Deep_Learning_input_data.ipynb

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      "name": "Deep_Learning_input_data.ipynb",
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    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WfNaSr-gwKGH"
      },
      "source": [
        "<<목차>>\n",
        "\n",
        "0. 필요한 패키지 임포트\n",
        "1. 데이터 불러오기\n",
        "2. 데이터 전처리\n",
        "3. X값 만들기\n",
        "4. Y값 만들기"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ptL9SR73wKGJ"
      },
      "source": [
        "# 0. 필요한 패키지 임포트"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "zII2Zto5wKGJ"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import pickle\n",
        "import os\n",
        "import sys\n",
        "\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "import sklearn\n",
        "from sklearn.model_selection import train_test_split, cross_val_score, KFold\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from sklearn.preprocessing import MinMaxScaler, StandardScaler"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y1WMPdZ8wKGO",
        "outputId": "729133b1-3cd5-4584-f1b3-4e70f83eb5cd"
      },
      "source": [
        "print(np.__version__)\n",
        "print(pd.__version__)\n",
        "print(pickle.format_version)\n",
        "print(mpl.__version__)\n",
        "print(sns.__version__)\n",
        "print(sklearn.__version__)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.19.1\n",
            "1.1.1\n",
            "4.0\n",
            "3.3.1\n",
            "0.11.0\n",
            "0.23.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0cKJCbR1wKGT"
      },
      "source": [
        "os.chdir('./데이터')   # 파일 경로 설정"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-mFQqptkwKGZ"
      },
      "source": [
        "# 1. 데이터 불러오기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sKl-c9DewKGa",
        "outputId": "83499de5-0cc1-43d3-dd30-4eb37522f11a"
      },
      "source": [
        "with open('최종_데이터프레임.pickle', 'rb') as f:\n",
        "    data=pickle.load(f)\n",
        "data.head()"
      ],
      "execution_count": null,
      "outputs": [
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              "      id  조사년도  조사월  단속활동유무  적발횟수_0  적발횟수_1  적발횟수_2  적발횟수_3  적발횟수_4  적발횟수_5  \\\n",
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              "\n",
              "      관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  \n",
              "0  3852.639324  4612.220563   0   0   0   0  \n",
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        "outputId": "2186967c-2f1e-4094-aac4-48ea25d16fde"
      },
      "source": [
        "data.shape"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(9003120, 81)"
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          },
          "metadata": {
            "tags": []
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        }
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      "source": [
        "data.columns"
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id', '조사년도', '조사월', '단속활동유무', '적발횟수_0', '적발횟수_1', '적발횟수_2', '적발횟수_3',\n",
              "       '적발횟수_4', '적발횟수_5', '적발횟수_6', '돼지고기', '소고기', '닭고기', '김치', '쌀', '콩',\n",
              "       '기타', '미위반', '일반음식점_미위반', '식육 판매업_미위반', '슈퍼_미위반', '가공업체_미위반', '양곡상_미위반',\n",
              "       '휴게음식점_미위반', '기타_미위반', '일반음식점_위반', '식육 판매업_위반', '슈퍼_위반', '가공업체_위반',\n",
              "       '양곡상_위반', '휴게음식점_위반', '기타_위반', '도소매업_미위반', '음식점업_미위반', '식품제조업(가공)_미위반',\n",
              "       '업태누락_미위반', '도소매업_위반', '음식점업_위반', '식품제조업(가공)_위반', '업태누락_위반', '65세이상인구',\n",
              "       '총수급자', '독거노인수', '독거노인수_기초생활보장수급권자', '독거노인수_저소득', '총인구', '한국총인구',\n",
              "       '외국인인구', '전체평균연령', '남자', '여자', '행정동', '음식점업', '도소매업', '식품제조업(가공)',\n",
              "       '업태누락', '쇠고기냉장_수량_톤', '쇠고기냉동_수량_톤', '돼지고기냉장_수량_톤', '돼지고기냉동_수량_톤',\n",
              "       '닭고기_수량_톤', '쇠고기가격_도매', '쇠고기가격_소매', '돼지고기가격_도매', '돼지고기가격_소매',\n",
              "       '닭고기가격_도매', '닭고기가격_소매', '한우갈비_100g', '한우불고기_100g', '호주산갈비_냉동_100g',\n",
              "       '호주산갈비_냉장_100g', '호주산불고기_냉동_100g', '호주산불고기_냉장_100g', '모범업소와의 거리',\n",
              "       '관공서와의 거리', '적발지점과의 거리', 'Q1', 'Q2', 'Q3', 'Q4'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
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        "outputId": "e6025085-8c2c-457b-b18a-3c13b7592063"
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      "source": [
        "data.tail()"
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      "execution_count": null,
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              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>False</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>3249</td>\n",
              "      <td>1560</td>\n",
              "      <td>2029</td>\n",
              "      <td>6319.049065</td>\n",
              "      <td>1406.722464</td>\n",
              "      <td>1051.195622</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9003118</th>\n",
              "      <td>111913.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>11</td>\n",
              "      <td>False</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>2890</td>\n",
              "      <td>1564</td>\n",
              "      <td>2030</td>\n",
              "      <td>6319.049065</td>\n",
              "      <td>1406.722464</td>\n",
              "      <td>1051.195622</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9003119</th>\n",
              "      <td>111913.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>12</td>\n",
              "      <td>False</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>2558</td>\n",
              "      <td>1568</td>\n",
              "      <td>2030</td>\n",
              "      <td>6319.049065</td>\n",
              "      <td>1406.722464</td>\n",
              "      <td>1051.195622</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 81 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               id  조사년도  조사월  단속활동유무  적발횟수_0  적발횟수_1  적발횟수_2  적발횟수_3  적발횟수_4  \\\n",
              "9003115  111913.0  2019    8   False       0       0       0       0       0   \n",
              "9003116  111913.0  2019    9   False       0       0       0       0       0   \n",
              "9003117  111913.0  2019   10   False       0       0       0       0       0   \n",
              "9003118  111913.0  2019   11   False       0       0       0       0       0   \n",
              "9003119  111913.0  2019   12   False       0       0       0       0       0   \n",
              "\n",
              "         적발횟수_5  ...  호주산갈비_냉장_100g  호주산불고기_냉동_100g  호주산불고기_냉장_100g  \\\n",
              "9003115       0  ...           2820            1551            2027   \n",
              "9003116       0  ...           3125            1556            2030   \n",
              "9003117       0  ...           3249            1560            2029   \n",
              "9003118       0  ...           2890            1564            2030   \n",
              "9003119       0  ...           2558            1568            2030   \n",
              "\n",
              "           모범업소와의 거리     관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  \n",
              "9003115  6319.049065  1406.722464  1051.195622   0   0   0   0  \n",
              "9003116  6319.049065  1406.722464  1051.195622   0   0   0   0  \n",
              "9003117  6319.049065  1406.722464  1051.195622   0   0   0   0  \n",
              "9003118  6319.049065  1406.722464  1051.195622   0   0   0   0  \n",
              "9003119  6319.049065  1406.722464  1051.195622   0   0   0   0  \n",
              "\n",
              "[5 rows x 81 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9OlTYQGWwKGo"
      },
      "source": [
        "# 2. 데이터 전처리"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6jg_yHNHwKGo"
      },
      "source": [
        "# 한 번도 조사 나가지 않았던 곳 제외\n",
        "criteria = (data.적발횟수_0 == 0) & (data.적발횟수_1 == 0) & (data.적발횟수_2 == 0) & (data.적발횟수_3 == 0) & (data.적발횟수_4 == 0) & (data.적발횟수_5 == 0) & (data.적발횟수_6 == 0)\n",
        "data.drop(data[criteria].index, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "htarILmHwKGr",
        "outputId": "98396d88-668e-42a9-afa9-61f7aecc24f7"
      },
      "source": [
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>조사년도</th>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>2209</td>\n",
              "      <td>1100</td>\n",
              "      <td>1681</td>\n",
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              "      <td>110992.0</td>\n",
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              "      <td>4</td>\n",
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              "    <tr>\n",
              "      <th>9002659</th>\n",
              "      <td>111610.0</td>\n",
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              "      <td>1100</td>\n",
              "      <td>1878</td>\n",
              "      <td>2642.290162</td>\n",
              "      <td>1327.471248</td>\n",
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              "      <th>9002702</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>3</td>\n",
              "      <td>True</td>\n",
              "      <td>2</td>\n",
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              "      <td>2478</td>\n",
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              "      <td>1327.471248</td>\n",
              "      <td>948.801329</td>\n",
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              "      <th>9002757</th>\n",
              "      <td>111610.0</td>\n",
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              "      <td>True</td>\n",
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              "      <td>1560</td>\n",
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              "      <td>6315.950726</td>\n",
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              "      <td>959.702931</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>92614 rows × 81 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               id  조사년도  조사월  단속활동유무  적발횟수_0  적발횟수_1  적발횟수_2  적발횟수_3  적발횟수_4  \\\n",
              "125         162.0  2010    6    True       4       0       0       0       0   \n",
              "24732      4397.0  2011    1    True       1       0       0       0       0   \n",
              "40812      5879.0  2011    1    True       1       0       0       0       0   \n",
              "46445      6192.0  2010    6    True       1       0       0       0       0   \n",
              "46446      6192.0  2010    7    True       1       0       0       0       0   \n",
              "...           ...   ...  ...     ...     ...     ...     ...     ...     ...   \n",
              "8997477  110992.0  2019   10    True       1       0       0       0       0   \n",
              "9002659  111610.0  2011    8    True       1       0       0       0       0   \n",
              "9002660  111610.0  2011    9    True       1       0       0       0       0   \n",
              "9002702  111610.0  2015    3    True       2       0       0       0       0   \n",
              "9002757  111610.0  2019   10    True       1       0       0       0       0   \n",
              "\n",
              "         적발횟수_5  ...  호주산갈비_냉장_100g  호주산불고기_냉동_100g  호주산불고기_냉장_100g  \\\n",
              "125           0  ...           1645            1100            1374   \n",
              "24732         0  ...           2209            1100            1681   \n",
              "40812         0  ...           2209            1100            1681   \n",
              "46445         0  ...           1645            1100            1374   \n",
              "46446         0  ...           1469            1100            1433   \n",
              "...         ...  ...            ...             ...             ...   \n",
              "8997477       0  ...           3249            1560            2029   \n",
              "9002659       0  ...           1868            1100            1878   \n",
              "9002660       0  ...           2341            1100            1736   \n",
              "9002702       0  ...           2478            1400            2418   \n",
              "9002757       0  ...           3249            1560            2029   \n",
              "\n",
              "           모범업소와의 거리     관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  \n",
              "125      8517.740954  3900.057991  4668.864521   0   0   0   0  \n",
              "24732    5331.239728  2841.434788  2867.345386   0   0   0   0  \n",
              "40812    5942.053610  2352.696260  2340.621779   0   0   0   0  \n",
              "46445    7759.830956  1851.104842  2444.678466   0   0   0   0  \n",
              "46446    7759.830956  1851.104842  2444.678466   0   0   0   0  \n",
              "...              ...          ...          ...  ..  ..  ..  ..  \n",
              "8997477  7301.190220   884.021012  1224.179893   0   0   0   4  \n",
              "9002659  2642.290162  1327.471248  2369.320204   0   0   0   0  \n",
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              "[92614 rows x 81 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-8unC1BewKGu",
        "outputId": "9db1d5b3-d972-4ef3-c6a1-945b74391b7e"
      },
      "source": [
        "# grid의 id와 조사년도, 조사월 순으로 정렬\n",
        "data1=data.copy() \n",
        "data1=data1.sort_values(['id','조사년도','조사월'])\n",
        "data1.reset_index(drop=True, inplace=True)\n",
        "data1.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "       id  조사년도  조사월  단속활동유무  적발횟수_0  적발횟수_1  적발횟수_2  적발횟수_3  적발횟수_4  적발횟수_5  \\\n",
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              "\n",
              "   ...  호주산갈비_냉장_100g  호주산불고기_냉동_100g  호주산불고기_냉장_100g    모범업소와의 거리  \\\n",
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              "\n",
              "      관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  \n",
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              "[5 rows x 81 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7JglLYRYwKG0",
        "outputId": "4b7942b2-4016-4f83-aafd-bd1c8178e01d"
      },
      "source": [
        "data1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92613</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>True</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>3249</td>\n",
              "      <td>1560</td>\n",
              "      <td>2029</td>\n",
              "      <td>6315.950726</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>959.702931</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>92614 rows × 81 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  조사년도  조사월  단속활동유무  적발횟수_0  적발횟수_1  적발횟수_2  적발횟수_3  적발횟수_4  \\\n",
              "0         162.0  2010    6    True       4       0       0       0       0   \n",
              "1        4397.0  2011    1    True       1       0       0       0       0   \n",
              "2        5879.0  2011    1    True       1       0       0       0       0   \n",
              "3        6192.0  2010    6    True       1       0       0       0       0   \n",
              "4        6192.0  2010    7    True       1       0       0       0       0   \n",
              "...         ...   ...  ...     ...     ...     ...     ...     ...     ...   \n",
              "92609  110992.0  2019   10    True       1       0       0       0       0   \n",
              "92610  111610.0  2011    8    True       1       0       0       0       0   \n",
              "92611  111610.0  2011    9    True       1       0       0       0       0   \n",
              "92612  111610.0  2015    3    True       2       0       0       0       0   \n",
              "92613  111610.0  2019   10    True       1       0       0       0       0   \n",
              "\n",
              "       적발횟수_5  ...  호주산갈비_냉장_100g  호주산불고기_냉동_100g  호주산불고기_냉장_100g  \\\n",
              "0           0  ...           1645            1100            1374   \n",
              "1           0  ...           2209            1100            1681   \n",
              "2           0  ...           2209            1100            1681   \n",
              "3           0  ...           1645            1100            1374   \n",
              "4           0  ...           1469            1100            1433   \n",
              "...       ...  ...            ...             ...             ...   \n",
              "92609       0  ...           3249            1560            2029   \n",
              "92610       0  ...           1868            1100            1878   \n",
              "92611       0  ...           2341            1100            1736   \n",
              "92612       0  ...           2478            1400            2418   \n",
              "92613       0  ...           3249            1560            2029   \n",
              "\n",
              "         모범업소와의 거리     관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  \n",
              "0      8517.740954  3900.057991  4668.864521   0   0   0   0  \n",
              "1      5331.239728  2841.434788  2867.345386   0   0   0   0  \n",
              "2      5942.053610  2352.696260  2340.621779   0   0   0   0  \n",
              "3      7759.830956  1851.104842  2444.678466   0   0   0   0  \n",
              "4      7759.830956  1851.104842  2444.678466   0   0   0   0  \n",
              "...            ...          ...          ...  ..  ..  ..  ..  \n",
              "92609  7301.190220   884.021012  1224.179893   0   0   0   4  \n",
              "92610  2642.290162  1327.471248  2369.320204   0   0   0   0  \n",
              "92611  2642.290162  1327.471248  2369.320204   0   0   0   0  \n",
              "92612   955.504602  1327.471248   948.801329   0   0   0   0  \n",
              "92613  6315.950726  1327.471248   959.702931   0   0   0   0  \n",
              "\n",
              "[92614 rows x 81 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tpQCd0SzwKG3"
      },
      "source": [
        "data1.to_csv('최종_데이터프레임_조사나간곳만.csv', encoding='cp949')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cngTZAN0wKG5"
      },
      "source": [
        "# 최종_데이터프레임_조사나간곳만"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cKVvb_nFwKG7"
      },
      "source": [
        "### 필요한 columns 추가하고, 필요없는 columns 제거"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oYzo9ZFJwKG7"
      },
      "source": [
        "data1 = pd.read_csv('최종_데이터프레임_조사나간곳만.csv', encoding='cp949', index_col=0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QBFarBhXwKG-",
        "outputId": "973310a4-11cc-4138-9526-e284bcb1649f"
      },
      "source": [
        "data1.drop_duplicates(['id', '행정동'])  # id와 행정동 2가지가 모두 중복되는 것만 보여주기"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>조사년도</th>\n",
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              "      <td>2209</td>\n",
              "      <td>1100</td>\n",
              "      <td>1681</td>\n",
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              "      <td>110381.0</td>\n",
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              "      <td>1100</td>\n",
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              "      <th>92604</th>\n",
              "      <td>110401.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1100</td>\n",
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              "    <tr>\n",
              "      <th>92606</th>\n",
              "      <td>110988.0</td>\n",
              "      <td>2018</td>\n",
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              "      <td>1981</td>\n",
              "      <td>7406.116592</td>\n",
              "      <td>658.719915</td>\n",
              "      <td>1468.376806</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>92607</th>\n",
              "      <td>110992.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>5</td>\n",
              "      <td>True</td>\n",
              "      <td>2</td>\n",
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              "      <td>...</td>\n",
              "      <td>1863</td>\n",
              "      <td>1100</td>\n",
              "      <td>1570</td>\n",
              "      <td>2405.038107</td>\n",
              "      <td>884.021012</td>\n",
              "      <td>2153.817367</td>\n",
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              "    <tr>\n",
              "      <th>92610</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>8</td>\n",
              "      <td>True</td>\n",
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              "      <td>1868</td>\n",
              "      <td>1100</td>\n",
              "      <td>1878</td>\n",
              "      <td>2642.290162</td>\n",
              "      <td>1327.471248</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16235 rows × 81 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  조사년도  조사월  단속활동유무  적발횟수_0  적발횟수_1  적발횟수_2  적발횟수_3  적발횟수_4  \\\n",
              "0         162.0  2010    6    True       4       0       0       0       0   \n",
              "1        4397.0  2011    1    True       1       0       0       0       0   \n",
              "2        5879.0  2011    1    True       1       0       0       0       0   \n",
              "3        6192.0  2010    6    True       1       0       0       0       0   \n",
              "5        7393.0  2010    7    True       1       0       0       0       0   \n",
              "...         ...   ...  ...     ...     ...     ...     ...     ...     ...   \n",
              "92600  110381.0  2010    8    True       1       0       0       0       0   \n",
              "92604  110401.0  2010    6    True       1       0       0       0       0   \n",
              "92606  110988.0  2018    8    True       1       0       0       0       0   \n",
              "92607  110992.0  2011    5    True       2       0       0       0       0   \n",
              "92610  111610.0  2011    8    True       1       0       0       0       0   \n",
              "\n",
              "       적발횟수_5  ...  호주산갈비_냉장_100g  호주산불고기_냉동_100g  호주산불고기_냉장_100g  \\\n",
              "0           0  ...           1645            1100            1374   \n",
              "1           0  ...           2209            1100            1681   \n",
              "2           0  ...           2209            1100            1681   \n",
              "3           0  ...           1645            1100            1374   \n",
              "5           0  ...           1469            1100            1433   \n",
              "...       ...  ...            ...             ...             ...   \n",
              "92600       0  ...           1500            1100            1642   \n",
              "92604       0  ...           1645            1100            1374   \n",
              "92606       0  ...           2287            1560            1981   \n",
              "92607       0  ...           1863            1100            1570   \n",
              "92610       0  ...           1868            1100            1878   \n",
              "\n",
              "         모범업소와의 거리     관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  \n",
              "0      8517.740954  3900.057991  4668.864521   0   0   0   0  \n",
              "1      5331.239728  2841.434788  2867.345386   0   0   0   0  \n",
              "2      5942.053610  2352.696260  2340.621779   0   0   0   0  \n",
              "3      7759.830956  1851.104842  2444.678466   0   0   0   0  \n",
              "5      7635.786943  1714.559216  1869.793401   0   0   0   0  \n",
              "...            ...          ...          ...  ..  ..  ..  ..  \n",
              "92600  2493.607680   420.708348  4053.119685   0   0   0   0  \n",
              "92604  2242.796490   929.271559  3065.501023   0   0   0   0  \n",
              "92606  7406.116592   658.719915  1468.376806   0   0   0   0  \n",
              "92607  2405.038107   884.021012  2153.817367   0   0   0   0  \n",
              "92610  2642.290162  1327.471248  2369.320204   0   0   0   0  \n",
              "\n",
              "[16235 rows x 81 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c0J6rUemwKHB"
      },
      "source": [
        "0. 그냥 뺄 것 : \n",
        "    - '단속활동유무' --> 이미 조사나간 적 있는 곳만 추려냈으니 다 True\n",
        "    - '적발횟수_1', '적발횟수_2', '적발횟수_3','적발횟수_4', '적발횟수_5', '적발횟수_6'\n",
        "    - '한우갈비_100g', '한우불고기_100g', '호주산갈비_냉동_100g', '호주산갈비_냉장_100g', '호주산불고기_냉동_100g', '호주산불고기_냉장_100g'\n",
        "1. '적발횟수_0' --> '미적발건수'로 변경\n",
        "2. 적발횟수_1 ~ 적발횟수_6 다 더해서 '총적발건수'\n",
        "3. 적발횟수_2 ~ 적발횟수_6 다 더해서 '재적발건수'\n",
        "4. \n",
        "    - (1) '한우갈비_100g' - '호주산갈비_냉동_100g' : '냉동갈비_가격차이_100g'\n",
        "    - (2) '한우갈비_100g' - '호주산갈비_냉장_100g' : '냉장갈비_가격차이_100g'\n",
        "    - (3) '한우불고기_100g' - '호주산불고기_냉동_100g' : '냉동불고기_가격차이_100g'\n",
        "    - (4) '한우불고기_100g' - '호주산불고기_냉장_100g' : '냉장불고기_가격차이_100g'"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "ZWRdAAfjwKHC",
        "outputId": "8226f2da-8c59-4eb4-93ef-c5e560f13e39"
      },
      "source": [
        "# 새로 추가할 변수 column 추가\n",
        "\n",
        "data1['총적발건수'] = np.nan\n",
        "data1['재적발건수'] = np.nan\n",
        "data1['냉동갈비_가격차이_100g'] = np.nan\n",
        "data1['냉장갈비_가격차이_100g'] = np.nan\n",
        "data1['냉동불고기_가격차이_100g'] = np.nan\n",
        "data1['냉장불고기_가격차이_100g'] = np.nan\n",
        "data1.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id', '조사년도', '조사월', '단속활동유무', '적발횟수_0', '적발횟수_1', '적발횟수_2', '적발횟수_3',\n",
              "       '적발횟수_4', '적발횟수_5', '적발횟수_6', '돼지고기', '소고기', '닭고기', '김치', '쌀', '콩',\n",
              "       '기타', '미위반', '일반음식점_미위반', '식육 판매업_미위반', '슈퍼_미위반', '가공업체_미위반', '양곡상_미위반',\n",
              "       '휴게음식점_미위반', '기타_미위반', '일반음식점_위반', '식육 판매업_위반', '슈퍼_위반', '가공업체_위반',\n",
              "       '양곡상_위반', '휴게음식점_위반', '기타_위반', '도소매업_미위반', '음식점업_미위반', '식품제조업(가공)_미위반',\n",
              "       '업태누락_미위반', '도소매업_위반', '음식점업_위반', '식품제조업(가공)_위반', '업태누락_위반', '65세이상인구',\n",
              "       '총수급자', '독거노인수', '독거노인수_기초생활보장수급권자', '독거노인수_저소득', '총인구', '한국총인구',\n",
              "       '외국인인구', '전체평균연령', '남자', '여자', '행정동', '음식점업', '도소매업', '식품제조업(가공)',\n",
              "       '업태누락', '쇠고기냉장_수량_톤', '쇠고기냉동_수량_톤', '돼지고기냉장_수량_톤', '돼지고기냉동_수량_톤',\n",
              "       '닭고기_수량_톤', '쇠고기가격_도매', '쇠고기가격_소매', '돼지고기가격_도매', '돼지고기가격_소매',\n",
              "       '닭고기가격_도매', '닭고기가격_소매', '한우갈비_100g', '한우불고기_100g', '호주산갈비_냉동_100g',\n",
              "       '호주산갈비_냉장_100g', '호주산불고기_냉동_100g', '호주산불고기_냉장_100g', '모범업소와의 거리',\n",
              "       '관공서와의 거리', '적발지점과의 거리', 'Q1', 'Q2', 'Q3', 'Q4', '총적발건수', '재적발건수',\n",
              "       '냉동갈비_가격차이_100g', '냉장갈비_가격차이_100g', '냉동불고기_가격차이_100g',\n",
              "       '냉장불고기_가격차이_100g'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2SChnOFuwKHE",
        "outputId": "a0504fea-9483-4ea9-be62-18ddf4a28d16"
      },
      "source": [
        "%%time\n",
        "# 새로운 변수값 채워넣기\n",
        "for i in range(len(data1)):  \n",
        "    print('Process : {} | Total : {}'.format(i+1, len(data1)), end='\\r')\n",
        "    data1.iloc[i, -6] = data1.iloc[i, 5] + data1.iloc[i, 6] + data1.iloc[i, 7] + data1.iloc[i, 8] + data1.iloc[i, 9] + data1.iloc[i, 10]    # 총적발건수\n",
        "    data1.iloc[i, -5] = data1.iloc[i, 6] + data1.iloc[i, 7] + data1.iloc[i, 8] + data1.iloc[i, 9] + data1.iloc[i, 10]    # 재적발건수\n",
        "    data1.iloc[i, -4] = data1.iloc[i, -19] - data1.iloc[i, -17]    # 냉동갈비_가격차이_100g\n",
        "    data1.iloc[i, -3] = data1.iloc[i, -19] - data1.iloc[i, -16]   # 냉장갈비_가격차이_100g\n",
        "    data1.iloc[i, -2] = data1.iloc[i, -18] - data1.iloc[i, -15]   # 냉동불고기_가격차이_100g\n",
        "    data1.iloc[i, -1] = data1.iloc[i, -18] - data1.iloc[i, -14]   # 냉장불고기_가격차이_100g"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Wall time: 12min 12stal : 92614\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VMuYpZ0gwKHH",
        "outputId": "e6d7b6b7-a214-48c0-b2db-6148613f2311"
      },
      "source": [
        "data1.head()"
      ],
      "execution_count": null,
      "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>조사년도</th>\n",
              "      <th>조사월</th>\n",
              "      <th>단속활동유무</th>\n",
              "      <th>적발횟수_0</th>\n",
              "      <th>적발횟수_1</th>\n",
              "      <th>적발횟수_2</th>\n",
              "      <th>적발횟수_3</th>\n",
              "      <th>적발횟수_4</th>\n",
              "      <th>적발횟수_5</th>\n",
              "      <th>...</th>\n",
              "      <th>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>총적발건수</th>\n",
              "      <th>재적발건수</th>\n",
              "      <th>냉동갈비_가격차이_100g</th>\n",
              "      <th>냉장갈비_가격차이_100g</th>\n",
              "      <th>냉동불고기_가격차이_100g</th>\n",
              "      <th>냉장불고기_가격차이_100g</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>162.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6736.0</td>\n",
              "      <td>6371.0</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4397.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>True</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5188.0</td>\n",
              "      <td>4579.0</td>\n",
              "      <td>2410.0</td>\n",
              "      <td>1829.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5879.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>True</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5188.0</td>\n",
              "      <td>4579.0</td>\n",
              "      <td>2410.0</td>\n",
              "      <td>1829.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6736.0</td>\n",
              "      <td>6371.0</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>7</td>\n",
              "      <td>True</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>6621.0</td>\n",
              "      <td>6584.0</td>\n",
              "      <td>2787.0</td>\n",
              "      <td>2454.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 87 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       id  조사년도  조사월  단속활동유무  적발횟수_0  적발횟수_1  적발횟수_2  적발횟수_3  적발횟수_4  적발횟수_5  \\\n",
              "0   162.0  2010    6    True       4       0       0       0       0       0   \n",
              "1  4397.0  2011    1    True       1       0       0       0       0       0   \n",
              "2  5879.0  2011    1    True       1       0       0       0       0       0   \n",
              "3  6192.0  2010    6    True       1       0       0       0       0       0   \n",
              "4  6192.0  2010    7    True       1       0       0       0       0       0   \n",
              "\n",
              "   ...  Q1  Q2  Q3  Q4  총적발건수  재적발건수  냉동갈비_가격차이_100g  냉장갈비_가격차이_100g  \\\n",
              "0  ...   0   0   0   0    0.0    0.0          6736.0          6371.0   \n",
              "1  ...   0   0   0   0    0.0    0.0          5188.0          4579.0   \n",
              "2  ...   0   0   0   0    0.0    0.0          5188.0          4579.0   \n",
              "3  ...   0   0   0   0    0.0    0.0          6736.0          6371.0   \n",
              "4  ...   0   0   0   0    0.0    0.0          6621.0          6584.0   \n",
              "\n",
              "   냉동불고기_가격차이_100g  냉장불고기_가격차이_100g  \n",
              "0           3163.0           2889.0  \n",
              "1           2410.0           1829.0  \n",
              "2           2410.0           1829.0  \n",
              "3           3163.0           2889.0  \n",
              "4           2787.0           2454.0  \n",
              "\n",
              "[5 rows x 87 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sEX6uHtJwKHK"
      },
      "source": [
        "# '적발횟수_0' --> '미적발건수'로 변경\n",
        "data1.rename(columns = {'적발횟수_0' : '미적발건수'}, inplace = True)  \n",
        "\n",
        "# 필요없는 변수, 사용했던 변수 칼럼은 삭제\n",
        "data1.drop(['단속활동유무', '적발횟수_1', '적발횟수_2', '적발횟수_3','적발횟수_4', '적발횟수_5', '적발횟수_6', \n",
        "            '한우갈비_100g', '한우불고기_100g', '호주산갈비_냉동_100g', '호주산갈비_냉장_100g', '호주산불고기_냉동_100g', '호주산불고기_냉장_100g'], axis=1, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FXGnlYn2wKHN"
      },
      "source": [
        "# 필요한 column만 사용하기\n",
        "nec_columns = ['id', '조사년도', '조사월', '행정동', \n",
        "               '재적발건수', '미적발건수', \n",
        "               '65세이상인구','총수급자', '독거노인수', '독거노인수_기초생활보장수급권자', '독거노인수_저소득', '한국총인구', '외국인인구', \n",
        "               '음식점업', '도소매업', '식품제조업(가공)', '업태누락', \n",
        "               '쇠고기냉장_수량_톤', '쇠고기냉동_수량_톤', '돼지고기냉장_수량_톤', '돼지고기냉동_수량_톤', '닭고기_수량_톤', '쇠고기가격_도매', '쇠고기가격_소매', \n",
        "               '돼지고기가격_도매', '돼지고기가격_소매', '닭고기가격_도매', '닭고기가격_소매', \n",
        "               '냉동갈비_가격차이_100g', '냉장갈비_가격차이_100g', '냉동불고기_가격차이_100g', '냉장불고기_가격차이_100g',\n",
        "               '모범업소와의 거리', '관공서와의 거리', '적발지점과의 거리', 'Q1', 'Q2', 'Q3', 'Q4',\n",
        "               '총적발건수']\n",
        "data2 = data1[nec_columns]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fsGpge-IwKHP"
      },
      "source": [
        "data2.to_csv('최종_데이터프레임_데이터정제.csv', encoding='cp949')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tlRCqlw_wKHS"
      },
      "source": [
        "# Scaling"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iCzo9qI4wKHS",
        "outputId": "5986237d-dd3b-41bf-f61a-5a132853bd73"
      },
      "source": [
        "data2 = pd.read_csv('최종_데이터프레임_데이터정제.csv', encoding='cp949', index_col=0)\n",
        "data2"
      ],
      "execution_count": null,
      "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>조사년도</th>\n",
              "      <th>조사월</th>\n",
              "      <th>행정동</th>\n",
              "      <th>재적발건수</th>\n",
              "      <th>미적발건수</th>\n",
              "      <th>65세이상인구</th>\n",
              "      <th>총수급자</th>\n",
              "      <th>독거노인수</th>\n",
              "      <th>독거노인수_기초생활보장수급권자</th>\n",
              "      <th>...</th>\n",
              "      <th>냉동불고기_가격차이_100g</th>\n",
              "      <th>냉장불고기_가격차이_100g</th>\n",
              "      <th>모범업소와의 거리</th>\n",
              "      <th>관공서와의 거리</th>\n",
              "      <th>적발지점과의 거리</th>\n",
              "      <th>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>총적발건수</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>162.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
              "      <td>8517.740954</td>\n",
              "      <td>3900.057991</td>\n",
              "      <td>4668.864521</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4397.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2283.0</td>\n",
              "      <td>217.0</td>\n",
              "      <td>532.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2410.0</td>\n",
              "      <td>1829.0</td>\n",
              "      <td>5331.239728</td>\n",
              "      <td>2841.434788</td>\n",
              "      <td>2867.345386</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5879.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2283.0</td>\n",
              "      <td>217.0</td>\n",
              "      <td>532.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2410.0</td>\n",
              "      <td>1829.0</td>\n",
              "      <td>5942.053610</td>\n",
              "      <td>2352.696260</td>\n",
              "      <td>2340.621779</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
              "      <td>7759.830956</td>\n",
              "      <td>1851.104842</td>\n",
              "      <td>2444.678466</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>7</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2787.0</td>\n",
              "      <td>2454.0</td>\n",
              "      <td>7759.830956</td>\n",
              "      <td>1851.104842</td>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <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>92609</th>\n",
              "      <td>110992.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>4527.0</td>\n",
              "      <td>589.0</td>\n",
              "      <td>627.0</td>\n",
              "      <td>159.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2692.0</td>\n",
              "      <td>2223.0</td>\n",
              "      <td>7301.190220</td>\n",
              "      <td>884.021012</td>\n",
              "      <td>1224.179893</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92610</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>8</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>3109.0</td>\n",
              "      <td>256.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1904.0</td>\n",
              "      <td>1126.0</td>\n",
              "      <td>2642.290162</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>2369.320204</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92611</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>9</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>3109.0</td>\n",
              "      <td>256.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2218.0</td>\n",
              "      <td>1582.0</td>\n",
              "      <td>2642.290162</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>2369.320204</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92612</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>3</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2</td>\n",
              "      <td>3759.0</td>\n",
              "      <td>429.0</td>\n",
              "      <td>428.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2152.0</td>\n",
              "      <td>1134.0</td>\n",
              "      <td>955.504602</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>948.801329</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92613</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>4527.0</td>\n",
              "      <td>589.0</td>\n",
              "      <td>627.0</td>\n",
              "      <td>159.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2692.0</td>\n",
              "      <td>2223.0</td>\n",
              "      <td>6315.950726</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>959.702931</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>92614 rows × 40 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  조사년도  조사월  행정동  재적발건수  미적발건수  65세이상인구   총수급자  독거노인수  \\\n",
              "0         162.0  2010    6  공항동    0.0      4   2175.0  246.0  495.0   \n",
              "1        4397.0  2011    1  공항동    0.0      1   2283.0  217.0  532.0   \n",
              "2        5879.0  2011    1  공항동    0.0      1   2283.0  217.0  532.0   \n",
              "3        6192.0  2010    6  공항동    0.0      1   2175.0  246.0  495.0   \n",
              "4        6192.0  2010    7  공항동    0.0      1   2175.0  246.0  495.0   \n",
              "...         ...   ...  ...  ...    ...    ...      ...    ...    ...   \n",
              "92609  110992.0  2019   10  강일동    0.0      1   4527.0  589.0  627.0   \n",
              "92610  111610.0  2011    8  강일동    0.0      1   3109.0  256.0  310.0   \n",
              "92611  111610.0  2011    9  강일동    0.0      1   3109.0  256.0  310.0   \n",
              "92612  111610.0  2015    3  강일동    0.0      2   3759.0  429.0  428.0   \n",
              "92613  111610.0  2019   10  강일동    0.0      1   4527.0  589.0  627.0   \n",
              "\n",
              "       독거노인수_기초생활보장수급권자  ...  냉동불고기_가격차이_100g  냉장불고기_가격차이_100g    모범업소와의 거리  \\\n",
              "0                  87.0  ...           3163.0           2889.0  8517.740954   \n",
              "1                 102.0  ...           2410.0           1829.0  5331.239728   \n",
              "2                 102.0  ...           2410.0           1829.0  5942.053610   \n",
              "3                  87.0  ...           3163.0           2889.0  7759.830956   \n",
              "4                  87.0  ...           2787.0           2454.0  7759.830956   \n",
              "...                 ...  ...              ...              ...          ...   \n",
              "92609             159.0  ...           2692.0           2223.0  7301.190220   \n",
              "92610              44.0  ...           1904.0           1126.0  2642.290162   \n",
              "92611              44.0  ...           2218.0           1582.0  2642.290162   \n",
              "92612              71.0  ...           2152.0           1134.0   955.504602   \n",
              "92613             159.0  ...           2692.0           2223.0  6315.950726   \n",
              "\n",
              "          관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  총적발건수  \n",
              "0      3900.057991  4668.864521   0   0   0   0    0.0  \n",
              "1      2841.434788  2867.345386   0   0   0   0    0.0  \n",
              "2      2352.696260  2340.621779   0   0   0   0    0.0  \n",
              "3      1851.104842  2444.678466   0   0   0   0    0.0  \n",
              "4      1851.104842  2444.678466   0   0   0   0    0.0  \n",
              "...            ...          ...  ..  ..  ..  ..    ...  \n",
              "92609   884.021012  1224.179893   0   0   0   4    0.0  \n",
              "92610  1327.471248  2369.320204   0   0   0   0    0.0  \n",
              "92611  1327.471248  2369.320204   0   0   0   0    0.0  \n",
              "92612  1327.471248   948.801329   0   0   0   0    0.0  \n",
              "92613  1327.471248   959.702931   0   0   0   0    0.0  \n",
              "\n",
              "[92614 rows x 40 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k4buQzO0wKHV",
        "outputId": "e379023c-5500-49a0-e9bd-63855e3d0336"
      },
      "source": [
        "scaler_x = MinMaxScaler(feature_range=(0,1)) # normalize the features\n",
        "scaler_x.fit(data2.iloc[:, 4:])\n",
        "data2_scaled = scaler_x.transform(data2.iloc[:, 4:])\n",
        "data2_scaled"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.        , 0.01923077, 0.26425397, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       [0.        , 0.00480769, 0.27796825, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       [0.        , 0.00480769, 0.27796825, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       ...,\n",
              "       [0.        , 0.00480769, 0.38285714, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       [0.        , 0.00961538, 0.46539683, ..., 0.        , 0.        ,\n",
              "        0.        ],\n",
              "       [0.        , 0.00480769, 0.56292063, ..., 0.        , 0.        ,\n",
              "        0.        ]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qk-39XdPwKHX",
        "outputId": "8cfcfa20-9245-43aa-a860-842a26288d6f"
      },
      "source": [
        "data2_scaled.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(92614, 36)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "seYvOPHCwKHa",
        "outputId": "ae91aab2-59bb-49a2-a846-1573e6665a05"
      },
      "source": [
        "data2.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id', '조사년도', '조사월', '행정동', '재적발건수', '미적발건수', '65세이상인구', '총수급자',\n",
              "       '독거노인수', '독거노인수_기초생활보장수급권자', '독거노인수_저소득', '한국총인구', '외국인인구', '음식점업',\n",
              "       '도소매업', '식품제조업(가공)', '업태누락', '쇠고기냉장_수량_톤', '쇠고기냉동_수량_톤', '돼지고기냉장_수량_톤',\n",
              "       '돼지고기냉동_수량_톤', '닭고기_수량_톤', '쇠고기가격_도매', '쇠고기가격_소매', '돼지고기가격_도매',\n",
              "       '돼지고기가격_소매', '닭고기가격_도매', '닭고기가격_소매', '냉동갈비_가격차이_100g', '냉장갈비_가격차이_100g',\n",
              "       '냉동불고기_가격차이_100g', '냉장불고기_가격차이_100g', '모범업소와의 거리', '관공서와의 거리',\n",
              "       '적발지점과의 거리', 'Q1', 'Q2', 'Q3', 'Q4', '총적발건수'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "qwjbEgClwKHg",
        "outputId": "b3640a54-dc4a-4c9a-adb2-78797efb4df2"
      },
      "source": [
        "# grid의 id와 행정동 2가지가 모두 중복되는 것만 나타내기\n",
        "unique_input = data2.drop_duplicates(['id','행정동'])\n",
        "unique_input"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>조사년도</th>\n",
              "      <th>조사월</th>\n",
              "      <th>행정동</th>\n",
              "      <th>재적발건수</th>\n",
              "      <th>미적발건수</th>\n",
              "      <th>65세이상인구</th>\n",
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              "      <th>독거노인수</th>\n",
              "      <th>독거노인수_기초생활보장수급권자</th>\n",
              "      <th>...</th>\n",
              "      <th>냉동불고기_가격차이_100g</th>\n",
              "      <th>냉장불고기_가격차이_100g</th>\n",
              "      <th>모범업소와의 거리</th>\n",
              "      <th>관공서와의 거리</th>\n",
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              "      <th>Q1</th>\n",
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              "      <th>0</th>\n",
              "      <td>162.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
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              "      <th>1</th>\n",
              "      <td>4397.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2283.0</td>\n",
              "      <td>217.0</td>\n",
              "      <td>532.0</td>\n",
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              "      <td>5879.0</td>\n",
              "      <td>2011</td>\n",
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              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2283.0</td>\n",
              "      <td>217.0</td>\n",
              "      <td>532.0</td>\n",
              "      <td>102.0</td>\n",
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              "      <th>3</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
              "      <td>7759.830956</td>\n",
              "      <td>1851.104842</td>\n",
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              "      <th>5</th>\n",
              "      <td>7393.0</td>\n",
              "      <td>2010</td>\n",
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              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
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              "      <td>248.0</td>\n",
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              "      <td>2508.0</td>\n",
              "      <td>2493.607680</td>\n",
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              "    <tr>\n",
              "      <th>92604</th>\n",
              "      <td>110401.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
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              "      <td>1897.0</td>\n",
              "      <td>177.0</td>\n",
              "      <td>248.0</td>\n",
              "      <td>43.0</td>\n",
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              "    <tr>\n",
              "      <th>92606</th>\n",
              "      <td>110988.0</td>\n",
              "      <td>2018</td>\n",
              "      <td>8</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>4333.0</td>\n",
              "      <td>543.0</td>\n",
              "      <td>536.0</td>\n",
              "      <td>176.0</td>\n",
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              "      <td>110992.0</td>\n",
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              "      <td>5</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2</td>\n",
              "      <td>3109.0</td>\n",
              "      <td>256.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1843.0</td>\n",
              "      <td>1373.0</td>\n",
              "      <td>2405.038107</td>\n",
              "      <td>884.021012</td>\n",
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              "    <tr>\n",
              "      <th>92610</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>8</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>3109.0</td>\n",
              "      <td>256.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1904.0</td>\n",
              "      <td>1126.0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>16235 rows × 40 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  조사년도  조사월  행정동  재적발건수  미적발건수  65세이상인구   총수급자  독거노인수  \\\n",
              "0         162.0  2010    6  공항동    0.0      4   2175.0  246.0  495.0   \n",
              "1        4397.0  2011    1  공항동    0.0      1   2283.0  217.0  532.0   \n",
              "2        5879.0  2011    1  공항동    0.0      1   2283.0  217.0  532.0   \n",
              "3        6192.0  2010    6  공항동    0.0      1   2175.0  246.0  495.0   \n",
              "5        7393.0  2010    7  공항동    0.0      1   2175.0  246.0  495.0   \n",
              "...         ...   ...  ...  ...    ...    ...      ...    ...    ...   \n",
              "92600  110381.0  2010    8  강일동    0.0      1   1897.0  177.0  248.0   \n",
              "92604  110401.0  2010    6  강일동    0.0      1   1897.0  177.0  248.0   \n",
              "92606  110988.0  2018    8  강일동    0.0      1   4333.0  543.0  536.0   \n",
              "92607  110992.0  2011    5  강일동    0.0      2   3109.0  256.0  310.0   \n",
              "92610  111610.0  2011    8  강일동    0.0      1   3109.0  256.0  310.0   \n",
              "\n",
              "       독거노인수_기초생활보장수급권자  ...  냉동불고기_가격차이_100g  냉장불고기_가격차이_100g    모범업소와의 거리  \\\n",
              "0                  87.0  ...           3163.0           2889.0  8517.740954   \n",
              "1                 102.0  ...           2410.0           1829.0  5331.239728   \n",
              "2                 102.0  ...           2410.0           1829.0  5942.053610   \n",
              "3                  87.0  ...           3163.0           2889.0  7759.830956   \n",
              "5                  87.0  ...           2787.0           2454.0  7635.786943   \n",
              "...                 ...  ...              ...              ...          ...   \n",
              "92600              43.0  ...           3050.0           2508.0  2493.607680   \n",
              "92604              43.0  ...           3163.0           2889.0  2242.796490   \n",
              "92606             176.0  ...           2645.0           2224.0  7406.116592   \n",
              "92607              44.0  ...           1843.0           1373.0  2405.038107   \n",
              "92610              44.0  ...           1904.0           1126.0  2642.290162   \n",
              "\n",
              "          관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  총적발건수  \n",
              "0      3900.057991  4668.864521   0   0   0   0    0.0  \n",
              "1      2841.434788  2867.345386   0   0   0   0    0.0  \n",
              "2      2352.696260  2340.621779   0   0   0   0    0.0  \n",
              "3      1851.104842  2444.678466   0   0   0   0    0.0  \n",
              "5      1714.559216  1869.793401   0   0   0   0    0.0  \n",
              "...            ...          ...  ..  ..  ..  ..    ...  \n",
              "92600   420.708348  4053.119685   0   0   0   0    0.0  \n",
              "92604   929.271559  3065.501023   0   0   0   0    0.0  \n",
              "92606   658.719915  1468.376806   0   0   0   0    0.0  \n",
              "92607   884.021012  2153.817367   0   0   0   0    0.0  \n",
              "92610  1327.471248  2369.320204   0   0   0   0    0.0  \n",
              "\n",
              "[16235 rows x 40 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9rWdBQiPwKHj"
      },
      "source": [
        "# grid id, 조사년도, 조사월을 기준으로 정렬했을 때의 순서로 행정동 리스트 저장\n",
        "with open('dong_list.pkl', 'wb') as f:\n",
        "    pickle.dump(unique_input['행정동'].values.reshape(16235,1), f)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ptzj6M3JwKHl"
      },
      "source": [
        "# grid id, 조사년도, 조사월을 기준으로 정렬했을 때의 순서로 grid id 리스트 저장\n",
        "np.save('grid_id_list.npy',unique_input['id'].values.astype(np.int32))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6oClYu6EwKHn",
        "outputId": "cfe11981-d916-4227-ad25-607b74fa2abc"
      },
      "source": [
        "# 확인용(grid별로 조사나간 횟수가 얼마나 되는지)\n",
        "temp_df = data2.groupby(['id', '행정동'], as_index=True).count().sort_values(by=['조사년도', '조사월'], ascending=False)\n",
        "temp_df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>조사년도</th>\n",
              "      <th>조사월</th>\n",
              "      <th>재적발건수</th>\n",
              "      <th>미적발건수</th>\n",
              "      <th>65세이상인구</th>\n",
              "      <th>총수급자</th>\n",
              "      <th>독거노인수</th>\n",
              "      <th>독거노인수_기초생활보장수급권자</th>\n",
              "      <th>독거노인수_저소득</th>\n",
              "      <th>한국총인구</th>\n",
              "      <th>...</th>\n",
              "      <th>냉동불고기_가격차이_100g</th>\n",
              "      <th>냉장불고기_가격차이_100g</th>\n",
              "      <th>모범업소와의 거리</th>\n",
              "      <th>관공서와의 거리</th>\n",
              "      <th>적발지점과의 거리</th>\n",
              "      <th>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>총적발건수</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>id</th>\n",
              "      <th>행정동</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>92038.0</th>\n",
              "      <th>가락1동</th>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>...</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "      <td>106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73220.0</th>\n",
              "      <th>제기동</th>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>...</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73218.0</th>\n",
              "      <th>제기동</th>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>...</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "      <td>70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73522.0</th>\n",
              "      <th>제기동</th>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>...</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74556.0</th>\n",
              "      <th>양재2동</th>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>...</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "      <td>68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108591.0</th>\n",
              "      <th>상일동</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109181.0</th>\n",
              "      <th>강일동</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109191.0</th>\n",
              "      <th>상일동</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109192.0</th>\n",
              "      <th>상일동</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110988.0</th>\n",
              "      <th>강일동</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16235 rows × 38 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               조사년도  조사월  재적발건수  미적발건수  65세이상인구  총수급자  독거노인수  \\\n",
              "id       행정동                                                   \n",
              "92038.0  가락1동   106  106    106    106      106   106    106   \n",
              "73220.0  제기동    101  101    101    101      101   101    101   \n",
              "73218.0  제기동     70   70     70     70       70    70     70   \n",
              "73522.0  제기동     68   68     68     68       68    68     68   \n",
              "74556.0  양재2동    68   68     68     68       68    68     68   \n",
              "...             ...  ...    ...    ...      ...   ...    ...   \n",
              "108591.0 상일동      1    1      1      1        1     1      1   \n",
              "109181.0 강일동      1    1      1      1        1     1      1   \n",
              "109191.0 상일동      1    1      1      1        1     1      1   \n",
              "109192.0 상일동      1    1      1      1        1     1      1   \n",
              "110988.0 강일동      1    1      1      1        1     1      1   \n",
              "\n",
              "               독거노인수_기초생활보장수급권자  독거노인수_저소득  한국총인구  ...  냉동불고기_가격차이_100g  \\\n",
              "id       행정동                                       ...                    \n",
              "92038.0  가락1동               106        106    106  ...              106   \n",
              "73220.0  제기동                101        101    101  ...              101   \n",
              "73218.0  제기동                 70         70     70  ...               70   \n",
              "73522.0  제기동                 68         68     68  ...               68   \n",
              "74556.0  양재2동                68         68     68  ...               68   \n",
              "...                         ...        ...    ...  ...              ...   \n",
              "108591.0 상일동                  1          1      1  ...                1   \n",
              "109181.0 강일동                  1          1      1  ...                1   \n",
              "109191.0 상일동                  1          1      1  ...                1   \n",
              "109192.0 상일동                  1          1      1  ...                1   \n",
              "110988.0 강일동                  1          1      1  ...                1   \n",
              "\n",
              "               냉장불고기_가격차이_100g  모범업소와의 거리  관공서와의 거리  적발지점과의 거리   Q1   Q2   Q3  \\\n",
              "id       행정동                                                                    \n",
              "92038.0  가락1동              106        106       106        106  106  106  106   \n",
              "73220.0  제기동               101        101       101        101  101  101  101   \n",
              "73218.0  제기동                70         70        70         70   70   70   70   \n",
              "73522.0  제기동                68         68        68         68   68   68   68   \n",
              "74556.0  양재2동               68         68        68         68   68   68   68   \n",
              "...                        ...        ...       ...        ...  ...  ...  ...   \n",
              "108591.0 상일동                 1          1         1          1    1    1    1   \n",
              "109181.0 강일동                 1          1         1          1    1    1    1   \n",
              "109191.0 상일동                 1          1         1          1    1    1    1   \n",
              "109192.0 상일동                 1          1         1          1    1    1    1   \n",
              "110988.0 강일동                 1          1         1          1    1    1    1   \n",
              "\n",
              "                Q4  총적발건수  \n",
              "id       행정동               \n",
              "92038.0  가락1동  106    106  \n",
              "73220.0  제기동   101    101  \n",
              "73218.0  제기동    70     70  \n",
              "73522.0  제기동    68     68  \n",
              "74556.0  양재2동   68     68  \n",
              "...            ...    ...  \n",
              "108591.0 상일동     1      1  \n",
              "109181.0 강일동     1      1  \n",
              "109191.0 상일동     1      1  \n",
              "109192.0 상일동     1      1  \n",
              "110988.0 강일동     1      1  \n",
              "\n",
              "[16235 rows x 38 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xo2QVHuzwKHp"
      },
      "source": [
        "def length_adjust(str_) :                   # if month, day is single number, convert to two-numbers (ex. 6 → 06, 7 → 07)\n",
        "    return (2-len(str_)) * '0' + str_ \n",
        "\n",
        "def date_convertor(date) :                  # ex. '2010-01-01' → '20100101'\n",
        "    year = length_adjust(str(date.year))\n",
        "    month = length_adjust(str(date.month))\n",
        "    yyyymm = year+month\n",
        "    return yyyymm                       # return 'str' type\n",
        "\n",
        "year_month = pd.date_range(start='20100101', end='20191231', freq='M')  # 20100101 ~ 20191231의 날짜를 월 단위로 생성(201001, 201002, ..., 201912)\n",
        "year_month = list(map(date_convertor, year_month))  # len(year_month) : 120\n",
        "temp_columns = data2.columns[4:]  # 36"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NJbJkL24wKHs"
      },
      "source": [
        "#### 각각의 고유한 grid마다 'master_tabel_1' ~ 'master_table_16235'라는 변수를 생성하여 index는 20100101 ~ 20191231의 날짜, column은 변수인 데이터프레임을 지정해준다."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PepTWR_jwKHt"
      },
      "source": [
        "# columns 36개, Y값 1개\n",
        "for i in range(16235):  # 고유한 grid 개수\n",
        "    globals()['master_table_{}'.format(i+1)] = pd.DataFrame(np.full(shape = (len(year_month), len(temp_columns)), fill_value=-1), index = year_month, columns = temp_columns)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bGcKLBqrwKHw",
        "outputId": "da03c5e8-8698-4bcd-eb85-821714c9f55d"
      },
      "source": [
        "master_table_1"
      ],
      "execution_count": null,
      "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>재적발건수</th>\n",
              "      <th>미적발건수</th>\n",
              "      <th>65세이상인구</th>\n",
              "      <th>총수급자</th>\n",
              "      <th>독거노인수</th>\n",
              "      <th>독거노인수_기초생활보장수급권자</th>\n",
              "      <th>독거노인수_저소득</th>\n",
              "      <th>한국총인구</th>\n",
              "      <th>외국인인구</th>\n",
              "      <th>음식점업</th>\n",
              "      <th>...</th>\n",
              "      <th>냉동불고기_가격차이_100g</th>\n",
              "      <th>냉장불고기_가격차이_100g</th>\n",
              "      <th>모범업소와의 거리</th>\n",
              "      <th>관공서와의 거리</th>\n",
              "      <th>적발지점과의 거리</th>\n",
              "      <th>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>총적발건수</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>201001</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201002</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201003</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201004</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201005</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201908</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201909</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201910</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201911</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201912</th>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>...</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>120 rows × 36 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        재적발건수  미적발건수  65세이상인구  총수급자  독거노인수  독거노인수_기초생활보장수급권자  독거노인수_저소득  \\\n",
              "201001     -1     -1       -1    -1     -1                -1         -1   \n",
              "201002     -1     -1       -1    -1     -1                -1         -1   \n",
              "201003     -1     -1       -1    -1     -1                -1         -1   \n",
              "201004     -1     -1       -1    -1     -1                -1         -1   \n",
              "201005     -1     -1       -1    -1     -1                -1         -1   \n",
              "...       ...    ...      ...   ...    ...               ...        ...   \n",
              "201908     -1     -1       -1    -1     -1                -1         -1   \n",
              "201909     -1     -1       -1    -1     -1                -1         -1   \n",
              "201910     -1     -1       -1    -1     -1                -1         -1   \n",
              "201911     -1     -1       -1    -1     -1                -1         -1   \n",
              "201912     -1     -1       -1    -1     -1                -1         -1   \n",
              "\n",
              "        한국총인구  외국인인구  음식점업  ...  냉동불고기_가격차이_100g  냉장불고기_가격차이_100g  모범업소와의 거리  \\\n",
              "201001     -1     -1    -1  ...               -1               -1         -1   \n",
              "201002     -1     -1    -1  ...               -1               -1         -1   \n",
              "201003     -1     -1    -1  ...               -1               -1         -1   \n",
              "201004     -1     -1    -1  ...               -1               -1         -1   \n",
              "201005     -1     -1    -1  ...               -1               -1         -1   \n",
              "...       ...    ...   ...  ...              ...              ...        ...   \n",
              "201908     -1     -1    -1  ...               -1               -1         -1   \n",
              "201909     -1     -1    -1  ...               -1               -1         -1   \n",
              "201910     -1     -1    -1  ...               -1               -1         -1   \n",
              "201911     -1     -1    -1  ...               -1               -1         -1   \n",
              "201912     -1     -1    -1  ...               -1               -1         -1   \n",
              "\n",
              "        관공서와의 거리  적발지점과의 거리  Q1  Q2  Q3  Q4  총적발건수  \n",
              "201001        -1         -1  -1  -1  -1  -1     -1  \n",
              "201002        -1         -1  -1  -1  -1  -1     -1  \n",
              "201003        -1         -1  -1  -1  -1  -1     -1  \n",
              "201004        -1         -1  -1  -1  -1  -1     -1  \n",
              "201005        -1         -1  -1  -1  -1  -1     -1  \n",
              "...          ...        ...  ..  ..  ..  ..    ...  \n",
              "201908        -1         -1  -1  -1  -1  -1     -1  \n",
              "201909        -1         -1  -1  -1  -1  -1     -1  \n",
              "201910        -1         -1  -1  -1  -1  -1     -1  \n",
              "201911        -1         -1  -1  -1  -1  -1     -1  \n",
              "201912        -1         -1  -1  -1  -1  -1     -1  \n",
              "\n",
              "[120 rows x 36 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oMbHsAN2wKHy"
      },
      "source": [
        "# 3. X값 만들기"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k8AugiFZwKHz"
      },
      "source": [
        "### 2차원 X값 먼저 만들기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OFx9yZ8zwKH0",
        "outputId": "5fd915bf-392d-4d1f-8e20-63c1ca507703"
      },
      "source": [
        "%%time\n",
        "total_input = []   \n",
        "for i in range(16235):  # 고유한 grid 개수\n",
        "    print('Process : {} | Total : 16235'.format(i+1), end='\\r')\n",
        "    master_table_clip = globals()['master_table_{}'.format(i+1)]   # master_table 1개씩 master_table_clip 변수에 저장\n",
        "    clip = data2[(data2['id']==unique_input['id'].iloc[i])&(data2['행정동']==unique_input['행정동'].iloc[i])]   # 고유한 grid id, 행정동에 맞는 데이터들을 clip 변수에 저장\n",
        "    for j in range(len(clip)):  # clip의 행의 개수\n",
        "        mm = length_adjust(str(clip.iloc[j,2]))  # 조사월 형태 맞추기(ex. 6 → 06, 7 → 07)\n",
        "        ym = str(clip.iloc[j,1]) + mm    # (ex. 2010 + 01 → 201001)\n",
        "        master_table_clip.loc[ym, :] = data2_scaled[clip.index[j]]    # scaling한 X_column의 값\n",
        "    total_input.append(master_table_clip.values[:108, :])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Wall time: 13min 26stal : 16235\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4v4J2jiFwKH2",
        "outputId": "b296f643-b4f9-4556-95ee-7d4373eb6877"
      },
      "source": [
        "len(total_input)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16235"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0CjnGc1uwKH5"
      },
      "source": [
        "## 2차원으로 되어있는 total_input을 3차원으로 쌓기 위해 array를 쌓는 작업"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4jTCC0_AwKH6",
        "outputId": "12ba3ba2-5f64-427f-fa61-b6661a90bf2b"
      },
      "source": [
        "%%time\n",
        "\n",
        "total_input_stacked = total_input[0]\n",
        "for s in range(len(total_input)-1):\n",
        "    print('process:{}'.format(s+1), end='\\r')\n",
        "    total_input_stacked = np.vstack((total_input_stacked, total_input[s+1]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Wall time: 35min 33s\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ORDl3dEKwKH-",
        "outputId": "27bb98ef-4a3e-43d3-dc6b-36af80b436c0"
      },
      "source": [
        "real_total_input = total_input_stacked.reshape(-1, 108, 36)\n",
        "real_total_input.ndim"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DOXl_QIFwKIB",
        "outputId": "9ec9ba8f-aa74-4d48-c45a-5a14642ad1f1"
      },
      "source": [
        "real_total_input.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(16235, 108, 36)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Tss1dCXvwKID"
      },
      "source": [
        "# array save\n",
        "np.save(\"Deep_input_X_scaled_full_36.npy\", real_total_input)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6Hh5_LtbwKIF",
        "outputId": "e95d45cb-cbf7-4965-e32b-d77b7c0b067b"
      },
      "source": [
        "# load\n",
        "x = np.load(\"Deep_input_X_scaled_full_36.npy\")\n",
        "x.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(16235, 108, 36)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qmcrIzfmwKIH"
      },
      "source": [
        "# X에 NaN값이 있는지 확인"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y_Xgw4BWwKII"
      },
      "source": [
        "for i in range(16235):  # 고유한 grid 개수\n",
        "    master_table_clip = globals()['master_table_{}'.format(i+1)]\n",
        "    if master_table_clip.isnull().values.any() == True:\n",
        "        print(i, True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r4n3SFpowKIM"
      },
      "source": [
        "# 4. Y값 만들기\n",
        "### 2019년 적발건수"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z_1_ftt0wKIN",
        "outputId": "b73b59d0-378f-41cb-da9c-9dad0ad3ff9a"
      },
      "source": [
        "data2 = pd.read_csv('최종_데이터프레임_데이터정제.csv', encoding='cp949', index_col=0)\n",
        "data2"
      ],
      "execution_count": null,
      "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>조사년도</th>\n",
              "      <th>조사월</th>\n",
              "      <th>행정동</th>\n",
              "      <th>재적발건수</th>\n",
              "      <th>미적발건수</th>\n",
              "      <th>65세이상인구</th>\n",
              "      <th>총수급자</th>\n",
              "      <th>독거노인수</th>\n",
              "      <th>독거노인수_기초생활보장수급권자</th>\n",
              "      <th>...</th>\n",
              "      <th>냉동불고기_가격차이_100g</th>\n",
              "      <th>냉장불고기_가격차이_100g</th>\n",
              "      <th>모범업소와의 거리</th>\n",
              "      <th>관공서와의 거리</th>\n",
              "      <th>적발지점과의 거리</th>\n",
              "      <th>Q1</th>\n",
              "      <th>Q2</th>\n",
              "      <th>Q3</th>\n",
              "      <th>Q4</th>\n",
              "      <th>총적발건수</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>162.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
              "      <td>8517.740954</td>\n",
              "      <td>3900.057991</td>\n",
              "      <td>4668.864521</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4397.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2283.0</td>\n",
              "      <td>217.0</td>\n",
              "      <td>532.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2410.0</td>\n",
              "      <td>1829.0</td>\n",
              "      <td>5331.239728</td>\n",
              "      <td>2841.434788</td>\n",
              "      <td>2867.345386</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5879.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2283.0</td>\n",
              "      <td>217.0</td>\n",
              "      <td>532.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2410.0</td>\n",
              "      <td>1829.0</td>\n",
              "      <td>5942.053610</td>\n",
              "      <td>2352.696260</td>\n",
              "      <td>2340.621779</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>3163.0</td>\n",
              "      <td>2889.0</td>\n",
              "      <td>7759.830956</td>\n",
              "      <td>1851.104842</td>\n",
              "      <td>2444.678466</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>7</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2175.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>495.0</td>\n",
              "      <td>87.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2787.0</td>\n",
              "      <td>2454.0</td>\n",
              "      <td>7759.830956</td>\n",
              "      <td>1851.104842</td>\n",
              "      <td>2444.678466</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92609</th>\n",
              "      <td>110992.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>4527.0</td>\n",
              "      <td>589.0</td>\n",
              "      <td>627.0</td>\n",
              "      <td>159.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2692.0</td>\n",
              "      <td>2223.0</td>\n",
              "      <td>7301.190220</td>\n",
              "      <td>884.021012</td>\n",
              "      <td>1224.179893</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92610</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>8</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>3109.0</td>\n",
              "      <td>256.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1904.0</td>\n",
              "      <td>1126.0</td>\n",
              "      <td>2642.290162</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>2369.320204</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92611</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>9</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>3109.0</td>\n",
              "      <td>256.0</td>\n",
              "      <td>310.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2218.0</td>\n",
              "      <td>1582.0</td>\n",
              "      <td>2642.290162</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>2369.320204</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92612</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>3</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2</td>\n",
              "      <td>3759.0</td>\n",
              "      <td>429.0</td>\n",
              "      <td>428.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2152.0</td>\n",
              "      <td>1134.0</td>\n",
              "      <td>955.504602</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>948.801329</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92613</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1</td>\n",
              "      <td>4527.0</td>\n",
              "      <td>589.0</td>\n",
              "      <td>627.0</td>\n",
              "      <td>159.0</td>\n",
              "      <td>...</td>\n",
              "      <td>2692.0</td>\n",
              "      <td>2223.0</td>\n",
              "      <td>6315.950726</td>\n",
              "      <td>1327.471248</td>\n",
              "      <td>959.702931</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>92614 rows × 40 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  조사년도  조사월  행정동  재적발건수  미적발건수  65세이상인구   총수급자  독거노인수  \\\n",
              "0         162.0  2010    6  공항동    0.0      4   2175.0  246.0  495.0   \n",
              "1        4397.0  2011    1  공항동    0.0      1   2283.0  217.0  532.0   \n",
              "2        5879.0  2011    1  공항동    0.0      1   2283.0  217.0  532.0   \n",
              "3        6192.0  2010    6  공항동    0.0      1   2175.0  246.0  495.0   \n",
              "4        6192.0  2010    7  공항동    0.0      1   2175.0  246.0  495.0   \n",
              "...         ...   ...  ...  ...    ...    ...      ...    ...    ...   \n",
              "92609  110992.0  2019   10  강일동    0.0      1   4527.0  589.0  627.0   \n",
              "92610  111610.0  2011    8  강일동    0.0      1   3109.0  256.0  310.0   \n",
              "92611  111610.0  2011    9  강일동    0.0      1   3109.0  256.0  310.0   \n",
              "92612  111610.0  2015    3  강일동    0.0      2   3759.0  429.0  428.0   \n",
              "92613  111610.0  2019   10  강일동    0.0      1   4527.0  589.0  627.0   \n",
              "\n",
              "       독거노인수_기초생활보장수급권자  ...  냉동불고기_가격차이_100g  냉장불고기_가격차이_100g    모범업소와의 거리  \\\n",
              "0                  87.0  ...           3163.0           2889.0  8517.740954   \n",
              "1                 102.0  ...           2410.0           1829.0  5331.239728   \n",
              "2                 102.0  ...           2410.0           1829.0  5942.053610   \n",
              "3                  87.0  ...           3163.0           2889.0  7759.830956   \n",
              "4                  87.0  ...           2787.0           2454.0  7759.830956   \n",
              "...                 ...  ...              ...              ...          ...   \n",
              "92609             159.0  ...           2692.0           2223.0  7301.190220   \n",
              "92610              44.0  ...           1904.0           1126.0  2642.290162   \n",
              "92611              44.0  ...           2218.0           1582.0  2642.290162   \n",
              "92612              71.0  ...           2152.0           1134.0   955.504602   \n",
              "92613             159.0  ...           2692.0           2223.0  6315.950726   \n",
              "\n",
              "          관공서와의 거리    적발지점과의 거리  Q1  Q2  Q3  Q4  총적발건수  \n",
              "0      3900.057991  4668.864521   0   0   0   0    0.0  \n",
              "1      2841.434788  2867.345386   0   0   0   0    0.0  \n",
              "2      2352.696260  2340.621779   0   0   0   0    0.0  \n",
              "3      1851.104842  2444.678466   0   0   0   0    0.0  \n",
              "4      1851.104842  2444.678466   0   0   0   0    0.0  \n",
              "...            ...          ...  ..  ..  ..  ..    ...  \n",
              "92609   884.021012  1224.179893   0   0   0   4    0.0  \n",
              "92610  1327.471248  2369.320204   0   0   0   0    0.0  \n",
              "92611  1327.471248  2369.320204   0   0   0   0    0.0  \n",
              "92612  1327.471248   948.801329   0   0   0   0    0.0  \n",
              "92613  1327.471248   959.702931   0   0   0   0    0.0  \n",
              "\n",
              "[92614 rows x 40 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "daZ8SG85wKIQ",
        "outputId": "10e102ba-80cd-485c-9c42-57e87a741772"
      },
      "source": [
        "# Y(적발건수) 만드는 버전\n",
        "data2 = data2[['id', '조사년도', '조사월', '행정동',\n",
        "               '총적발건수']]\n",
        "data2"
      ],
      "execution_count": null,
      "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",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>조사년도</th>\n",
              "      <th>조사월</th>\n",
              "      <th>행정동</th>\n",
              "      <th>총적발건수</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>162.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4397.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5879.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>1</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>6</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6192.0</td>\n",
              "      <td>2010</td>\n",
              "      <td>7</td>\n",
              "      <td>공항동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92609</th>\n",
              "      <td>110992.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92610</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>8</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92611</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2011</td>\n",
              "      <td>9</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92612</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>3</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92613</th>\n",
              "      <td>111610.0</td>\n",
              "      <td>2019</td>\n",
              "      <td>10</td>\n",
              "      <td>강일동</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>92614 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  조사년도  조사월  행정동  총적발건수\n",
              "0         162.0  2010    6  공항동    0.0\n",
              "1        4397.0  2011    1  공항동    0.0\n",
              "2        5879.0  2011    1  공항동    0.0\n",
              "3        6192.0  2010    6  공항동    0.0\n",
              "4        6192.0  2010    7  공항동    0.0\n",
              "...         ...   ...  ...  ...    ...\n",
              "92609  110992.0  2019   10  강일동    0.0\n",
              "92610  111610.0  2011    8  강일동    0.0\n",
              "92611  111610.0  2011    9  강일동    0.0\n",
              "92612  111610.0  2015    3  강일동    0.0\n",
              "92613  111610.0  2019   10  강일동    0.0\n",
              "\n",
              "[92614 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UXsMciaJwKIU",
        "outputId": "853304d1-bb15-42cb-958d-1bf5e5636fbe"
      },
      "source": [
        "data2['총적발건수'].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0.,  1.,  2.,  4.,  3.,  5., 13., 12.,  8., 15.,  9., 10.,  6.])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0SSmgzIowKIW",
        "outputId": "32319748-8d15-487d-d645-d87a8a3370d6"
      },
      "source": [
        "def length_adjust(str_) :                   # if month, day is single number, convert to two-numbers (ex. 6 → 06, 7 → 07)\n",
        "    return (2-len(str_)) * '0' + str_ \n",
        "\n",
        "def date_convertor(date) :                  # ex. '2010-01-01' → '20100101'\n",
        "    year = length_adjust(str(date.year))\n",
        "    month = length_adjust(str(date.month))\n",
        "    yyyymm = year+month\n",
        "    return yyyymm                       # return 'str' type\n",
        "\n",
        "year_month = pd.date_range(start='20100101', end='20191231', freq='M')  # 20100101 ~ 20191231의 날짜를 월 단위로 생성(201001, 201002, ..., 201912)\n",
        "year_month = list(map(date_convertor, year_month))  # len(year_month) : 120\n",
        "temp_columns = data2.columns[4:]  # 1\n",
        "temp_columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['총적발건수'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CUT0B-QtwKIb"
      },
      "source": [
        "#### 각각의 고유한 grid마다 'master_tabel_1' ~ 'master_table_16235'라는 변수를 생성하여 index는 20100101 ~ 20191231의 날짜, column은 변수인 데이터프레임을 지정해준다."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a9aUA1EywKIc"
      },
      "source": [
        "for i in range(16235):  # 고유한 grid 개수\n",
        "    globals()['master_table_{}'.format(i+1)] = pd.DataFrame(np.full(shape = (len(year_month), len(temp_columns)), fill_value=-1), index = year_month, columns = temp_columns)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pTS6HT7nwKIf",
        "outputId": "8557fd8f-f0b1-4518-8903-fa8b125d3a71"
      },
      "source": [
        "master_table_1"
      ],
      "execution_count": null,
      "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>총적발건수</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>201001</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201002</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201003</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201004</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201005</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201908</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201909</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201910</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201911</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201912</th>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>120 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        총적발건수\n",
              "201001     -1\n",
              "201002     -1\n",
              "201003     -1\n",
              "201004     -1\n",
              "201005     -1\n",
              "...       ...\n",
              "201908     -1\n",
              "201909     -1\n",
              "201910     -1\n",
              "201911     -1\n",
              "201912     -1\n",
              "\n",
              "[120 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WK8bwB7OwKIi",
        "outputId": "64ae2aac-8bc8-4201-ee4e-4ab7c6571869"
      },
      "source": [
        "%%time\n",
        "# scaling하지 않고 데이터프레임에서 값 가져오기\n",
        "for i in range(16235):  # 고유한 grid 개수\n",
        "    print('Process : {} | Total : 16235'.format(i+1), end='\\r')\n",
        "    master_table_clip = globals()['master_table_{}'.format(i+1)]   # master_table 1개씩 master_table_clip 변수에 저장\n",
        "    clip = data2[(data2['id']==unique_input['id'].iloc[i])&(data2['행정동']==unique_input['행정동'].iloc[i])]   # 고유한 grid id, 행정동에 맞는 데이터들을 clip 변수에 저장\n",
        "    for j in range(len(clip)):  # clip의 행의 개수\n",
        "        mm = length_adjust(str(clip.iloc[j,2]))  # 조사월 형태 맞추기(ex. 6 → 06, 7 → 07)\n",
        "        ym = str(clip.iloc[j,1]) + mm      # (ex. 2010 + 01 → 201001)\n",
        "        master_table_clip.loc[ym, :] = clip.values[j][4:]  # 총적발건수 값을 추가"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Wall time: 4min 56sotal : 16235\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fen6b6NDwKIj",
        "outputId": "d0a5b98d-8ab8-4fc2-bbe3-185b603b368c"
      },
      "source": [
        "%%time\n",
        "y_grid = []  # 완성본 \n",
        "\n",
        "for i in range(16235):  # 16235 grid별\n",
        "    sum_ = 0  # 총 적발건수\n",
        "    print('Process : {} | Total : 16235'.format(i+1), end='\\r')\n",
        "    master_table_clip = globals()['master_table_{}'.format(i+1)]\n",
        "    \n",
        "    # 총적발건수 value counts\n",
        "    unique, counts = np.unique(master_table_clip.iloc[-12:, 0].values, return_counts=True)    # 2019년 총적발건수\n",
        "    cnt_dict = dict(zip(unique, counts))   # 2019년 총적발건수 {value : count}\n",
        "    del cnt_dict[-1.0]  # padding값 -1 제거\n",
        "    \n",
        "    # 총 적발건수 count\n",
        "    if len(cnt_dict) == 0:         # padding값 -1밖에 없었다면(모두 결측치라면)\n",
        "        # 각 grid의 2010~2018년 총적발건수 다 더해서, \"조사나간 연도 수\"로 나누기\n",
        "        count = 0  # 조사나간 연도 수\n",
        "        for k in range(9):\n",
        "            master_table_year = master_table_clip.iloc[12*k:12*(k+1), :]  # 1년치만 잘라서\n",
        "            jucval_list = list(master_table_year['총적발건수'].values)\n",
        "            if all(jucval_list) != -1:  # 전체가 padding값 -1이 아니라면,\n",
        "                count += 1              # 조사나간 연도수 count + 1\n",
        "                for char in jucval_list:  # 값을 하나씩 가져와서,\n",
        "                    if char >= 0:         # padding값이 아니라면,\n",
        "                        sum_ += char  # 총 적발건수에 더해주기\n",
        "        y_grid.append(sum_/count)\n",
        "    else:                          # padding값 -1 이외의 값이 있었다면\n",
        "        # 각 grid의 2019년 총적발건수 세기\n",
        "        list_ = []\n",
        "        for a in cnt_dict:\n",
        "            list_.append(a * cnt_dict[a])      # a : 적발건수 unique값 --> unique값에, 해당하는 list_2값 곱해서 다 더해주면 \"총적발건수\"\n",
        "                                               # 즉, a * cnt_dict1[a] 한 것들을 다 더해주면 \"총적발건수\"\n",
        "        sum_ += np.sum(list_)\n",
        "        y_grid.append(sum_)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Wall time: 43.8 s Total : 16235\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WlLvd1g5wKIn",
        "outputId": "f5b5ee29-4b0f-4fa8-f4c3-dc62e3e03fa1"
      },
      "source": [
        "y_grid = np.array(y_grid)\n",
        "y_grid = y_grid.reshape(16235, 1)\n",
        "y_grid.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(16235, 1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uA9xso7UwKIs",
        "outputId": "a3753620-5b71-4f34-cbb1-35a966bf0ad5"
      },
      "source": [
        "y_grid_df = pd.DataFrame(y_grid, columns=['총적발건수'])\n",
        "y_grid_df"
      ],
      "execution_count": null,
      "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>총적발건수</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16230</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16231</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16232</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16233</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16234</th>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>16235 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       총적발건수\n",
              "0        0.0\n",
              "1        0.0\n",
              "2        0.0\n",
              "3        0.0\n",
              "4        0.0\n",
              "...      ...\n",
              "16230    0.0\n",
              "16231    0.0\n",
              "16232    0.0\n",
              "16233    0.0\n",
              "16234    0.0\n",
              "\n",
              "[16235 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TebrvsUQwKIu",
        "outputId": "aded3276-7f4d-414e-f8af-e34c30164098"
      },
      "source": [
        "final_scaler_y = MinMaxScaler(feature_range=(0,1))  # normalize the label\n",
        "final_scaler_y.fit(y_grid_df)\n",
        "y_scaled = final_scaler_y.transform(y_grid_df)\n",
        "y_scaled"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.],\n",
              "       [0.],\n",
              "       [0.],\n",
              "       ...,\n",
              "       [0.],\n",
              "       [0.],\n",
              "       [0.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n-amc5nuwKIz",
        "outputId": "aa582bda-90fd-44d3-980e-7dc2f1ff2195"
      },
      "source": [
        "np.max(y_scaled)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vZ7Z_NeUwKI4",
        "outputId": "18c054b9-f259-4e51-af22-93b3645e0663"
      },
      "source": [
        "y_scaled.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(16235, 1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qSfmdY1twKI8"
      },
      "source": [
        "# array save\n",
        "np.save(\"Deep_input_Y_MSE_scaled.npy\", y_scaled)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vbcG6h8CwKJA"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}