvurenOlQ7Wu6+9P7N1bVz81X0mqoqn+f5BuSXJ3p\nRXDtIlxdl+nDjYM4wIfZhVl8mCXxYXYI+m/YC5O8qbvfv3ZjVf3QLNWskKr65SRfnmmo6oXd/VeL\n7R+etbAVUVX/Msm3Jbkt0wGMb8uUTX43iTC1irr7qVX1qCRfuPiG+6ju/lB3/9Tcta2Ajyd50tph\nve6+u6q+ccaaVokPszH6b8yLkzy5qp6e5JhM731vXaUjAzO67H6GpZ72gFeymh6d5AXdfeOabXdU\n1cvnKmgjDPOtsTgC9ZQk25I8JMnvdvfz5q1qNVTVY5N8U6aAfmySR3b3d81b1eqoquOTPDlT/33u\nw2zeqlaH/huzmMC/JckXZ3r9/l53f+u8Va2Gqjo703Vo1773nTdvVaujqr4w0/SQtf136bxVHT5L\nI9zbP0jyZUnenWm4wJl86/dLSfYleWqSL8l0yJb1e3um+QJvTPKmJP/7vOWsHP035uHd/Zwkv5Pk\nq5KcNHM9q+RNmebYPizTXJ/fnbWa1fP2JE9P8vIkL0py6rzlbIwwdW9/uzitdVt335zE+iHrd/vi\n28RfdveLk3zpzPWsGh9mY/TfmE9X1TGZ3vs+k+Thcxe0Qj65OAp6W3f/UKbnH+t3THe/PMnHknx9\npqOjK0eYurfrqupfJ/mrqvovmYb7WJ+7q+qRSbZV1UOTPGruglaMD7Mx+m/M25P8QJI/rKrfSXLH\nzPWskruq6suSPKSqvjQremRlRndU1UMyfd7eneSLZq5nQ0xAX6O7X1VV25N8Nsn5Sa6duaRV8ppM\nZ/P9YpI/W/xk/e77YfbpQ+zPvem/Ad39U1V1THfvW8yfumHumlbI92SaFvKTmdbXc/b34Xljku9O\n8t5M60xdM285G2MCepKq+reLm/syTV7db193v2aGkngQWvNh9uVJbujuz85d0yrRf4evqn7+fh7a\n190vfUCL4UGvqk5e1auOODI1+ePFz29L8keZFvs7O9O3DQ6iqv5ocfO4JFszXVbh4Ul2d/c/nK2w\nFXHfD7Oq2n9zX6YVvTkI/TfsDYuf/zrJb+We975nzlbRiljz3ndypsnnf5LkcUn+urufOFthK6Kq\n3nc/2/d199c+0PWMEqaSdPeVSVJVF3T39y82v6eqfmvGslZCd3958rkPtdd2d1fVGUn+r3krWxk+\nzMbovwHd/eFkOj29uy/bv7mqXjRjWSthzXvf25L8i+7+5OLSKIb51uebFj9/LNPw6AczLU30z2ar\naIAwdW9fUFWP7e6PL661ZAL6+p3R3Z0k3f2JqvqSmetZCT7Mxui/pXlIVT0ryf+TaXmT42auZ5Wc\n2t2fTJLu3rNY+JlD2N9nVXXamkVP37+qC+0KU/f23UmurKpHJPnLJN85cz2r5JNV9cNJPpzka5Lc\nNHM9q8aH2Rj9N+alSX40SSW5PtOK6KzPR6rqFzM9985J4lqQh+euqvqO3PPaXcmTR4SpNbr7f2Ra\nuJPD962ZFl17bqY34x+Yt5yV48NsjP7bgKo6vrvvSHJj7hl2SaY5Z6zPv0lybqbn3i9196/OW87K\neWGS7890kejrMy3cuXKEqTWq6tszvTBOXGza192PmbGkVXJskrdlWp/mgkwLnjo6tU6LuWb/JFM/\nnp3kr2YuaaXovw37hSQvSNL32b4vife+9XlHdz917iJWVXf/TVVdkns+d7cl2T1jSRsiTN3b9yX5\nR0n+37kLWUFXZrqswj/NdHbkmzNdb4l1qKqfyHQ20GlJvjLJ3yT59lmLWiH6b2O6+wWLmz/Q3daG\n25jdVXVhpkC6L9OX8PfOXNPKqKo3ZhrR+J9rNp89UzkbJkzd2ye622J1G3NSknckubC7X1RVz567\noBXz5O6+sKre393nVtVVcxe0YvTfmAtiod2N2p3kKxZ/9hOm1u+rkzxmcSm3lSVM3dtnq+rdSf4g\n93zDuGjmmlbF1iQXZrokzxOTPHTmelbNsVV1VpIbq+qEJNvnLmjF6L8xJ1TVH2Q6unJ3pve+fz5z\nTSthcS1SNu4TSR6SFZ14vp8wdW+/ERMvN+p7kjw/ySWZJqNfOG85K+cXMg2TviTJv0vyM/OWs3L0\n3wZU1au7++JMUxweleks5mPifXDdqmr/8NQxSXYk+bPudqH39ft7SW6qqhtyz0GMc2au6bAJU/f2\ni0m+K8kTM31D++l5y1kd3X3N4mKV35xp4cSPz1zSSunuN1bVW5J8SZJXd/ftM5e0ah7a3V+9uP3d\ns1ayWp6V5OLufn9Vva+7LXZ6mLr7kftvV9VpSX5ovmpW0kou0nlfx85dwCbz5iRnZBrvPj3JZQff\nnf2q6tJMl+O5IMlXxSrAh6Wq/mmS92cK9P+qql49b0Ur57lV5cshs+rum5I8fu46VsyL7/NnJU8c\n8eZzb4/t7qctbv+3qrL42vo9tbuftvh2+3NVdcHcBa2Yf5XpDJZ3JfmRJNcmuXjWilbLw5P8VVXd\nmHvm/KzcUAGrp6reuubuI5P89Vy1rKi/yTS8d2ySJ2VFD/IIU/d2QlU9tLs/XVUnZUX/U2dyXFWd\nmCRVdVySu2auZ9Xc1d1/V1Xp7juryjDf4Xne3AWsqLPWfGl8wprbwuj6/XSm+VJJ8neZrgLBOnX3\nvabTLE4CWznC1L39RJI/qKo/znSo9ofmLWel/Ick1yXZmemoyo/PW87K+e3FN9xHV9XPZLq0Auv3\n4vvc35fkNTPUsWrOnLuAVbUYVj4u08k2++f9HJdpmsjXzlXXqqmqx625+6hME9JXjjCVpKp+PtOb\n7zFJPpapXz6e5OuSvPUgf5WF7n5bVf1Wkr+f5Mb9F7Fkfbr7VVV1fpLfS/Kx7v61uWtaMUfFUMED\nrbv/fO4aVthLk7wq09Ue9q8gf3eSD85W0Wp6c6bX7o4kn8x0ZvjKOWbfPmfAVtVHMi06+ZYk/2Pt\nY939nlmKWjGLQLrWvu5+6SzFrKCqOjnJ+bn3pYx+YcaSVlpVvbu7nzN3HRz9quo7uvtn565j1VTV\nkzKdqPTVma488tNJ9iT53u5+x5y1bYQjU0m6+8yq+vJM6yN9X6ZvFv/ZauiH5b/m3kcGHjVvOSvn\nVzOt8bNr7kJW0dEyVMBK+kBVXZTp8/TYJI/s7u+auaZV8GNJvr2791bVxUmek2lE6N2ZrqaxUoSp\nhe7+o0xBKlX19CSvraov7u6nzFvZaujutZMG31VVvzlbMavpmO7+1rmLWGH7hwqSaRLwSg4VsJJ+\nKcmvJHk57A0LAAADw0lEQVRqpgtsm+KwPsd29x9W1aOTnNTd1yVJVa3kZWWEqTUWQy3fmGky4UPj\nWlXrVlXn5Z4Ps0cl+aIZy1lFH6mqpyT5/Sz6sbv3zlvS6ujuc+eugQet27v70qp6XHe/pKp+fe6C\nVsQdi5/nJfmtJKmq45Nsm62iAcJUkqr6lkwB6u8l+b+T/IvuvnHeqlZDVf3X7v6WJC/IvY8MmC91\neM7NNG9grdNnqGMlVdW/TfJ/JLlzsWlfdxtq5oFwd1U9Msm2qnpoTHFYr6uq6ppMn7v/uKoek+QN\nSX553rI2xgT0fO6w4seS/OF9HnKxz0NwCQo2g6r6cJKndfdn566FB5eqekaSJ2S6UO9/TPLz3W2Y\neR2q6glJbunuv6yqM5Kc2d1vn7uujXBkarJ/TZD9yfKY+9zn/j2mqn4k9/TZfvu6+6I5ClolVfW+\nxc39S3Pst6+7rVWzfv9f7jkqBUfcfc5G+8JMZ6N9MsnVc9a1Srr7+jW3P5HkEzOWM0SYStLd75+7\nhhX2mdyzxsp+rjq/ft+0+PljmZbm+GCSp+QoufjnkbbmUh5flOT3q+qjuefK844qcyStPRvtkkxL\nm6zs2WiMEaYY9dfd/Z/mLmJV7V/ctKpO6+79Z0C+v6p+aL6qVsqzMgXSzzsyOkMtPLgcVWejMUaY\nYtR1cxdwlLirqr4j03W9vibT/AsO7Y+727AKcziqzkZjjDDFkO7+3rlrOEq8MMn3J/nmJNcnedG8\n5awMc/aYy1F1NhpjhCnYBLr7b6rqHUnOSPKhTHPROLQDzdmDI667X7t4za49G+3Nq3o2GmMsjQCb\nQFVdmuTRSR6f5E1Jvq67XzBvVZufpTmAzcCV1WFzeGp3f1um1ZR/LhbsXC9z9oDZCVOwORxXVScm\nSVUdl+SumetZCebsAZuBMAUzqqozFzf/Q6ajLE9Mcm2SN85WFACHxZwpmFFVvT/T2UBXJ3lvkhuS\n3Lh//SkANj9hCma2GN47O8kzkjw102n+V3f3a2YtDIB1McwHM+vuv8s0xPeRxZ/jknzlrEUBsG6O\nTMGMqup7kzw3yRdkWkX5XUl+u7vvOOhfBGDTEKZgRlV1S6YLo16eaWhv78wlAXCYhCmYUVVtTfK0\nTFecf3qSv07yG0l+o7v/Ys7aAFgfYQo2kap6TqZr9J3T3cfNXQ8Ah+bafDCjqnpypiNTT0vypUn+\nMMkVSb51xrIAOAzCFMzr0iS/meSHk/xBd989cz0AHCbDfAAAA6wzBQAwQJgCABggTAEADBCmAAAG\nCFMAAAP+f5lXn4da8hmGAAAAAElFTkSuQmCC\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10f255978>"
+       ]
+      }
+     ],
+     "prompt_number": 119
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "pop_data = pd.read_csv(\"NST_EST2014_ALLDATA.csv\")"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 120
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "pop_data_by_state = pop_data[[\"NAME\", \"POPESTIMATE2014\"]][5:]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 121
+    },
+    {
+     "cell_type": "code",
+     "collapsed": true,
+     "input": [
+      "pop_data_by_state.index = pop_data_by_state.pop(\"NAME\")"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 122
+    },
+    {
+     "cell_type": "code",
+     "collapsed": true,
+     "input": [
+      "pop_data_by_state[\"POPESTIMATE2014\"]\n"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 123,
+       "text": [
+        "NAME\n",
+        "Alabama                  4849377\n",
+        "Alaska                    736732\n",
+        "Arizona                  6731484\n",
+        "Arkansas                 2966369\n",
+        "California              38802500\n",
+        "Colorado                 5355866\n",
+        "Connecticut              3596677\n",
+        "Delaware                  935614\n",
+        "District of Columbia      658893\n",
+        "Florida                 19893297\n",
+        "Georgia                 10097343\n",
+        "Hawaii                   1419561\n",
+        "Idaho                    1634464\n",
+        "Illinois                12880580\n",
+        "Indiana                  6596855\n",
+        "Iowa                     3107126\n",
+        "Kansas                   2904021\n",
+        "Kentucky                 4413457\n",
+        "Louisiana                4649676\n",
+        "Maine                    1330089\n",
+        "Maryland                 5976407\n",
+        "Massachusetts            6745408\n",
+        "Michigan                 9909877\n",
+        "Minnesota                5457173\n",
+        "Mississippi              2994079\n",
+        "Missouri                 6063589\n",
+        "Montana                  1023579\n",
+        "Nebraska                 1881503\n",
+        "Nevada                   2839099\n",
+        "New Hampshire            1326813\n",
+        "New Jersey               8938175\n",
+        "New Mexico               2085572\n",
+        "New York                19746227\n",
+        "North Carolina           9943964\n",
+        "North Dakota              739482\n",
+        "Ohio                    11594163\n",
+        "Oklahoma                 3878051\n",
+        "Oregon                   3970239\n",
+        "Pennsylvania            12787209\n",
+        "Rhode Island             1055173\n",
+        "South Carolina           4832482\n",
+        "South Dakota              853175\n",
+        "Tennessee                6549352\n",
+        "Texas                   26956958\n",
+        "Utah                     2942902\n",
+        "Vermont                   626562\n",
+        "Virginia                 8326289\n",
+        "Washington               7061530\n",
+        "West Virginia            1850326\n",
+        "Wisconsin                5757564\n",
+        "Wyoming                   584153\n",
+        "Puerto Rico              3548397\n",
+        "Name: POPESTIMATE2014, Length: 52, dtype: int64"
+       ]
+      }
+     ],
+     "prompt_number": 123
+    },
+    {
+     "cell_type": "code",
+     "collapsed": true,
+     "input": [
+      "complaints_by_state = cc_data[\"State\"]\n",
+      "complaint_by_state_counts = complaints_by_state.value_counts()[:53]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 124
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "state_abbreviation_conversion = {\"ND\": \"North Dakota\",\n",
+      "                                 \"WY\": \"Wyoming\",\n",
+      "                                 \"MT\": \"Montana\",\n",
+      "                                 \"AK\": \"Arkansas\",\n",
+      "                                 \"VT\": \"Vermont\",\n",
+      "                                 \"SD\": \"South Dakota\",\n",
+      "                                 \"WV\": \"West Virginia\",\n",
+      "                                 \"PR\": \"Puerto Rico\",\n",
+      "                                 \"NE\": \"Nebraska\",\n",
+      "                                 \"ME\": \"Maine\",\n",
+      "                                 \"ID\": \"Idaho\",\n",
+      "                                 \"RI\": \"Rhode Island\",\n",
+      "                                 \"DE\": \"Delaware\",\n",
+      "                                 \"NH\": \"New Hampshire\",\n",
+      "                                 \"HI\": \"Hawaii\",\n",
+      "                                 \"IA\": \"Iowa\",\n",
+      "                                 \"NM\": \"New Mexico\",\n",
+      "                                 \"KS\": \"Kansas\",\n",
+      "                                 \"MS\": \"Mississippi\",\n",
+      "                                 \"AR\": \"Arizona\",\n",
+      "                                 \"KY\": \"Kentucky\",\n",
+      "                                 \"UT\": \"Utah\",\n",
+      "                                 \"DC\": \"District of Columbia\",\n",
+      "                                 \"OK\": \"Oklahoma\",\n",
+      "                                 \"CT\": \"Connecticut\",\n",
+      "                                 \"MO\": \"Missouri\",\n",
+      "                                 \"OR\": \"Oregon\",\n",
+      "                                 \"LA\": \"Louisiana\",\n",
+      "                                 \"SC\": \"South Carolina\",\n",
+      "                                 \"IN\": \"Indiana\",\n",
+      "                                 \"MN\": \"Minnesota\",\n",
+      "                                 \"WI\": \"Wisconsin\",\n",
+      "                                 \"AL\": \"Alabama\",\n",
+      "                                 \"NV\": \"Nevada\",\n",
+      "                                 \"CO\": \"Colorado\",\n",
+      "                                 \"TN\": \"Tennessee\",\n",
+      "                                 \"MA\": \"Massachusetts\",\n",
+      "                                 \"AZ\": \"Arizona\",\n",
+      "                                 \"WA\": \"Washington\",\n",
+      "                                 \"MI\": \"Michigan\",\n",
+      "                                 \"NC\": \"North Carolina\",\n",
+      "                                 \"MD\": \"Maryland\",\n",
+      "                                 \"OH\": \"Ohio\",\n",
+      "                                 \"VA\": \"Virginia\",\n",
+      "                                 \"PA\": \"Pennsylvania\",\n",
+      "                                 \"IL\": \"Illinois\",\n",
+      "                                 \"NJ\": \"New Jersey\",\n",
+      "                                 \"GA\": \"Georgia\",\n",
+      "                                 \"NY\": \"New York\",\n",
+      "                                 \"FL\": \"Florida\",\n",
+      "                                 \"TX\": \"Texas\",\n",
+      "                                 \"CA\": \"California\"\n",
+      "                                 }"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 125
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "complaints_per_capita = []\n",
+      "state_list = []\n",
+      "for key, value in state_abbreviation_conversion.items():\n",
+      "    complaints_per_capita.append(complaint_by_state_counts[key] / pop_data_by_state[\"POPESTIMATE2014\"][value])\n",
+      "    state_list.append(key)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 126
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "per_capita_data = pd.Series(complaints_per_capita)\n",
+      "per_capita_data.plot(kind=\"bar\", color=\"black\")\n",
+      "plt.xticks(np.arange(0,52), state_list)\n",
+      "plt.gcf().set_size_inches(12,10)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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8GnBAz7S9gdsyc11mbgSuAQ5talb1qdkvM69qfl8FHA48C1idmRsz8x7gNkpP933Af2me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\nAABJRU5ErkJggg==\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10f2d5438>"
+       ]
+      }
+     ],
+     "prompt_number": 151
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "fig, ax = plt.subplots()\n",
+      "plt.gcf().set_size_inches(12,10)\n",
+      "per_capita_np = per_capita_data.values\n",
+      "per_capita_np = per_capita_np[None, :]\n",
+      "ax.pcolor(per_capita_np, cmap=plt.cm.Blues)\n",
+      "ax.set_xticks(np.arange(per_capita_np.shape[1])+0.5, minor=False)\n",
+      "ax.set_xticklabels(state_list, rotation='vertical', minor=False)\n",
+      "ax.set_xlim(0, 52)\n",
+      "ax.yaxis.set_visible(False)\n",
+      "PCM=ax.get_children()[2]\n",
+      "plt.colorbar(PCM, ax=ax)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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RcTRwTDWP12XmRRHxIOBfgAcDdwN/kpn/HRF7A2+pyl6ama+dtv42c0uSpOGZ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\nOAf442q+fw28mLIf/6wWzDG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+       "text": [
+        "<matplotlib.figure.Figure at 0x10f1eecf8>"
+       ]
+      }
+     ],
+     "prompt_number": 250
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 205
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}
\ No newline at end of file