Allstate (Sphia).ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "bghyUVB8IyDg"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "jzXme5cPA8Sn"
      },
      "outputs": [],
      "source": [
        "from sklearn.ensemble import RandomForestClassifier"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "KkpA6esPq_d5"
      },
      "outputs": [],
      "source": [
        "from sklearn.preprocessing import LabelEncoder"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "5SSbdQWHIlVT"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import train_test_split"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "NQHvnEgVQlnn"
      },
      "outputs": [],
      "source": [
        "#from sklearn.linear_model import LogisticRegression"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "U0nOre7ERHVf"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import cross_val_score"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "YARPIFh1OYUf"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import GridSearchCV"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "x6Ii4flIWbGj"
      },
      "outputs": [],
      "source": [
        "# file_id_county_level = '1SKNqdTImQQUq9AjIrmXX0_1a30HZQ-Vm'\n",
        "\n",
        "# down = drive.CreateFile({'id': file_id_county_level})\n",
        "# down.GetContentFile('county_level_population.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "SgO-UBqDU3E8"
      },
      "outputs": [],
      "source": [
        "df_ = pd.read_csv('datasets/fires_2010.csv')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "mhZMewVgXM6L",
        "outputId": "e93146c7-43b8-4227-f094-e63fe30bc077"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>OBJECTID</th>\n",
              "      <th>FOD_ID</th>\n",
              "      <th>FIRE_YEAR</th>\n",
              "      <th>DISCOVERY_DOY</th>\n",
              "      <th>DISCOVERY_TIME</th>\n",
              "      <th>STAT_CAUSE_CODE</th>\n",
              "      <th>CONT_DOY</th>\n",
              "      <th>CONT_TIME</th>\n",
              "      <th>FIRE_SIZE</th>\n",
              "      <th>LATITUDE</th>\n",
              "      <th>LONGITUDE</th>\n",
              "      <th>OWNER_CODE</th>\n",
              "      <th>FIPS_CODE</th>\n",
              "      <th>bbox_xmin</th>\n",
              "      <th>bbox_xmax</th>\n",
              "      <th>bbox_ymin</th>\n",
              "      <th>bbox_ymax</th>\n",
              "      <th>fips_state_cd</th>\n",
              "      <th>county_fips</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>7.988900e+04</td>\n",
              "      <td>7.988900e+04</td>\n",
              "      <td>7.988900e+04</td>\n",
              "      <td>79889.0</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>40257.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>33834.000000</td>\n",
              "      <td>29848.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>63159.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "      <td>79889.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.315363e+06</td>\n",
              "      <td>1.315364e+06</td>\n",
              "      <td>4.377702e+07</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>187.132659</td>\n",
              "      <td>1456.864396</td>\n",
              "      <td>6.358122</td>\n",
              "      <td>199.431489</td>\n",
              "      <td>1514.818514</td>\n",
              "      <td>43.728864</td>\n",
              "      <td>36.492649</td>\n",
              "      <td>-94.208878</td>\n",
              "      <td>10.069647</td>\n",
              "      <td>102.040754</td>\n",
              "      <td>-94.208885</td>\n",
              "      <td>-94.208871</td>\n",
              "      <td>36.492647</td>\n",
              "      <td>36.492652</td>\n",
              "      <td>29.209966</td>\n",
              "      <td>24093.251787</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.803478e+05</td>\n",
              "      <td>1.803478e+05</td>\n",
              "      <td>8.672774e+07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>92.578800</td>\n",
              "      <td>383.144656</td>\n",
              "      <td>3.451852</td>\n",
              "      <td>84.728789</td>\n",
              "      <td>405.815767</td>\n",
              "      <td>1512.638775</td>\n",
              "      <td>6.497777</td>\n",
              "      <td>17.037866</td>\n",
              "      <td>3.966482</td>\n",
              "      <td>104.208243</td>\n",
              "      <td>17.037867</td>\n",
              "      <td>17.037865</td>\n",
              "      <td>6.497776</td>\n",
              "      <td>6.497777</td>\n",
              "      <td>17.730361</td>\n",
              "      <td>19028.130410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.067487e+06</td>\n",
              "      <td>1.067488e+06</td>\n",
              "      <td>1.302561e+06</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.001000</td>\n",
              "      <td>17.956533</td>\n",
              "      <td>-164.344400</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-164.344406</td>\n",
              "      <td>-164.344376</td>\n",
              "      <td>17.956532</td>\n",
              "      <td>17.956533</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.195552e+06</td>\n",
              "      <td>1.195553e+06</td>\n",
              "      <td>1.449595e+06</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>1250.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>122.000000</td>\n",
              "      <td>1300.000000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>32.504633</td>\n",
              "      <td>-103.998900</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>-103.998901</td>\n",
              "      <td>-103.998886</td>\n",
              "      <td>32.504631</td>\n",
              "      <td>32.504635</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>5027.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.218905e+06</td>\n",
              "      <td>1.218906e+06</td>\n",
              "      <td>1.476542e+06</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>189.000000</td>\n",
              "      <td>1454.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>207.000000</td>\n",
              "      <td>1532.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>35.511667</td>\n",
              "      <td>-91.490000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>-91.490013</td>\n",
              "      <td>-91.489998</td>\n",
              "      <td>35.511665</td>\n",
              "      <td>35.511673</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>26129.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.423229e+06</td>\n",
              "      <td>1.423230e+06</td>\n",
              "      <td>1.950201e+07</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>264.000000</td>\n",
              "      <td>1700.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>266.750000</td>\n",
              "      <td>1800.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>40.722535</td>\n",
              "      <td>-82.038900</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>129.000000</td>\n",
              "      <td>-82.038902</td>\n",
              "      <td>-82.038887</td>\n",
              "      <td>40.722534</td>\n",
              "      <td>40.722538</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>41029.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.880429e+06</td>\n",
              "      <td>1.880430e+06</td>\n",
              "      <td>3.003482e+08</td>\n",
              "      <td>2010.0</td>\n",
              "      <td>365.000000</td>\n",
              "      <td>2359.000000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>365.000000</td>\n",
              "      <td>2359.000000</td>\n",
              "      <td>306113.000000</td>\n",
              "      <td>69.336700</td>\n",
              "      <td>-65.364670</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>810.000000</td>\n",
              "      <td>-65.364677</td>\n",
              "      <td>-65.364670</td>\n",
              "      <td>69.336693</td>\n",
              "      <td>69.336700</td>\n",
              "      <td>72.000000</td>\n",
              "      <td>56045.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Unnamed: 0      OBJECTID        FOD_ID  FIRE_YEAR  DISCOVERY_DOY  \\\n",
              "count  7.988900e+04  7.988900e+04  7.988900e+04    79889.0   79889.000000   \n",
              "mean   1.315363e+06  1.315364e+06  4.377702e+07     2010.0     187.132659   \n",
              "std    1.803478e+05  1.803478e+05  8.672774e+07        0.0      92.578800   \n",
              "min    1.067487e+06  1.067488e+06  1.302561e+06     2010.0       1.000000   \n",
              "25%    1.195552e+06  1.195553e+06  1.449595e+06     2010.0     100.000000   \n",
              "50%    1.218905e+06  1.218906e+06  1.476542e+06     2010.0     189.000000   \n",
              "75%    1.423229e+06  1.423230e+06  1.950201e+07     2010.0     264.000000   \n",
              "max    1.880429e+06  1.880430e+06  3.003482e+08     2010.0     365.000000   \n",
              "\n",
              "       DISCOVERY_TIME  STAT_CAUSE_CODE      CONT_DOY     CONT_TIME  \\\n",
              "count    40257.000000     79889.000000  33834.000000  29848.000000   \n",
              "mean      1456.864396         6.358122    199.431489   1514.818514   \n",
              "std        383.144656         3.451852     84.728789    405.815767   \n",
              "min          0.000000         1.000000      1.000000      0.000000   \n",
              "25%       1250.000000         4.000000    122.000000   1300.000000   \n",
              "50%       1454.000000         5.000000    207.000000   1532.000000   \n",
              "75%       1700.000000         9.000000    266.750000   1800.000000   \n",
              "max       2359.000000        13.000000    365.000000   2359.000000   \n",
              "\n",
              "           FIRE_SIZE      LATITUDE     LONGITUDE    OWNER_CODE     FIPS_CODE  \\\n",
              "count   79889.000000  79889.000000  79889.000000  79889.000000  63159.000000   \n",
              "mean       43.728864     36.492649    -94.208878     10.069647    102.040754   \n",
              "std      1512.638775      6.497777     17.037866      3.966482    104.208243   \n",
              "min         0.001000     17.956533   -164.344400      1.000000      1.000000   \n",
              "25%         0.100000     32.504633   -103.998900      8.000000     31.000000   \n",
              "50%         1.000000     35.511667    -91.490000     11.000000     71.000000   \n",
              "75%         3.000000     40.722535    -82.038900     14.000000    129.000000   \n",
              "max    306113.000000     69.336700    -65.364670     15.000000    810.000000   \n",
              "\n",
              "          bbox_xmin     bbox_xmax     bbox_ymin     bbox_ymax  fips_state_cd  \\\n",
              "count  79889.000000  79889.000000  79889.000000  79889.000000   79889.000000   \n",
              "mean     -94.208885    -94.208871     36.492647     36.492652      29.209966   \n",
              "std       17.037867     17.037865      6.497776      6.497777      17.730361   \n",
              "min     -164.344406   -164.344376     17.956532     17.956533       1.000000   \n",
              "25%     -103.998901   -103.998886     32.504631     32.504635      13.000000   \n",
              "50%      -91.490013    -91.489998     35.511665     35.511673      31.000000   \n",
              "75%      -82.038902    -82.038887     40.722534     40.722538      45.000000   \n",
              "max      -65.364677    -65.364670     69.336693     69.336700      72.000000   \n",
              "\n",
              "        county_fips  \n",
              "count  79889.000000  \n",
              "mean   24093.251787  \n",
              "std    19028.130410  \n",
              "min        0.000000  \n",
              "25%     5027.000000  \n",
              "50%    26129.000000  \n",
              "75%    41029.000000  \n",
              "max    56045.000000  "
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df_.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 984
        },
        "id": "Jp6E-cYVY4Up",
        "outputId": "ef51c237-e99b-4479-e8d2-ec8169475b89"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,29) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,29) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,29) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,19,29,31) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,19,29,31) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,19,29,31) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,19,29,31) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (19) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,19,29) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11,19) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (19) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n",
            "C:\\Users\\Sphia\\AppData\\Local\\Temp\\ipykernel_14580\\261610884.py:7: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(file)\n"
          ]
        },
        {
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>OBJECTID</th>\n",
              "      <th>FOD_ID</th>\n",
              "      <th>FPA_ID</th>\n",
              "      <th>SOURCE_SYSTEM_TYPE</th>\n",
              "      <th>SOURCE_SYSTEM</th>\n",
              "      <th>NWCG_REPORTING_AGENCY</th>\n",
              "      <th>NWCG_REPORTING_UNIT_ID</th>\n",
              "      <th>NWCG_REPORTING_UNIT_NAME</th>\n",
              "      <th>SOURCE_REPORTING_UNIT</th>\n",
              "      <th>...</th>\n",
              "      <th>agency_State</th>\n",
              "      <th>agency_Code</th>\n",
              "      <th>agency_Name</th>\n",
              "      <th>bbox_xmin</th>\n",
              "      <th>bbox_xmax</th>\n",
              "      <th>bbox_ymin</th>\n",
              "      <th>bbox_ymax</th>\n",
              "      <th>fips_state_cd</th>\n",
              "      <th>county_fips</th>\n",
              "      <th>Year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>41875</td>\n",
              "      <td>41876</td>\n",
              "      <td>42087</td>\n",
              "      <td>FS-255009</td>\n",
              "      <td>FED</td>\n",
              "      <td>FS-FIRESTAT</td>\n",
              "      <td>FS</td>\n",
              "      <td>USMTBDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>0102</td>\n",
              "      <td>...</td>\n",
              "      <td>MT</td>\n",
              "      <td>BDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>-113.078346</td>\n",
              "      <td>-113.078331</td>\n",
              "      <td>45.359993</td>\n",
              "      <td>45.360001</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1992</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>41876</td>\n",
              "      <td>41877</td>\n",
              "      <td>42088</td>\n",
              "      <td>FS-255013</td>\n",
              "      <td>FED</td>\n",
              "      <td>FS-FIRESTAT</td>\n",
              "      <td>FS</td>\n",
              "      <td>USMTBDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>0102</td>\n",
              "      <td>...</td>\n",
              "      <td>MT</td>\n",
              "      <td>BDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>-112.683334</td>\n",
              "      <td>-112.683319</td>\n",
              "      <td>44.539993</td>\n",
              "      <td>44.540001</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1992</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>41877</td>\n",
              "      <td>41878</td>\n",
              "      <td>42089</td>\n",
              "      <td>FS-255017</td>\n",
              "      <td>FED</td>\n",
              "      <td>FS-FIRESTAT</td>\n",
              "      <td>FS</td>\n",
              "      <td>USMTBDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>0102</td>\n",
              "      <td>...</td>\n",
              "      <td>MT</td>\n",
              "      <td>BDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>-112.983345</td>\n",
              "      <td>-112.983330</td>\n",
              "      <td>44.516666</td>\n",
              "      <td>44.516670</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1992</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>41878</td>\n",
              "      <td>41879</td>\n",
              "      <td>42090</td>\n",
              "      <td>FS-255018</td>\n",
              "      <td>FED</td>\n",
              "      <td>FS-FIRESTAT</td>\n",
              "      <td>FS</td>\n",
              "      <td>USMTBDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>0102</td>\n",
              "      <td>...</td>\n",
              "      <td>MT</td>\n",
              "      <td>BDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>-112.730003</td>\n",
              "      <td>-112.729988</td>\n",
              "      <td>44.689999</td>\n",
              "      <td>44.690006</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1992</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>41879</td>\n",
              "      <td>41880</td>\n",
              "      <td>42091</td>\n",
              "      <td>FS-255024</td>\n",
              "      <td>FED</td>\n",
              "      <td>FS-FIRESTAT</td>\n",
              "      <td>FS</td>\n",
              "      <td>USMTBDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>0102</td>\n",
              "      <td>...</td>\n",
              "      <td>MT</td>\n",
              "      <td>BDF</td>\n",
              "      <td>Beaverhead/Deerlodge National Forest</td>\n",
              "      <td>-112.820015</td>\n",
              "      <td>-112.820000</td>\n",
              "      <td>45.763332</td>\n",
              "      <td>45.763340</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1992</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 50 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0  OBJECTID  FOD_ID     FPA_ID SOURCE_SYSTEM_TYPE SOURCE_SYSTEM  \\\n",
              "0       41875     41876   42087  FS-255009                FED   FS-FIRESTAT   \n",
              "1       41876     41877   42088  FS-255013                FED   FS-FIRESTAT   \n",
              "2       41877     41878   42089  FS-255017                FED   FS-FIRESTAT   \n",
              "3       41878     41879   42090  FS-255018                FED   FS-FIRESTAT   \n",
              "4       41879     41880   42091  FS-255024                FED   FS-FIRESTAT   \n",
              "\n",
              "  NWCG_REPORTING_AGENCY NWCG_REPORTING_UNIT_ID  \\\n",
              "0                    FS                USMTBDF   \n",
              "1                    FS                USMTBDF   \n",
              "2                    FS                USMTBDF   \n",
              "3                    FS                USMTBDF   \n",
              "4                    FS                USMTBDF   \n",
              "\n",
              "               NWCG_REPORTING_UNIT_NAME SOURCE_REPORTING_UNIT  ...  \\\n",
              "0  Beaverhead/Deerlodge National Forest                  0102  ...   \n",
              "1  Beaverhead/Deerlodge National Forest                  0102  ...   \n",
              "2  Beaverhead/Deerlodge National Forest                  0102  ...   \n",
              "3  Beaverhead/Deerlodge National Forest                  0102  ...   \n",
              "4  Beaverhead/Deerlodge National Forest                  0102  ...   \n",
              "\n",
              "  agency_State agency_Code                           agency_Name   bbox_xmin  \\\n",
              "0           MT         BDF  Beaverhead/Deerlodge National Forest -113.078346   \n",
              "1           MT         BDF  Beaverhead/Deerlodge National Forest -112.683334   \n",
              "2           MT         BDF  Beaverhead/Deerlodge National Forest -112.983345   \n",
              "3           MT         BDF  Beaverhead/Deerlodge National Forest -112.730003   \n",
              "4           MT         BDF  Beaverhead/Deerlodge National Forest -112.820015   \n",
              "\n",
              "    bbox_xmax  bbox_ymin  bbox_ymax  fips_state_cd county_fips  Year  \n",
              "0 -113.078331  45.359993  45.360001             30           0  1992  \n",
              "1 -112.683319  44.539993  44.540001             30           0  1992  \n",
              "2 -112.983330  44.516666  44.516670             30           0  1992  \n",
              "3 -112.729988  44.689999  44.690006             30           0  1992  \n",
              "4 -112.820000  45.763332  45.763340             30           0  1992  \n",
              "\n",
              "[5 rows x 50 columns]"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "csv_files = [\"datasets/fires_1992.csv\", \"datasets/fires_1993.csv\", \"datasets/fires_1994.csv\", \"datasets/fires_1995.csv\", \"datasets/fires_1996.csv\", \"datasets/fires_1997.csv\", \"datasets/fires_1998.csv\", \"datasets/fires_1999.csv\", \"datasets/fires_2000.csv\", \"datasets/fires_2001.csv\", \"datasets/fires_2002.csv\", \"datasets/fires_2003.csv\", \"datasets/fires_2004.csv\", \"datasets/fires_2005.csv\", \"datasets/fires_2006.csv\", \"datasets/fires_2007.csv\", \"datasets/fires_2008.csv\", \"datasets/fires_2009.csv\", \"datasets/fires_2010.csv\", \"datasets/fires_2011.csv\", \"datasets/fires_2012.csv\", \"datasets/fires_2013.csv\", \"datasets/fires_2014.csv\", \"datasets/fires_2015.csv\"]\n",
        "\n",
        "data_frames = []\n",
        "year = 1992\n",
        "\n",
        "for file in csv_files:\n",
        "    df = pd.read_csv(file)\n",
        "    df['Year'] = year\n",
        "    data_frames.append(df)\n",
        "    year+=1\n",
        "\n",
        "combined_df = pd.concat(data_frames, ignore_index=True)\n",
        "\n",
        "combined_df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gh2yxf_HGZSa"
      },
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "geD5eUE-EqSc"
      },
      "source": [
        "Replacing Missing Values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "SgCMoRRTE6Ks"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import scipy.stats as stats\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1bDF4by4Es6j",
        "outputId": "c850d77f-c32a-4c5c-dd06-a64c69421702"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Unnamed: 0                         0\n",
            "OBJECTID                           0\n",
            "FOD_ID                             0\n",
            "FPA_ID                             0\n",
            "SOURCE_SYSTEM_TYPE                 0\n",
            "SOURCE_SYSTEM                      0\n",
            "NWCG_REPORTING_AGENCY              0\n",
            "NWCG_REPORTING_UNIT_ID             0\n",
            "NWCG_REPORTING_UNIT_NAME           0\n",
            "SOURCE_REPORTING_UNIT              0\n",
            "SOURCE_REPORTING_UNIT_NAME         0\n",
            "LOCAL_INCIDENT_ID             820821\n",
            "FIRE_NAME                     960479\n",
            "FIRE_YEAR                          0\n",
            "DISCOVERY_DATE                     0\n",
            "DISCOVERY_DOY                      0\n",
            "DISCOVERY_TIME                882638\n",
            "STAT_CAUSE_CODE                    0\n",
            "STAT_CAUSE_DESCR                   0\n",
            "CONT_DATE                     891531\n",
            "CONT_DOY                      891531\n",
            "CONT_TIME                     972553\n",
            "FIRE_SIZE                          0\n",
            "FIRE_SIZE_CLASS                    0\n",
            "LATITUDE                           0\n",
            "LONGITUDE                          0\n",
            "OWNER_CODE                         0\n",
            "OWNER_DESCR                        0\n",
            "STATE                              0\n",
            "COUNTY                        678148\n",
            "FIPS_CODE                     678148\n",
            "FIPS_NAME                     678148\n",
            "agency_UnitId                  34757\n",
            "agency_GeographicArea          34757\n",
            "agency_Gacc                    34757\n",
            "agency_WildlandRole            34757\n",
            "agency_UnitType                34757\n",
            "agency_Department              96061\n",
            "agency_Agency                  96840\n",
            "agency_Country                 34757\n",
            "agency_State                   34757\n",
            "agency_Code                    34757\n",
            "agency_Name                    34757\n",
            "bbox_xmin                          0\n",
            "bbox_xmax                          0\n",
            "bbox_ymin                          0\n",
            "bbox_ymax                          0\n",
            "fips_state_cd                      0\n",
            "county_fips                        0\n",
            "Year                               0\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "nan_count = np.sum(combined_df.isnull(), axis = 0)\n",
        "nan_cols = nan_count != 0\n",
        "print(nan_count)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ymzZbEzpFZ69",
        "outputId": "fa2e9db6-114c-4e21-9724-b9ea9c147996"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Unnamed: 0                      int64\n",
              "OBJECTID                        int64\n",
              "FOD_ID                          int64\n",
              "FPA_ID                         object\n",
              "SOURCE_SYSTEM_TYPE             object\n",
              "SOURCE_SYSTEM                  object\n",
              "NWCG_REPORTING_AGENCY          object\n",
              "NWCG_REPORTING_UNIT_ID         object\n",
              "NWCG_REPORTING_UNIT_NAME       object\n",
              "SOURCE_REPORTING_UNIT          object\n",
              "SOURCE_REPORTING_UNIT_NAME     object\n",
              "LOCAL_INCIDENT_ID              object\n",
              "FIRE_NAME                      object\n",
              "FIRE_YEAR                       int64\n",
              "DISCOVERY_DATE                 object\n",
              "DISCOVERY_DOY                   int64\n",
              "DISCOVERY_TIME                float64\n",
              "STAT_CAUSE_CODE               float64\n",
              "STAT_CAUSE_DESCR               object\n",
              "CONT_DATE                      object\n",
              "CONT_DOY                      float64\n",
              "CONT_TIME                     float64\n",
              "FIRE_SIZE                     float64\n",
              "FIRE_SIZE_CLASS                object\n",
              "LATITUDE                      float64\n",
              "LONGITUDE                     float64\n",
              "OWNER_CODE                    float64\n",
              "OWNER_DESCR                    object\n",
              "STATE                          object\n",
              "COUNTY                         object\n",
              "FIPS_CODE                     float64\n",
              "FIPS_NAME                      object\n",
              "agency_UnitId                  object\n",
              "agency_GeographicArea          object\n",
              "agency_Gacc                    object\n",
              "agency_WildlandRole            object\n",
              "agency_UnitType                object\n",
              "agency_Department              object\n",
              "agency_Agency                  object\n",
              "agency_Country                 object\n",
              "agency_State                   object\n",
              "agency_Code                    object\n",
              "agency_Name                    object\n",
              "bbox_xmin                     float64\n",
              "bbox_xmax                     float64\n",
              "bbox_ymin                     float64\n",
              "bbox_ymax                     float64\n",
              "fips_state_cd                   int64\n",
              "county_fips                     int64\n",
              "Year                            int64\n",
              "dtype: object"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "combined_df.dtypes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "Qb7zyfyMDG-V"
      },
      "outputs": [],
      "source": [
        "columns_with_nan = combined_df.columns[nan_count != 0]\n",
        "num_columns = [col for col in columns_with_nan if combined_df[col].dtype == 'int64' or combined_df[col].dtype == 'float64']\n",
        "cat_columns = columns_with_nan.drop(num_columns)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_z-b1uhwJF9s"
      },
      "source": [
        "# Replace missing values: Numerical"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "ig7EPMU5JRa8"
      },
      "outputs": [],
      "source": [
        "def replaceNullNum(col):\n",
        "  mean = combined_df[col].mean()\n",
        "  combined_df[col].fillna(value=mean, inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "id": "2hTfFcPnEdkd"
      },
      "outputs": [],
      "source": [
        "for col in num_columns:\n",
        "  replaceNullNum(col)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_cdXhimcE12P"
      },
      "source": [
        "# Replace missing values: Categorical\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "c_7gdu3VEGm6"
      },
      "outputs": [],
      "source": [
        "def replaceNullCat(col):\n",
        "    mode = combined_df[col].mode().iloc[0]\n",
        "    combined_df[col].fillna(value= mode, inplace=True)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "imU2wovsEtB2"
      },
      "outputs": [],
      "source": [
        "for col in cat_columns:\n",
        "  replaceNullCat(col)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uKFjTwJiFBNo"
      },
      "source": [
        "Check for missing values again"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WvCMp1ObFEks",
        "outputId": "c8deb505-a8dc-4cb2-f70c-bbe1134b2ca1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Unnamed: 0                    0\n",
            "OBJECTID                      0\n",
            "FOD_ID                        0\n",
            "FPA_ID                        0\n",
            "SOURCE_SYSTEM_TYPE            0\n",
            "SOURCE_SYSTEM                 0\n",
            "NWCG_REPORTING_AGENCY         0\n",
            "NWCG_REPORTING_UNIT_ID        0\n",
            "NWCG_REPORTING_UNIT_NAME      0\n",
            "SOURCE_REPORTING_UNIT         0\n",
            "SOURCE_REPORTING_UNIT_NAME    0\n",
            "LOCAL_INCIDENT_ID             0\n",
            "FIRE_NAME                     0\n",
            "FIRE_YEAR                     0\n",
            "DISCOVERY_DATE                0\n",
            "DISCOVERY_DOY                 0\n",
            "DISCOVERY_TIME                0\n",
            "STAT_CAUSE_CODE               0\n",
            "STAT_CAUSE_DESCR              0\n",
            "CONT_DATE                     0\n",
            "CONT_DOY                      0\n",
            "CONT_TIME                     0\n",
            "FIRE_SIZE                     0\n",
            "FIRE_SIZE_CLASS               0\n",
            "LATITUDE                      0\n",
            "LONGITUDE                     0\n",
            "OWNER_CODE                    0\n",
            "OWNER_DESCR                   0\n",
            "STATE                         0\n",
            "COUNTY                        0\n",
            "FIPS_CODE                     0\n",
            "FIPS_NAME                     0\n",
            "agency_UnitId                 0\n",
            "agency_GeographicArea         0\n",
            "agency_Gacc                   0\n",
            "agency_WildlandRole           0\n",
            "agency_UnitType               0\n",
            "agency_Department             0\n",
            "agency_Agency                 0\n",
            "agency_Country                0\n",
            "agency_State                  0\n",
            "agency_Code                   0\n",
            "agency_Name                   0\n",
            "bbox_xmin                     0\n",
            "bbox_xmax                     0\n",
            "bbox_ymin                     0\n",
            "bbox_ymax                     0\n",
            "fips_state_cd                 0\n",
            "county_fips                   0\n",
            "Year                          0\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "nan_count = np.sum(combined_df.isnull(), axis = 0)\n",
        "nan_cols = nan_count != 0\n",
        "print(nan_count)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jo8XnzfOWt1d"
      },
      "source": [
        "Combine County Level Dataset with Fire Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "X5GIVaWKPtDd",
        "outputId": "848096c5-e1e5-4c3c-c878-da30dcb1d3bd"
      },
      "outputs": [
        {
          "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>county_fips</th>\n",
              "      <th>population</th>\n",
              "      <th>estimated_houses</th>\n",
              "      <th>allstate_policies_in_force</th>\n",
              "      <th>allstate_pif_fraction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.057120</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1003</td>\n",
              "      <td>182086</td>\n",
              "      <td>47341</td>\n",
              "      <td>4746</td>\n",
              "      <td>0.100251</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1005</td>\n",
              "      <td>28155</td>\n",
              "      <td>7320</td>\n",
              "      <td>806</td>\n",
              "      <td>0.110109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1007</td>\n",
              "      <td>23339</td>\n",
              "      <td>6069</td>\n",
              "      <td>645</td>\n",
              "      <td>0.106278</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1009</td>\n",
              "      <td>45074</td>\n",
              "      <td>11719</td>\n",
              "      <td>1143</td>\n",
              "      <td>0.097534</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   county_fips  population  estimated_houses  allstate_policies_in_force  \\\n",
              "0         1001       52724             13708                         783   \n",
              "1         1003      182086             47341                        4746   \n",
              "2         1005       28155              7320                         806   \n",
              "3         1007       23339              6069                         645   \n",
              "4         1009       45074             11719                        1143   \n",
              "\n",
              "   allstate_pif_fraction  \n",
              "0               0.057120  \n",
              "1               0.100251  \n",
              "2               0.110109  \n",
              "3               0.106278  \n",
              "4               0.097534  "
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df_county = pd.read_csv('datasets\\county_level_population.csv')\n",
        "df_county.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 738
        },
        "id": "LfjKEVANQFui",
        "outputId": "1ae00d1f-5aa5-4849-81c7-d00b37a6c629"
      },
      "outputs": [
        {
          "data": {
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              "      <th>county_fips</th>\n",
              "      <th>population</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
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              "      <td>41782</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1201845 rows × 54 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         county_fips  population  estimated_houses  \\\n",
              "0               1001       52724             13708   \n",
              "1               1001       52724             13708   \n",
              "2               1001       52724             13708   \n",
              "3               1001       52724             13708   \n",
              "4               1001       52724             13708   \n",
              "...              ...         ...               ...   \n",
              "1201840        72147        9098              2365   \n",
              "1201841        72147        9098              2365   \n",
              "1201842        72149       26488              6887   \n",
              "1201843        72151       38019              9885   \n",
              "1201844        72153       41782             10863   \n",
              "\n",
              "         allstate_policies_in_force  allstate_pif_fraction  Unnamed: 0  \\\n",
              "0                               783               0.057120   1429203.0   \n",
              "1                               783               0.057120   1429204.0   \n",
              "2                               783               0.057120   1429205.0   \n",
              "3                               783               0.057120   1429206.0   \n",
              "4                               783               0.057120   1429207.0   \n",
              "...                             ...                    ...         ...   \n",
              "1201840                         230               0.097252   1804867.0   \n",
              "1201841                         230               0.097252   1804871.0   \n",
              "1201842                         678               0.098446         NaN   \n",
              "1201843                         983               0.099444         NaN   \n",
              "1201844                        1424               0.131087         NaN   \n",
              "\n",
              "          OBJECTID       FOD_ID               FPA_ID SOURCE_SYSTEM_TYPE  ...  \\\n",
              "0        1429204.0   19900031.0     AL-AU-1994-5-001             NONFED  ...   \n",
              "1        1429205.0   19900032.0     AL-AU-1994-5-002             NONFED  ...   \n",
              "2        1429206.0   19900033.0     AL-AU-1994-5-003             NONFED  ...   \n",
              "3        1429207.0   19900034.0    AL-AU-1994-21-004             NONFED  ...   \n",
              "4        1429208.0   19900035.0    AL-AU-1994-33-005             NONFED  ...   \n",
              "...            ...          ...                  ...                ...  ...   \n",
              "1201840  1804868.0  300218365.0  FWS-2015USPRVQRJ45K                FED  ...   \n",
              "1201841  1804872.0  300218369.0  FWS-2015USPRVQRJ403                FED  ...   \n",
              "1201842        NaN          NaN                  NaN                NaN  ...   \n",
              "1201843        NaN          NaN                  NaN                NaN  ...   \n",
              "1201844        NaN          NaN                  NaN                NaN  ...   \n",
              "\n",
              "        agency_Country agency_State agency_Code  \\\n",
              "0                   US           AL         ALS   \n",
              "1                   US           AL         ALS   \n",
              "2                   US           AL         ALS   \n",
              "3                   US           AL         ALS   \n",
              "4                   US           AL         ALS   \n",
              "...                ...          ...         ...   \n",
              "1201840             US           PR         VQR   \n",
              "1201841             US           PR         VQR   \n",
              "1201842            NaN          NaN         NaN   \n",
              "1201843            NaN          NaN         NaN   \n",
              "1201844            NaN          NaN         NaN   \n",
              "\n",
              "                              agency_Name  bbox_xmin  bbox_xmax  bbox_ymin  \\\n",
              "0             Alabama Forestry Commission -86.835953 -86.835938  32.552738   \n",
              "1             Alabama Forestry Commission -86.836113 -86.836098  32.566769   \n",
              "2             Alabama Forestry Commission -86.836113 -86.836098  32.566769   \n",
              "3             Alabama Forestry Commission -86.852371 -86.852356  32.509739   \n",
              "4             Alabama Forestry Commission -86.599800 -86.599792  32.568069   \n",
              "...                                   ...        ...        ...        ...   \n",
              "1201840  Vieques National Wildlife Refuge -65.328613 -65.328606  18.144999   \n",
              "1201841  Vieques National Wildlife Refuge -65.328896 -65.328888  18.133451   \n",
              "1201842                               NaN        NaN        NaN        NaN   \n",
              "1201843                               NaN        NaN        NaN        NaN   \n",
              "1201844                               NaN        NaN        NaN        NaN   \n",
              "\n",
              "         bbox_ymax  fips_state_cd    Year  \n",
              "0        32.552742            1.0  1994.0  \n",
              "1        32.566772            1.0  1994.0  \n",
              "2        32.566772            1.0  1994.0  \n",
              "3        32.509743            1.0  1994.0  \n",
              "4        32.568073            1.0  1994.0  \n",
              "...            ...            ...     ...  \n",
              "1201840  18.145000           72.0  2015.0  \n",
              "1201841  18.133453           72.0  2015.0  \n",
              "1201842        NaN            NaN     NaN  \n",
              "1201843        NaN            NaN     NaN  \n",
              "1201844        NaN            NaN     NaN  \n",
              "\n",
              "[1201845 rows x 54 columns]"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "merged_df = pd.merge(df_county, combined_df, on='county_fips', how='left')\n",
        "merged_df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_Eu0J-04W39u"
      },
      "source": [
        "Checking one more time if there are missing values in the merged dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VYIoKlW3Si2s",
        "outputId": "d2153f57-afbe-447c-a006-4538fcc83e0a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "county_fips                     0\n",
            "population                      0\n",
            "estimated_houses                0\n",
            "allstate_policies_in_force      0\n",
            "allstate_pif_fraction           0\n",
            "Unnamed: 0                    419\n",
            "OBJECTID                      419\n",
            "FOD_ID                        419\n",
            "FPA_ID                        419\n",
            "SOURCE_SYSTEM_TYPE            419\n",
            "SOURCE_SYSTEM                 419\n",
            "NWCG_REPORTING_AGENCY         419\n",
            "NWCG_REPORTING_UNIT_ID        419\n",
            "NWCG_REPORTING_UNIT_NAME      419\n",
            "SOURCE_REPORTING_UNIT         419\n",
            "SOURCE_REPORTING_UNIT_NAME    419\n",
            "LOCAL_INCIDENT_ID             419\n",
            "FIRE_NAME                     419\n",
            "FIRE_YEAR                     419\n",
            "DISCOVERY_DATE                419\n",
            "DISCOVERY_DOY                 419\n",
            "DISCOVERY_TIME                419\n",
            "STAT_CAUSE_CODE               419\n",
            "STAT_CAUSE_DESCR              419\n",
            "CONT_DATE                     419\n",
            "CONT_DOY                      419\n",
            "CONT_TIME                     419\n",
            "FIRE_SIZE                     419\n",
            "FIRE_SIZE_CLASS               419\n",
            "LATITUDE                      419\n",
            "LONGITUDE                     419\n",
            "OWNER_CODE                    419\n",
            "OWNER_DESCR                   419\n",
            "STATE                         419\n",
            "COUNTY                        419\n",
            "FIPS_CODE                     419\n",
            "FIPS_NAME                     419\n",
            "agency_UnitId                 419\n",
            "agency_GeographicArea         419\n",
            "agency_Gacc                   419\n",
            "agency_WildlandRole           419\n",
            "agency_UnitType               419\n",
            "agency_Department             419\n",
            "agency_Agency                 419\n",
            "agency_Country                419\n",
            "agency_State                  419\n",
            "agency_Code                   419\n",
            "agency_Name                   419\n",
            "bbox_xmin                     419\n",
            "bbox_xmax                     419\n",
            "bbox_ymin                     419\n",
            "bbox_ymax                     419\n",
            "fips_state_cd                 419\n",
            "Year                          419\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "nan_count = np.sum(merged_df.isnull(), axis = 0)\n",
        "nan_cols = nan_count != 0\n",
        "print(nan_count)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P2uVekCaWnI_"
      },
      "source": [
        "Dropping Missing Rows (419 Missing)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "id": "57loTvP9WkbA"
      },
      "outputs": [],
      "source": [
        "merged_df.dropna(inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KqBhhcSKXs1O",
        "outputId": "7405ef8f-f9a3-4eaa-93d3-94273c546d44"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "county_fips                   0\n",
            "population                    0\n",
            "estimated_houses              0\n",
            "allstate_policies_in_force    0\n",
            "allstate_pif_fraction         0\n",
            "Unnamed: 0                    0\n",
            "OBJECTID                      0\n",
            "FOD_ID                        0\n",
            "FPA_ID                        0\n",
            "SOURCE_SYSTEM_TYPE            0\n",
            "SOURCE_SYSTEM                 0\n",
            "NWCG_REPORTING_AGENCY         0\n",
            "NWCG_REPORTING_UNIT_ID        0\n",
            "NWCG_REPORTING_UNIT_NAME      0\n",
            "SOURCE_REPORTING_UNIT         0\n",
            "SOURCE_REPORTING_UNIT_NAME    0\n",
            "LOCAL_INCIDENT_ID             0\n",
            "FIRE_NAME                     0\n",
            "FIRE_YEAR                     0\n",
            "DISCOVERY_DATE                0\n",
            "DISCOVERY_DOY                 0\n",
            "DISCOVERY_TIME                0\n",
            "STAT_CAUSE_CODE               0\n",
            "STAT_CAUSE_DESCR              0\n",
            "CONT_DATE                     0\n",
            "CONT_DOY                      0\n",
            "CONT_TIME                     0\n",
            "FIRE_SIZE                     0\n",
            "FIRE_SIZE_CLASS               0\n",
            "LATITUDE                      0\n",
            "LONGITUDE                     0\n",
            "OWNER_CODE                    0\n",
            "OWNER_DESCR                   0\n",
            "STATE                         0\n",
            "COUNTY                        0\n",
            "FIPS_CODE                     0\n",
            "FIPS_NAME                     0\n",
            "agency_UnitId                 0\n",
            "agency_GeographicArea         0\n",
            "agency_Gacc                   0\n",
            "agency_WildlandRole           0\n",
            "agency_UnitType               0\n",
            "agency_Department             0\n",
            "agency_Agency                 0\n",
            "agency_Country                0\n",
            "agency_State                  0\n",
            "agency_Code                   0\n",
            "agency_Name                   0\n",
            "bbox_xmin                     0\n",
            "bbox_xmax                     0\n",
            "bbox_ymin                     0\n",
            "bbox_ymax                     0\n",
            "fips_state_cd                 0\n",
            "Year                          0\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "nan_count = np.sum(merged_df.isnull(), axis = 0)\n",
        "nan_cols = nan_count != 0\n",
        "print(nan_count)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jflgStxnVQnC",
        "outputId": "157c0a89-4f15-4e61-84f8-d23430e25614"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0     Autauga\n",
              "1     Autauga\n",
              "2     Autauga\n",
              "3     Autauga\n",
              "4     Autauga\n",
              "       ...   \n",
              "95    Autauga\n",
              "96    Autauga\n",
              "97    Autauga\n",
              "98    Autauga\n",
              "99    Autauga\n",
              "Name: FIPS_NAME, Length: 100, dtype: object"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#Looking at the Values for Geographic Area\n",
        "merged_df[\"FIPS_NAME\"].head(100)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pXJOq5ovZ2HB"
      },
      "source": [
        "Status Code Reference:\n",
        "\n",
        "1-Lightning Natural\n",
        "\n",
        "2-Equipment Use Equipment and vehicle use\n",
        "\n",
        "3-Smoking Smoking\n",
        "\n",
        "4-Campfire Recreation and ceremony\n",
        "\n",
        "5-Debris Burning Debris and open burning\n",
        "\n",
        "6-Railroad Railroad operations and maintenance\n",
        "\n",
        "7-Arson Arson\n",
        "\n",
        "8-Children Misuse of fire by a minor\n",
        "\n",
        "9-Miscellaneous Other causes\n",
        "\n",
        "10-Fireworks Fireworks\n",
        "\n",
        "11- Power line Power generation/transmission/\n",
        "distribution\n",
        "\n",
        "12-Structure Structure (under Other)\n",
        "Firearms and explosive use\n",
        "\n",
        "Undetermined (Human or Natural)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H7Pu100xGbuA"
      },
      "source": [
        "Feature Engineering SectIon: Number of Columns in the Dataset\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "5UFY-TJrGiYo"
      },
      "outputs": [],
      "source": [
        "# num_columns = combined_df.shape[1]\n",
        "\n",
        "# print(\"Number of columns:\", num_columns)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NIhJ-KNfJ0p0"
      },
      "source": [
        "Feature Engineering/Selection Section:\n",
        "Dropping columns that are not relevant to the problem/label"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "ehv_Io6bKVpV"
      },
      "outputs": [],
      "source": [
        "# columns_to_keep = [\"FIRE_YEAR\",\"STATE\",\"DISCOVERY_DOY\",\"DISCOVERY_TIME\", \"STAT_CAUSE_CODE\",\"population\",\"LATITUDE\",\"LONGITUDE\", \"estimated_houses\",\t\"allstate_pif_fraction\",\"FIPS_NAME\",\"FIRE_SIZE_CLASS\"]\n",
        "\n",
        "# # columns_to_keep = [\"STATE\",\"FIPS_NAME\",\"STAT_CAUSE_CODE\",\"FIRE_SIZE_CLASS\"]\n",
        "# merged_df = merged_df[columns_to_keep]\n",
        "# This is just a rough draft I want you guys opinions on what features are relevant to our problem\n",
        "# Also I was thinking the label should be either the state or GeographicArea\n",
        "# We might want to keep county_fips if we want to identify regions as id"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yd8aXN98M9V5"
      },
      "source": [
        "Feature Engineering Section: Using  One Hot-encoding to convert catorical features to numerical ones"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MXAHt7E5qZhR",
        "outputId": "9e70b8b5-186b-4577-f5f1-b8bbef194437"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "county_fips                     int64\n",
              "population                      int64\n",
              "estimated_houses                int64\n",
              "allstate_policies_in_force      int64\n",
              "allstate_pif_fraction         float64\n",
              "Unnamed: 0                    float64\n",
              "OBJECTID                      float64\n",
              "FOD_ID                        float64\n",
              "FPA_ID                         object\n",
              "SOURCE_SYSTEM_TYPE             object\n",
              "SOURCE_SYSTEM                  object\n",
              "NWCG_REPORTING_AGENCY          object\n",
              "NWCG_REPORTING_UNIT_ID         object\n",
              "NWCG_REPORTING_UNIT_NAME       object\n",
              "SOURCE_REPORTING_UNIT          object\n",
              "SOURCE_REPORTING_UNIT_NAME     object\n",
              "LOCAL_INCIDENT_ID              object\n",
              "FIRE_NAME                      object\n",
              "FIRE_YEAR                     float64\n",
              "DISCOVERY_DATE                 object\n",
              "DISCOVERY_DOY                 float64\n",
              "DISCOVERY_TIME                float64\n",
              "STAT_CAUSE_CODE               float64\n",
              "STAT_CAUSE_DESCR               object\n",
              "CONT_DATE                      object\n",
              "CONT_DOY                      float64\n",
              "CONT_TIME                     float64\n",
              "FIRE_SIZE                     float64\n",
              "FIRE_SIZE_CLASS                object\n",
              "LATITUDE                      float64\n",
              "LONGITUDE                     float64\n",
              "OWNER_CODE                    float64\n",
              "OWNER_DESCR                    object\n",
              "STATE                          object\n",
              "COUNTY                         object\n",
              "FIPS_CODE                     float64\n",
              "FIPS_NAME                      object\n",
              "agency_UnitId                  object\n",
              "agency_GeographicArea          object\n",
              "agency_Gacc                    object\n",
              "agency_WildlandRole            object\n",
              "agency_UnitType                object\n",
              "agency_Department              object\n",
              "agency_Agency                  object\n",
              "agency_Country                 object\n",
              "agency_State                   object\n",
              "agency_Code                    object\n",
              "agency_Name                    object\n",
              "bbox_xmin                     float64\n",
              "bbox_xmax                     float64\n",
              "bbox_ymin                     float64\n",
              "bbox_ymax                     float64\n",
              "fips_state_cd                 float64\n",
              "Year                          float64\n",
              "dtype: object"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "merged_df.dtypes"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Reduce the Data Size to sample of 10% -Sphia Sadek"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {},
      "outputs": [],
      "source": [
        "# merged_df = merged_df.sample(frac=0.10, random_state=42)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E3Qg_5VH8Vm_"
      },
      "source": [
        "Fixed One Hot Encoding D.C"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5wnDuC7psz4Z",
        "outputId": "fec7c1cb-a8e4-4b60-a323-a3b1610ba273"
      },
      "outputs": [
        {
          "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",
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              "    .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>county_fips</th>\n",
              "      <th>population</th>\n",
              "      <th>estimated_houses</th>\n",
              "      <th>allstate_policies_in_force</th>\n",
              "      <th>allstate_pif_fraction</th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>OBJECTID</th>\n",
              "      <th>FOD_ID</th>\n",
              "      <th>FPA_ID</th>\n",
              "      <th>SOURCE_SYSTEM_TYPE</th>\n",
              "      <th>...</th>\n",
              "      <th>agency_Country</th>\n",
              "      <th>agency_State</th>\n",
              "      <th>agency_Code</th>\n",
              "      <th>agency_Name</th>\n",
              "      <th>bbox_xmin</th>\n",
              "      <th>bbox_xmax</th>\n",
              "      <th>bbox_ymin</th>\n",
              "      <th>bbox_ymax</th>\n",
              "      <th>fips_state_cd</th>\n",
              "      <th>Year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <td>0.057120</td>\n",
              "      <td>1429204.0</td>\n",
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              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.836113</td>\n",
              "      <td>-86.836098</td>\n",
              "      <td>32.566769</td>\n",
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              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
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              "    <tr>\n",
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              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.057120</td>\n",
              "      <td>1429205.0</td>\n",
              "      <td>1429206.0</td>\n",
              "      <td>19900033.0</td>\n",
              "      <td>AL-AU-1994-5-003</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>US</td>\n",
              "      <td>AL</td>\n",
              "      <td>ALS</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.836113</td>\n",
              "      <td>-86.836098</td>\n",
              "      <td>32.566769</td>\n",
              "      <td>32.566772</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.057120</td>\n",
              "      <td>1429206.0</td>\n",
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              "      <td>NONFED</td>\n",
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              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
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              "      <td>Alabama Forestry Commission</td>\n",
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              "      <td>1994.0</td>\n",
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              "      <th>...</th>\n",
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              "      <td>FED</td>\n",
              "      <td>...</td>\n",
              "      <td>US</td>\n",
              "      <td>PR</td>\n",
              "      <td>VQR</td>\n",
              "      <td>Vieques National Wildlife Refuge</td>\n",
              "      <td>-65.326668</td>\n",
              "      <td>-65.326660</td>\n",
              "      <td>18.143053</td>\n",
              "      <td>18.143057</td>\n",
              "      <td>72.0</td>\n",
              "      <td>2015.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1201838</th>\n",
              "      <td>72147</td>\n",
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              "      <td>0.097252</td>\n",
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              "      <td>FWS-2015USPRVQRJ45J</td>\n",
              "      <td>FED</td>\n",
              "      <td>...</td>\n",
              "      <td>US</td>\n",
              "      <td>PR</td>\n",
              "      <td>VQR</td>\n",
              "      <td>Vieques National Wildlife Refuge</td>\n",
              "      <td>-65.331947</td>\n",
              "      <td>-65.331940</td>\n",
              "      <td>18.146942</td>\n",
              "      <td>18.146944</td>\n",
              "      <td>72.0</td>\n",
              "      <td>2015.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>1804866.0</td>\n",
              "      <td>1804867.0</td>\n",
              "      <td>300218364.0</td>\n",
              "      <td>FWS-2015USPRVQRJ42A</td>\n",
              "      <td>FED</td>\n",
              "      <td>...</td>\n",
              "      <td>US</td>\n",
              "      <td>PR</td>\n",
              "      <td>VQR</td>\n",
              "      <td>Vieques National Wildlife Refuge</td>\n",
              "      <td>-65.333061</td>\n",
              "      <td>-65.333054</td>\n",
              "      <td>18.142221</td>\n",
              "      <td>18.142223</td>\n",
              "      <td>72.0</td>\n",
              "      <td>2015.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1201840</th>\n",
              "      <td>72147</td>\n",
              "      <td>9098</td>\n",
              "      <td>2365</td>\n",
              "      <td>230</td>\n",
              "      <td>0.097252</td>\n",
              "      <td>1804867.0</td>\n",
              "      <td>1804868.0</td>\n",
              "      <td>300218365.0</td>\n",
              "      <td>FWS-2015USPRVQRJ45K</td>\n",
              "      <td>FED</td>\n",
              "      <td>...</td>\n",
              "      <td>US</td>\n",
              "      <td>PR</td>\n",
              "      <td>VQR</td>\n",
              "      <td>Vieques National Wildlife Refuge</td>\n",
              "      <td>-65.328613</td>\n",
              "      <td>-65.328606</td>\n",
              "      <td>18.144999</td>\n",
              "      <td>18.145000</td>\n",
              "      <td>72.0</td>\n",
              "      <td>2015.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1201841</th>\n",
              "      <td>72147</td>\n",
              "      <td>9098</td>\n",
              "      <td>2365</td>\n",
              "      <td>230</td>\n",
              "      <td>0.097252</td>\n",
              "      <td>1804871.0</td>\n",
              "      <td>1804872.0</td>\n",
              "      <td>300218369.0</td>\n",
              "      <td>FWS-2015USPRVQRJ403</td>\n",
              "      <td>FED</td>\n",
              "      <td>...</td>\n",
              "      <td>US</td>\n",
              "      <td>PR</td>\n",
              "      <td>VQR</td>\n",
              "      <td>Vieques National Wildlife Refuge</td>\n",
              "      <td>-65.328896</td>\n",
              "      <td>-65.328888</td>\n",
              "      <td>18.133451</td>\n",
              "      <td>18.133453</td>\n",
              "      <td>72.0</td>\n",
              "      <td>2015.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1201426 rows × 54 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         county_fips  population  estimated_houses  \\\n",
              "0               1001       52724             13708   \n",
              "1               1001       52724             13708   \n",
              "2               1001       52724             13708   \n",
              "3               1001       52724             13708   \n",
              "4               1001       52724             13708   \n",
              "...              ...         ...               ...   \n",
              "1201837        72147        9098              2365   \n",
              "1201838        72147        9098              2365   \n",
              "1201839        72147        9098              2365   \n",
              "1201840        72147        9098              2365   \n",
              "1201841        72147        9098              2365   \n",
              "\n",
              "         allstate_policies_in_force  allstate_pif_fraction  Unnamed: 0  \\\n",
              "0                               783               0.057120   1429203.0   \n",
              "1                               783               0.057120   1429204.0   \n",
              "2                               783               0.057120   1429205.0   \n",
              "3                               783               0.057120   1429206.0   \n",
              "4                               783               0.057120   1429207.0   \n",
              "...                             ...                    ...         ...   \n",
              "1201837                         230               0.097252   1804856.0   \n",
              "1201838                         230               0.097252   1804862.0   \n",
              "1201839                         230               0.097252   1804866.0   \n",
              "1201840                         230               0.097252   1804867.0   \n",
              "1201841                         230               0.097252   1804871.0   \n",
              "\n",
              "          OBJECTID       FOD_ID               FPA_ID SOURCE_SYSTEM_TYPE  ...  \\\n",
              "0        1429204.0   19900031.0     AL-AU-1994-5-001             NONFED  ...   \n",
              "1        1429205.0   19900032.0     AL-AU-1994-5-002             NONFED  ...   \n",
              "2        1429206.0   19900033.0     AL-AU-1994-5-003             NONFED  ...   \n",
              "3        1429207.0   19900034.0    AL-AU-1994-21-004             NONFED  ...   \n",
              "4        1429208.0   19900035.0    AL-AU-1994-33-005             NONFED  ...   \n",
              "...            ...          ...                  ...                ...  ...   \n",
              "1201837  1804857.0  300218354.0  FWS-2015USPRVQRJ42C                FED  ...   \n",
              "1201838  1804863.0  300218360.0  FWS-2015USPRVQRJ45J                FED  ...   \n",
              "1201839  1804867.0  300218364.0  FWS-2015USPRVQRJ42A                FED  ...   \n",
              "1201840  1804868.0  300218365.0  FWS-2015USPRVQRJ45K                FED  ...   \n",
              "1201841  1804872.0  300218369.0  FWS-2015USPRVQRJ403                FED  ...   \n",
              "\n",
              "        agency_Country agency_State agency_Code  \\\n",
              "0                   US           AL         ALS   \n",
              "1                   US           AL         ALS   \n",
              "2                   US           AL         ALS   \n",
              "3                   US           AL         ALS   \n",
              "4                   US           AL         ALS   \n",
              "...                ...          ...         ...   \n",
              "1201837             US           PR         VQR   \n",
              "1201838             US           PR         VQR   \n",
              "1201839             US           PR         VQR   \n",
              "1201840             US           PR         VQR   \n",
              "1201841             US           PR         VQR   \n",
              "\n",
              "                              agency_Name  bbox_xmin  bbox_xmax  bbox_ymin  \\\n",
              "0             Alabama Forestry Commission -86.835953 -86.835938  32.552738   \n",
              "1             Alabama Forestry Commission -86.836113 -86.836098  32.566769   \n",
              "2             Alabama Forestry Commission -86.836113 -86.836098  32.566769   \n",
              "3             Alabama Forestry Commission -86.852371 -86.852356  32.509739   \n",
              "4             Alabama Forestry Commission -86.599800 -86.599792  32.568069   \n",
              "...                                   ...        ...        ...        ...   \n",
              "1201837  Vieques National Wildlife Refuge -65.326668 -65.326660  18.143053   \n",
              "1201838  Vieques National Wildlife Refuge -65.331947 -65.331940  18.146942   \n",
              "1201839  Vieques National Wildlife Refuge -65.333061 -65.333054  18.142221   \n",
              "1201840  Vieques National Wildlife Refuge -65.328613 -65.328606  18.144999   \n",
              "1201841  Vieques National Wildlife Refuge -65.328896 -65.328888  18.133451   \n",
              "\n",
              "         bbox_ymax  fips_state_cd    Year  \n",
              "0        32.552742            1.0  1994.0  \n",
              "1        32.566772            1.0  1994.0  \n",
              "2        32.566772            1.0  1994.0  \n",
              "3        32.509743            1.0  1994.0  \n",
              "4        32.568073            1.0  1994.0  \n",
              "...            ...            ...     ...  \n",
              "1201837  18.143057           72.0  2015.0  \n",
              "1201838  18.146944           72.0  2015.0  \n",
              "1201839  18.142223           72.0  2015.0  \n",
              "1201840  18.145000           72.0  2015.0  \n",
              "1201841  18.133453           72.0  2015.0  \n",
              "\n",
              "[1201426 rows x 54 columns]"
            ]
          },
          "execution_count": 31,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# merged_df[\"FIPS_NAME\"]\n",
        "merged_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "id": "ktQ0fiE23ehX"
      },
      "outputs": [],
      "source": [
        "another_df = pd.DataFrame(merged_df[\"FIPS_NAME\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "ZkQQOt9qwUUZ"
      },
      "outputs": [],
      "source": [
        "another_df['FIPS_NAME'] = another_df['FIPS_NAME'].astype('category')\n",
        "another_df[\"TYPE_FIPS_NAME\"] = another_df[\"FIPS_NAME\"].cat.codes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "id": "slMTyB4Z3K1v"
      },
      "outputs": [],
      "source": [
        "another_df_2 = pd.DataFrame(merged_df[\"STATE\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "id": "8FGtUqII0opx"
      },
      "outputs": [],
      "source": [
        "another_df_2['STATE'] = another_df_2['STATE'].astype('category')\n",
        "another_df_2['TYPE_STATE'] = another_df_2['STATE'].cat.codes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "id": "xWWlNfYZ3-xn"
      },
      "outputs": [],
      "source": [
        "another_df_3 = pd.DataFrame(merged_df[\"FIRE_SIZE_CLASS\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "id": "OYyoM6IH0yjI"
      },
      "outputs": [],
      "source": [
        "another_df_3['FIRE_SIZE_CLASS'] = another_df_3['FIRE_SIZE_CLASS'].astype('category')\n",
        "another_df_3[\"TYPE_FIRE_SIZE_CLASS\"] = another_df_3['FIRE_SIZE_CLASS'].cat.codes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "id": "DuiiMEgtx6vY"
      },
      "outputs": [],
      "source": [
        "to_extract_1 = another_df[\"TYPE_FIPS_NAME\"]\n",
        "to_extract_2 = another_df_2[\"TYPE_STATE\"]\n",
        "to_extract_3 = another_df_3[\"TYPE_FIRE_SIZE_CLASS\"]\n",
        "merged_df = merged_df.join(to_extract_1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "id": "CCXD6O0u4ToH"
      },
      "outputs": [],
      "source": [
        "merged_df = merged_df.join(to_extract_2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {
        "id": "tzN77WHK4XFv"
      },
      "outputs": [],
      "source": [
        "merged_df = merged_df.join(to_extract_3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "H4MSw8kD4ZK3",
        "outputId": "df41b6b5-8270-4122-b363-2d62e5a1ed14"
      },
      "outputs": [
        {
          "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>county_fips</th>\n",
              "      <th>population</th>\n",
              "      <th>estimated_houses</th>\n",
              "      <th>allstate_policies_in_force</th>\n",
              "      <th>allstate_pif_fraction</th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>OBJECTID</th>\n",
              "      <th>FOD_ID</th>\n",
              "      <th>FPA_ID</th>\n",
              "      <th>SOURCE_SYSTEM_TYPE</th>\n",
              "      <th>...</th>\n",
              "      <th>agency_Name</th>\n",
              "      <th>bbox_xmin</th>\n",
              "      <th>bbox_xmax</th>\n",
              "      <th>bbox_ymin</th>\n",
              "      <th>bbox_ymax</th>\n",
              "      <th>fips_state_cd</th>\n",
              "      <th>Year</th>\n",
              "      <th>TYPE_FIPS_NAME</th>\n",
              "      <th>TYPE_STATE</th>\n",
              "      <th>TYPE_FIRE_SIZE_CLASS</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429203.0</td>\n",
              "      <td>1429204.0</td>\n",
              "      <td>19900031.0</td>\n",
              "      <td>AL-AU-1994-5-001</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.835953</td>\n",
              "      <td>-86.835938</td>\n",
              "      <td>32.552738</td>\n",
              "      <td>32.552742</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429204.0</td>\n",
              "      <td>1429205.0</td>\n",
              "      <td>19900032.0</td>\n",
              "      <td>AL-AU-1994-5-002</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.836113</td>\n",
              "      <td>-86.836098</td>\n",
              "      <td>32.566769</td>\n",
              "      <td>32.566772</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429205.0</td>\n",
              "      <td>1429206.0</td>\n",
              "      <td>19900033.0</td>\n",
              "      <td>AL-AU-1994-5-003</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.836113</td>\n",
              "      <td>-86.836098</td>\n",
              "      <td>32.566769</td>\n",
              "      <td>32.566772</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429206.0</td>\n",
              "      <td>1429207.0</td>\n",
              "      <td>19900034.0</td>\n",
              "      <td>AL-AU-1994-21-004</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.852371</td>\n",
              "      <td>-86.852356</td>\n",
              "      <td>32.509739</td>\n",
              "      <td>32.509743</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429207.0</td>\n",
              "      <td>1429208.0</td>\n",
              "      <td>19900035.0</td>\n",
              "      <td>AL-AU-1994-33-005</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.599800</td>\n",
              "      <td>-86.599792</td>\n",
              "      <td>32.568069</td>\n",
              "      <td>32.568073</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429208.0</td>\n",
              "      <td>1429209.0</td>\n",
              "      <td>19900036.0</td>\n",
              "      <td>AL-AU-1994-33-006</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.599800</td>\n",
              "      <td>-86.599792</td>\n",
              "      <td>32.568069</td>\n",
              "      <td>32.568073</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429209.0</td>\n",
              "      <td>1429210.0</td>\n",
              "      <td>19900037.0</td>\n",
              "      <td>AL-AU-1994-33-007</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.599800</td>\n",
              "      <td>-86.599792</td>\n",
              "      <td>32.568069</td>\n",
              "      <td>32.568073</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429210.0</td>\n",
              "      <td>1429211.0</td>\n",
              "      <td>19900038.0</td>\n",
              "      <td>AL-AU-1994-33-008</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.649971</td>\n",
              "      <td>-86.649963</td>\n",
              "      <td>32.437027</td>\n",
              "      <td>32.437031</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429211.0</td>\n",
              "      <td>1429212.0</td>\n",
              "      <td>19900039.0</td>\n",
              "      <td>AL-AU-1994-45-001</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.636673</td>\n",
              "      <td>-86.636658</td>\n",
              "      <td>32.698936</td>\n",
              "      <td>32.698940</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429212.0</td>\n",
              "      <td>1429213.0</td>\n",
              "      <td>19900040.0</td>\n",
              "      <td>AL-AU-1994-48-007</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.771011</td>\n",
              "      <td>-86.770996</td>\n",
              "      <td>32.493828</td>\n",
              "      <td>32.493832</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 57 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   county_fips  population  estimated_houses  allstate_policies_in_force  \\\n",
              "0         1001       52724             13708                         783   \n",
              "1         1001       52724             13708                         783   \n",
              "2         1001       52724             13708                         783   \n",
              "3         1001       52724             13708                         783   \n",
              "4         1001       52724             13708                         783   \n",
              "5         1001       52724             13708                         783   \n",
              "6         1001       52724             13708                         783   \n",
              "7         1001       52724             13708                         783   \n",
              "8         1001       52724             13708                         783   \n",
              "9         1001       52724             13708                         783   \n",
              "\n",
              "   allstate_pif_fraction  Unnamed: 0   OBJECTID      FOD_ID  \\\n",
              "0                0.05712   1429203.0  1429204.0  19900031.0   \n",
              "1                0.05712   1429204.0  1429205.0  19900032.0   \n",
              "2                0.05712   1429205.0  1429206.0  19900033.0   \n",
              "3                0.05712   1429206.0  1429207.0  19900034.0   \n",
              "4                0.05712   1429207.0  1429208.0  19900035.0   \n",
              "5                0.05712   1429208.0  1429209.0  19900036.0   \n",
              "6                0.05712   1429209.0  1429210.0  19900037.0   \n",
              "7                0.05712   1429210.0  1429211.0  19900038.0   \n",
              "8                0.05712   1429211.0  1429212.0  19900039.0   \n",
              "9                0.05712   1429212.0  1429213.0  19900040.0   \n",
              "\n",
              "              FPA_ID SOURCE_SYSTEM_TYPE  ...                  agency_Name  \\\n",
              "0   AL-AU-1994-5-001             NONFED  ...  Alabama Forestry Commission   \n",
              "1   AL-AU-1994-5-002             NONFED  ...  Alabama Forestry Commission   \n",
              "2   AL-AU-1994-5-003             NONFED  ...  Alabama Forestry Commission   \n",
              "3  AL-AU-1994-21-004             NONFED  ...  Alabama Forestry Commission   \n",
              "4  AL-AU-1994-33-005             NONFED  ...  Alabama Forestry Commission   \n",
              "5  AL-AU-1994-33-006             NONFED  ...  Alabama Forestry Commission   \n",
              "6  AL-AU-1994-33-007             NONFED  ...  Alabama Forestry Commission   \n",
              "7  AL-AU-1994-33-008             NONFED  ...  Alabama Forestry Commission   \n",
              "8  AL-AU-1994-45-001             NONFED  ...  Alabama Forestry Commission   \n",
              "9  AL-AU-1994-48-007             NONFED  ...  Alabama Forestry Commission   \n",
              "\n",
              "   bbox_xmin  bbox_xmax  bbox_ymin  bbox_ymax fips_state_cd    Year  \\\n",
              "0 -86.835953 -86.835938  32.552738  32.552742           1.0  1994.0   \n",
              "1 -86.836113 -86.836098  32.566769  32.566772           1.0  1994.0   \n",
              "2 -86.836113 -86.836098  32.566769  32.566772           1.0  1994.0   \n",
              "3 -86.852371 -86.852356  32.509739  32.509743           1.0  1994.0   \n",
              "4 -86.599800 -86.599792  32.568069  32.568073           1.0  1994.0   \n",
              "5 -86.599800 -86.599792  32.568069  32.568073           1.0  1994.0   \n",
              "6 -86.599800 -86.599792  32.568069  32.568073           1.0  1994.0   \n",
              "7 -86.649971 -86.649963  32.437027  32.437031           1.0  1994.0   \n",
              "8 -86.636673 -86.636658  32.698936  32.698940           1.0  1994.0   \n",
              "9 -86.771011 -86.770996  32.493828  32.493832           1.0  1994.0   \n",
              "\n",
              "  TYPE_FIPS_NAME  TYPE_STATE TYPE_FIRE_SIZE_CLASS  \n",
              "0             71           1                    1  \n",
              "1             71           1                    1  \n",
              "2             71           1                    1  \n",
              "3             71           1                    2  \n",
              "4             71           1                    1  \n",
              "5             71           1                    1  \n",
              "6             71           1                    1  \n",
              "7             71           1                    1  \n",
              "8             71           1                    2  \n",
              "9             71           1                    1  \n",
              "\n",
              "[10 rows x 57 columns]"
            ]
          },
          "execution_count": 41,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "merged_df.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "id": "xlFn9cHGzmmI"
      },
      "outputs": [],
      "source": [
        "#merged_df.iloc[:,[0,1,13,2,3,4,5,6,7,8,9,10,12,11,14]]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "id": "ntHjFEw5z6Hw"
      },
      "outputs": [],
      "source": [
        "# merged_df = merged_df.drop([\"FIPS_NAME\", \"FIRE_SIZE_CLASS\", \"STATE\"], axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "0nKQVPGcMSTz",
        "outputId": "2ea41a23-11c1-4956-fa98-69ef2adbd8ae"
      },
      "outputs": [
        {
          "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>county_fips</th>\n",
              "      <th>population</th>\n",
              "      <th>estimated_houses</th>\n",
              "      <th>allstate_policies_in_force</th>\n",
              "      <th>allstate_pif_fraction</th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>OBJECTID</th>\n",
              "      <th>FOD_ID</th>\n",
              "      <th>FPA_ID</th>\n",
              "      <th>SOURCE_SYSTEM_TYPE</th>\n",
              "      <th>...</th>\n",
              "      <th>agency_Name</th>\n",
              "      <th>bbox_xmin</th>\n",
              "      <th>bbox_xmax</th>\n",
              "      <th>bbox_ymin</th>\n",
              "      <th>bbox_ymax</th>\n",
              "      <th>fips_state_cd</th>\n",
              "      <th>Year</th>\n",
              "      <th>TYPE_FIPS_NAME</th>\n",
              "      <th>TYPE_STATE</th>\n",
              "      <th>TYPE_FIRE_SIZE_CLASS</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429203.0</td>\n",
              "      <td>1429204.0</td>\n",
              "      <td>19900031.0</td>\n",
              "      <td>AL-AU-1994-5-001</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.835953</td>\n",
              "      <td>-86.835938</td>\n",
              "      <td>32.552738</td>\n",
              "      <td>32.552742</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429204.0</td>\n",
              "      <td>1429205.0</td>\n",
              "      <td>19900032.0</td>\n",
              "      <td>AL-AU-1994-5-002</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.836113</td>\n",
              "      <td>-86.836098</td>\n",
              "      <td>32.566769</td>\n",
              "      <td>32.566772</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429205.0</td>\n",
              "      <td>1429206.0</td>\n",
              "      <td>19900033.0</td>\n",
              "      <td>AL-AU-1994-5-003</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.836113</td>\n",
              "      <td>-86.836098</td>\n",
              "      <td>32.566769</td>\n",
              "      <td>32.566772</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429206.0</td>\n",
              "      <td>1429207.0</td>\n",
              "      <td>19900034.0</td>\n",
              "      <td>AL-AU-1994-21-004</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.852371</td>\n",
              "      <td>-86.852356</td>\n",
              "      <td>32.509739</td>\n",
              "      <td>32.509743</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429207.0</td>\n",
              "      <td>1429208.0</td>\n",
              "      <td>19900035.0</td>\n",
              "      <td>AL-AU-1994-33-005</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.599800</td>\n",
              "      <td>-86.599792</td>\n",
              "      <td>32.568069</td>\n",
              "      <td>32.568073</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429208.0</td>\n",
              "      <td>1429209.0</td>\n",
              "      <td>19900036.0</td>\n",
              "      <td>AL-AU-1994-33-006</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.599800</td>\n",
              "      <td>-86.599792</td>\n",
              "      <td>32.568069</td>\n",
              "      <td>32.568073</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429209.0</td>\n",
              "      <td>1429210.0</td>\n",
              "      <td>19900037.0</td>\n",
              "      <td>AL-AU-1994-33-007</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.599800</td>\n",
              "      <td>-86.599792</td>\n",
              "      <td>32.568069</td>\n",
              "      <td>32.568073</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429210.0</td>\n",
              "      <td>1429211.0</td>\n",
              "      <td>19900038.0</td>\n",
              "      <td>AL-AU-1994-33-008</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.649971</td>\n",
              "      <td>-86.649963</td>\n",
              "      <td>32.437027</td>\n",
              "      <td>32.437031</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429211.0</td>\n",
              "      <td>1429212.0</td>\n",
              "      <td>19900039.0</td>\n",
              "      <td>AL-AU-1994-45-001</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.636673</td>\n",
              "      <td>-86.636658</td>\n",
              "      <td>32.698936</td>\n",
              "      <td>32.698940</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1001</td>\n",
              "      <td>52724</td>\n",
              "      <td>13708</td>\n",
              "      <td>783</td>\n",
              "      <td>0.05712</td>\n",
              "      <td>1429212.0</td>\n",
              "      <td>1429213.0</td>\n",
              "      <td>19900040.0</td>\n",
              "      <td>AL-AU-1994-48-007</td>\n",
              "      <td>NONFED</td>\n",
              "      <td>...</td>\n",
              "      <td>Alabama Forestry Commission</td>\n",
              "      <td>-86.771011</td>\n",
              "      <td>-86.770996</td>\n",
              "      <td>32.493828</td>\n",
              "      <td>32.493832</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1994.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 57 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   county_fips  population  estimated_houses  allstate_policies_in_force  \\\n",
              "0         1001       52724             13708                         783   \n",
              "1         1001       52724             13708                         783   \n",
              "2         1001       52724             13708                         783   \n",
              "3         1001       52724             13708                         783   \n",
              "4         1001       52724             13708                         783   \n",
              "5         1001       52724             13708                         783   \n",
              "6         1001       52724             13708                         783   \n",
              "7         1001       52724             13708                         783   \n",
              "8         1001       52724             13708                         783   \n",
              "9         1001       52724             13708                         783   \n",
              "\n",
              "   allstate_pif_fraction  Unnamed: 0   OBJECTID      FOD_ID  \\\n",
              "0                0.05712   1429203.0  1429204.0  19900031.0   \n",
              "1                0.05712   1429204.0  1429205.0  19900032.0   \n",
              "2                0.05712   1429205.0  1429206.0  19900033.0   \n",
              "3                0.05712   1429206.0  1429207.0  19900034.0   \n",
              "4                0.05712   1429207.0  1429208.0  19900035.0   \n",
              "5                0.05712   1429208.0  1429209.0  19900036.0   \n",
              "6                0.05712   1429209.0  1429210.0  19900037.0   \n",
              "7                0.05712   1429210.0  1429211.0  19900038.0   \n",
              "8                0.05712   1429211.0  1429212.0  19900039.0   \n",
              "9                0.05712   1429212.0  1429213.0  19900040.0   \n",
              "\n",
              "              FPA_ID SOURCE_SYSTEM_TYPE  ...                  agency_Name  \\\n",
              "0   AL-AU-1994-5-001             NONFED  ...  Alabama Forestry Commission   \n",
              "1   AL-AU-1994-5-002             NONFED  ...  Alabama Forestry Commission   \n",
              "2   AL-AU-1994-5-003             NONFED  ...  Alabama Forestry Commission   \n",
              "3  AL-AU-1994-21-004             NONFED  ...  Alabama Forestry Commission   \n",
              "4  AL-AU-1994-33-005             NONFED  ...  Alabama Forestry Commission   \n",
              "5  AL-AU-1994-33-006             NONFED  ...  Alabama Forestry Commission   \n",
              "6  AL-AU-1994-33-007             NONFED  ...  Alabama Forestry Commission   \n",
              "7  AL-AU-1994-33-008             NONFED  ...  Alabama Forestry Commission   \n",
              "8  AL-AU-1994-45-001             NONFED  ...  Alabama Forestry Commission   \n",
              "9  AL-AU-1994-48-007             NONFED  ...  Alabama Forestry Commission   \n",
              "\n",
              "   bbox_xmin  bbox_xmax  bbox_ymin  bbox_ymax fips_state_cd    Year  \\\n",
              "0 -86.835953 -86.835938  32.552738  32.552742           1.0  1994.0   \n",
              "1 -86.836113 -86.836098  32.566769  32.566772           1.0  1994.0   \n",
              "2 -86.836113 -86.836098  32.566769  32.566772           1.0  1994.0   \n",
              "3 -86.852371 -86.852356  32.509739  32.509743           1.0  1994.0   \n",
              "4 -86.599800 -86.599792  32.568069  32.568073           1.0  1994.0   \n",
              "5 -86.599800 -86.599792  32.568069  32.568073           1.0  1994.0   \n",
              "6 -86.599800 -86.599792  32.568069  32.568073           1.0  1994.0   \n",
              "7 -86.649971 -86.649963  32.437027  32.437031           1.0  1994.0   \n",
              "8 -86.636673 -86.636658  32.698936  32.698940           1.0  1994.0   \n",
              "9 -86.771011 -86.770996  32.493828  32.493832           1.0  1994.0   \n",
              "\n",
              "  TYPE_FIPS_NAME  TYPE_STATE TYPE_FIRE_SIZE_CLASS  \n",
              "0             71           1                    1  \n",
              "1             71           1                    1  \n",
              "2             71           1                    1  \n",
              "3             71           1                    2  \n",
              "4             71           1                    1  \n",
              "5             71           1                    1  \n",
              "6             71           1                    1  \n",
              "7             71           1                    1  \n",
              "8             71           1                    2  \n",
              "9             71           1                    1  \n",
              "\n",
              "[10 rows x 57 columns]"
            ]
          },
          "execution_count": 44,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "merged_df.head(10)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fBMYHooZqzUh"
      },
      "source": [
        "Correlation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "id": "dFz-hWW2fwt7",
        "outputId": "c83ecd12-792e-4117-fb6a-85a2baa6d9bc"
      },
      "outputs": [],
      "source": [
        "#Correlation between fire cause code and location (longitude + latitude)\n",
        "\n",
        "# merged_df.corr(method ='pearson')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4Etg_PMgxHQ6"
      },
      "source": [
        "Outlier Detection Process:\n",
        "- Finding outliers only specifically for fire size, other columns are irrelevant for detecting outliers or contain non-numerical data\n",
        "- Utilized z-scores to measure each data point's standard deviation from the mean\n",
        "- Could alternatively implement IQR\n",
        "- Findings: 3670 outliers for the size of fires"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "id": "-d-8WmtKxKnN"
      },
      "outputs": [],
      "source": [
        "# Outlier Detection through Z-Scores:\n",
        "\n",
        "# import numpy as np\n",
        "# import pandas as pd\n",
        "# from scipy import stats\n",
        "# import matplotlib.pyplot as plt\n",
        "\n",
        "# csv_files = [\"fires_1992.csv\", \"fires_1993.csv\", \"fires_1994.csv\", \"fires_1995.csv\", \"fires_1996.csv\", \"fires_1997.csv\", \"fires_1998.csv\", \"fires_1999.csv\", \"fires_2000.csv\", \"fires_2001.csv\", \"fires_2002.csv\", \"fires_2003.csv\", \"fires_2004.csv\", \"fires_2005.csv\", \"fires_2006.csv\", \"fires_2007.csv\", \"fires_2008.csv\", \"fires_2009.csv\", \"fires_2010.csv\", \"fires_2011.csv\", \"fires_2012.csv\", \"fires_2013.csv\", \"fires_2014.csv\", \"fires_2015.csv\"]\n",
        "\n",
        "# data_frames = []\n",
        "# year = 1992\n",
        "\n",
        "# for file in csv_files:\n",
        "#     df = pd.read_csv(file)\n",
        "#     df['Year'] = year\n",
        "#     data_frames.append(df)\n",
        "#     year+=1\n",
        "\n",
        "# combined_df = pd.concat(data_frames, ignore_index=True)\n",
        "\n",
        "# numeric_column = ['FIRE_SIZE']\n",
        "\n",
        "# def detect_outliers_zscore(data, column, threshold=2): # 2 standard deviations from the mean\n",
        "#     z_scores = np.abs(stats.zscore(data[column]))\n",
        "#     return np.where(z_scores > threshold)\n",
        "\n",
        "# for column in numeric_column:\n",
        "#     outliers = detect_outliers_zscore(merged_df, column)\n",
        "#     outlier_count = len(outliers[0])\n",
        "#     print(f\"Outliers in {column}: {outliers}\")\n",
        "#     print(f\"Count of outliers: {outlier_count}\")\n",
        "\n",
        "\n",
        "# for column in numeric_column:\n",
        "#     plt.figure(figsize=(8, 6))\n",
        "#     merged_df.boxplot(column=column)\n",
        "#     plt.title(f'Box Plot for {column}')\n",
        "#     plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MusiJFqpdy98"
      },
      "source": [
        "Checking for Class Distribution"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MC0cWZwjd2-7",
        "outputId": "40013119-8478-49db-f4b7-27acdba6e80a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "STAT_CAUSE_CODE\n",
              "5.0     306270\n",
              "9.0     207135\n",
              "7.0     162539\n",
              "1.0     156806\n",
              "13.0    124878\n",
              "2.0      89106\n",
              "4.0      46254\n",
              "3.0      31873\n",
              "8.0      31364\n",
              "6.0      27953\n",
              "11.0     11558\n",
              "10.0      3500\n",
              "12.0      2190\n",
              "Name: count, dtype: int64"
            ]
          },
          "execution_count": 47,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "merged_df[\"STAT_CAUSE_CODE\"].value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {},
      "outputs": [],
      "source": [
        "merged_df.drop(merged_df[merged_df[\"STAT_CAUSE_CODE\"] == 9.0].index, inplace = True)\n",
        "merged_df.drop(merged_df[merged_df[\"STAT_CAUSE_CODE\"] == 13.0].index, inplace = True)\n",
        "# merged_df[\"STAT_CAUSE_CODE\"].value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "STAT_CAUSE_CODE\n",
              "5.0     306270\n",
              "7.0     162539\n",
              "1.0     156806\n",
              "2.0      89106\n",
              "4.0      46254\n",
              "3.0      31873\n",
              "8.0      31364\n",
              "6.0      27953\n",
              "11.0     11558\n",
              "10.0      3500\n",
              "12.0      2190\n",
              "Name: count, dtype: int64"
            ]
          },
          "execution_count": 49,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "merged_df[\"STAT_CAUSE_CODE\"].value_counts()\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {},
      "outputs": [],
      "source": [
        "# columns_to_keep = [\"LATITUDE\",\"LONGITUDE\", \"FIPS_CODE\", \"STAT_CAUSE_CODE\"]\n",
        "columns_to_keep = [\"Year\",\"LATITUDE\",\"LONGITUDE\", \"county_fips\", \"STAT_CAUSE_CODE\", \"population\", \"estimated_houses\", \"allstate_policies_in_force\",\"allstate_pif_fraction\"]\n",
        "\n",
        "# columns_to_keep = [\"STATE\",\"FIPS_NAME\",\"STAT_CAUSE_CODE\",\"FIRE_SIZE_CLASS\"]\n",
        "merged_df = merged_df[columns_to_keep]\n",
        "# This is just a rough draft I want you guys opinions on what features are relevant to our problem\n",
        "# Also I was thinking the label should be either the state or GeographicArea\n",
        "# We might want to keep county_fips if we want to identify regions as id"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We want to have a unique identifier for each county in different states, so we will combine the STATE feature and county_id"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {},
      "outputs": [],
      "source": [
        "# if 6015 in merged_df['county_fips'].values:\n",
        "#     print(\"County code 06015 exists in the dataframe.\")\n",
        "# else:\n",
        "#     print(\"County code 06015 does not exist in the dataframe.\")\n",
        "    \n",
        "# ans = merged_df[merged_df['county_fips'] == 6015]  \n",
        "\n",
        "# total = (ans.size)\n",
        "\n",
        "# print(ans[\"STAT_CAUSE_CODE\"].value_counts())\n",
        "\n",
        "# ans = ans[ans['STAT_CAUSE_CODE'] == 1.0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 75,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Empty DataFrame\n",
            "Columns: [Year, LATITUDE, LONGITUDE, county_fips, STAT_CAUSE_CODE, population, estimated_houses, allstate_policies_in_force, allstate_pif_fraction]\n",
            "Index: []\n"
          ]
        }
      ],
      "source": [
        "merged_df.corr(method ='pearson')\n",
        "\n",
        "filtered_df = merged_df[merged_df[\"county_fips\"] == 15009]\n",
        "print(filtered_df)\n",
        "value_counts = filtered_df[\"STAT_CAUSE_CODE\"].value_counts()\n",
        "# print(value_counts)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Model Selection Sphia"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 68,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy on the test set: 0.561\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        }
      ],
      "source": [
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.model_selection import cross_val_score\n",
        "from sklearn.model_selection import RepeatedStratifiedKFold\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.pipeline import Pipeline\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "new_df = merged_df.drop([\"Year\"], axis = 1)\n",
        "\n",
        "# Assuming 'merged_df' is your DataFrame\n",
        "train_data, test_data = train_test_split(new_df, test_size=0.2, random_state=123)\n",
        "X_train = train_data.drop('STAT_CAUSE_CODE', axis=1)\n",
        "y_train = train_data['STAT_CAUSE_CODE']\n",
        "\n",
        "# Separate features and labels for testing data\n",
        "X_test = test_data.drop('STAT_CAUSE_CODE', axis=1)\n",
        "y_test = test_data['STAT_CAUSE_CODE']\n",
        "\n",
        "# Assuming 'continuous_features' and 'discrete_features' are lists of feature column names\n",
        "continuous_features = [\"population\", \"estimated_houses\", \"allstate_pif_fraction\", \"allstate_policies_in_force\", \"LONGITUDE\", \"LATITUDE\"]\n",
        "discrete_features = [\"county_fips\"]\n",
        "\n",
        "# Define the preprocessing steps\n",
        "preprocessor = ColumnTransformer(\n",
        "    transformers=[\n",
        "        ('num', StandardScaler(), continuous_features),\n",
        "        ('cat', 'passthrough', discrete_features)\n",
        "    ]\n",
        ")\n",
        "\n",
        "# Combine preprocessing with the KNN classifier in a pipeline\n",
        "# Use the DTW distance function as the metric\n",
        "knn_model = Pipeline([\n",
        "    ('preprocessor', preprocessor),\n",
        "    ('classifier', KNeighborsClassifier(n_neighbors=15, metric=\"euclidean\"))  \n",
        "])\n",
        "\n",
        "\n",
        "# Fit the model on the training data\n",
        "knn_model.fit(X_train, y_train)\n",
        "\n",
        "# Make predictions on the test set\n",
        "y_pred = knn_model.predict(X_test)\n",
        "\n",
        "# Evaluate the model on the test set\n",
        "test_accuracy = accuracy_score(y_test, y_pred)\n",
        "print('Accuracy on the test set: %.3f' % test_accuracy)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "array([5.])"
            ]
          },
          "execution_count": 56,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# #37.916134 -122.310768\n",
        "# #6013\t1054436\t274156\t27236\t0.09934489852\n",
        "# #county_fips population estimated_houses\tallstate_policies_in_force\tallstate_pif_fraction\n",
        "# #Year 2023\n",
        "# cerrito = {\"county_fips\": [6013], \"population\": [1054436], \"estimated_houses\":[274156], \"allstate_policies_in_force\": [27236], \n",
        "#            \"allstate_pif_fraction\": [0.09934489852], \"Year\": [2015], \"LATITUDE\": [37.916134], \"LONGITUDE\": [-122.310768]}\n",
        "# # Year\tLATITUDE\tLONGITUDE\tcounty_fips\tSTAT_CAUSE_CODE\tpopulation\testimated_houses\tallstate_policies_in_force\tallstate_pif_fraction\n",
        "\n",
        "# # [2023,37.916134, -122.310768, 6013, 1054436,274156, 27236, 0.09934489852 ]\n",
        "# #cerrito = np.array([[2023,37.916134, -122.310768, 6013, 1054436,274156, 27236, 0.09934489852 ]])\n",
        "\n",
        "# knn_model.predict(df.from_dict(cerrito))\n",
        "\n",
        "\n",
        "butte = {\"county_fips\": [6007], \"population\": [220287], \"estimated_houses\":[57274], \"allstate_policies_in_force\": [4829], \n",
        "            \"allstate_pif_fraction\": [0.084313999], \"Year\": [2013], \"LATITUDE\": [39.767380], \"LONGITUDE\": [-121.633759]}\n",
        "\n",
        "knn_model.predict(df.from_dict(butte))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 69,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "array([5.])"
            ]
          },
          "execution_count": 69,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#Toledo Arson Example\n",
        "\n",
        "# 437581\t113772\t12523\t0.110071019 41.651031, -83.541939\n",
        "# population\testimated_houses\tallstate_policies_in_force\tallstate_pif_fraction\n",
        "\n",
        "toledo = {\"county_fips\": [39095], \"population\": [437581], \"estimated_houses\":[113772], \"allstate_policies_in_force\": [12523], \n",
        "           \"allstate_pif_fraction\": [0.110071019], \"LATITUDE\": [41.651031], \"LONGITUDE\": [-83.541939]}\n",
        "\n",
        "knn_model.predict(df.from_dict(toledo))\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "STAT_CAUSE_CODE\n",
            "2.0    1\n",
            "Name: count, dtype: int64\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "array([7.])"
            ]
          },
          "execution_count": 76,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Maui county Fire caused by power line\n",
        "# latitude of Makawao is 20.856944, and the longitude is -156.313056.\n",
        "# population\testimated_houses\tallstate_policies_in_force\tallstate_pif_fraction\n",
        "# 15009\t   154834\t40258\t3483\t0.086516966\n",
        "# 20.878525, -156.683746\n",
        "toledo = {\"county_fips\": [15009], \"population\": [154834], \"estimated_houses\":[40258], \"allstate_policies_in_force\": [3483], \n",
        "           \"allstate_pif_fraction\": [0.086516966], \"LATITUDE\": [20.856944], \"LONGITUDE\": [-156.313056]}\n",
        "\n",
        "knn_model.predict(df.from_dict(toledo))\n",
        "#https://www.washingtonpost.com/climate-environment/2023/08/15/maui-fires-power-line-cause/\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "STAT_CAUSE_CODE\n",
            "1.0     42\n",
            "4.0     17\n",
            "2.0      2\n",
            "11.0     1\n",
            "10.0     1\n",
            "3.0      1\n",
            "7.0      1\n",
            "Name: count, dtype: int64\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "array([1.])"
            ]
          },
          "execution_count": 77,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Salt Lake City\n",
        "# 49035 \n",
        "# 1031391\t268162\t29253\t0.109087044\n",
        "\n",
        "# latitude of Makawao is 20.856944, and the longitude is -156.313056.\n",
        "# population\testimated_houses\tallstate_policies_in_force\tallstate_pif_fraction\n",
        "# 40.7608 -111.8910\n",
        "\n",
        "salt_lake = {\"county_fips\": [49035], \"population\": [1031391], \"estimated_houses\":[268162], \"allstate_policies_in_force\": [29253], \n",
        "           \"allstate_pif_fraction\": [0.109087044], \"Year\": [2023], \"LATITUDE\": [40.7608], \"LONGITUDE\": [-111.8910]}\n",
        "\n",
        "knn_model.predict(df.from_dict(salt_lake))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 332,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:767: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if not hasattr(array, \"sparse\") and array.dtypes.apply(is_sparse).any():\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy on the test set: 0.511\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:605: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype):\n",
            "c:\\Python310\\lib\\site-packages\\sklearn\\utils\\validation.py:614: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.\n",
            "  if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n"
          ]
        }
      ],
      "source": [
        "from sklearn.ensemble import GradientBoostingClassifier\n",
        "\n",
        "# Combine preprocessing with the GBM classifier in a pipeline\n",
        "gbm_model = Pipeline([\n",
        "    ('preprocessor', preprocessor),\n",
        "    ('classifier', GradientBoostingClassifier())  \n",
        "])\n",
        "\n",
        "# Fit the model on the training data\n",
        "gbm_model.fit(X_train, y_train)\n",
        "\n",
        "# Make predictions on the test set\n",
        "y_pred = gbm_model.predict(X_test)\n",
        "\n",
        "# Evaluate the model on the test set \n",
        "test_accuracy = accuracy_score(y_test, y_pred)\n",
        "print('Accuracy on the test set: %.3f' % test_accuracy)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}