preliminary-analysis-2.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled0.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p-JOdiB2vVaZ",
        "outputId": "b248504a-5d23-478c-facb-1b08c7fbc448"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tK5DxtntW197"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eOgLxTs9W6fq"
      },
      "source": [
        "ROOT_FOLDER = '/content/drive/MyDrive/'"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oKFHw4bxW9bj"
      },
      "source": [
        "# data is now our pandas DataFrame containing all of the data from our csv file\n",
        "df = pd.read_csv(ROOT_FOLDER + \"eviction_with_census_tract.csv\",index_col=0)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "viv12eQ6XJLT",
        "outputId": "df3442a2-ad62-4173-8f60-b6795517bd5d"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0.1</th>\n",
              "      <th>Join_Count</th>\n",
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              "      <th>Addr_type</th>\n",
              "      <th>ARC_Street</th>\n",
              "      <th>ARC_City</th>\n",
              "      <th>ARC_State</th>\n",
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              "      <th>luc_2</th>\n",
              "      <th>...</th>\n",
              "      <th>owner_addr</th>\n",
              "      <th>owner_city</th>\n",
              "      <th>owner_stat</th>\n",
              "      <th>owner_zip</th>\n",
              "      <th>fy</th>\n",
              "      <th>lot_areaft</th>\n",
              "      <th>far</th>\n",
              "      <th>pct_imperv</th>\n",
              "      <th>pct_bldg</th>\n",
              "      <th>pct_pave</th>\n",
              "      <th>landv_pac</th>\n",
              "      <th>bldgv_psf</th>\n",
              "      <th>totv_pac</th>\n",
              "      <th>bldlnd_rat</th>\n",
              "      <th>sqm_imperv</th>\n",
              "      <th>sqm_bldg</th>\n",
              "      <th>sqm_pave</th>\n",
              "      <th>realesttyp</th>\n",
              "      <th>temp</th>\n",
              "      <th>st_area_sh</th>\n",
              "      <th>st_length_</th>\n",
              "      <th>geometry</th>\n",
              "      <th>CoreName</th>\n",
              "      <th>CleanName</th>\n",
              "      <th>Corp</th>\n",
              "      <th>EntityName</th>\n",
              "      <th>DataID</th>\n",
              "      <th>FEIN</th>\n",
              "      <th>Owner_Groups_All</th>\n",
              "      <th>Only_Groups</th>\n",
              "      <th>index_right</th>\n",
              "      <th>STATEFP</th>\n",
              "      <th>COUNTYFP</th>\n",
              "      <th>TRACTCE</th>\n",
              "      <th>AFFGEOID</th>\n",
              "      <th>GEOID</th>\n",
              "      <th>NAME</th>\n",
              "      <th>LSAD</th>\n",
              "      <th>ALAND</th>\n",
              "      <th>AWATER</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>92.63</td>\n",
              "      <td>A</td>\n",
              "      <td>159 BROOKLINE ROAD 8, TOWNSEND, MA, 01469</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>159  Brookline Road 5</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>2048SU000012</td>\n",
              "      <td>ayer district</td>\n",
              "      <td>2020-11-10</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>159  Brookline Road 5</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>821985</td>\n",
              "      <td>299</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>M_185312_938643</td>\n",
              "      <td>FEE</td>\n",
              "      <td>38</td>\n",
              "      <td>38 9 0</td>\n",
              "      <td>1</td>\n",
              "      <td>83300.0</td>\n",
              "      <td>563900.0</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>650900.0</td>\n",
              "      <td>195500.0</td>\n",
              "      <td>20090831.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>301</td>\n",
              "      <td>301</td>\n",
              "      <td>...</td>\n",
              "      <td>15 SCALES LANE</td>\n",
              "      <td>TOWNSEND</td>\n",
              "      <td>MA</td>\n",
              "      <td>01469</td>\n",
              "      <td>2019</td>\n",
              "      <td>1.000173e+05</td>\n",
              "      <td>0.044572</td>\n",
              "      <td>31.934645</td>\n",
              "      <td>4.924409</td>\n",
              "      <td>27.010236</td>\n",
              "      <td>3.627919e+04</td>\n",
              "      <td>126.491700</td>\n",
              "      <td>2.834829e+05</td>\n",
              "      <td>6.813926</td>\n",
              "      <td>2967.338976</td>\n",
              "      <td>457.571717</td>\n",
              "      <td>2509.767258</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9291.917091</td>\n",
              "      <td>436.954349</td>\n",
              "      <td>POINT (185305.2413596544 938650.9030090374)</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1171.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>301101.0</td>\n",
              "      <td>1400000US25017301101</td>\n",
              "      <td>2.501730e+10</td>\n",
              "      <td>3011.01</td>\n",
              "      <td>CT</td>\n",
              "      <td>44272760.0</td>\n",
              "      <td>54203.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>97.89</td>\n",
              "      <td>A</td>\n",
              "      <td>21 SCHOOL STREET 3, ATTLEBORO, MA, 02703</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>21 School Street Apt 3</td>\n",
              "      <td>Attleboro</td>\n",
              "      <td>MA</td>\n",
              "      <td>2703.0</td>\n",
              "      <td>2034SU000044</td>\n",
              "      <td>attleboro district</td>\n",
              "      <td>2020-11-13</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Attleboro</td>\n",
              "      <td>MA</td>\n",
              "      <td>21 School Street Apt 3</td>\n",
              "      <td>2703.0</td>\n",
              "      <td>51329</td>\n",
              "      <td>16</td>\n",
              "      <td>Attleboro</td>\n",
              "      <td>M_218112_854353</td>\n",
              "      <td>FEE</td>\n",
              "      <td>39</td>\n",
              "      <td>39_181</td>\n",
              "      <td>1</td>\n",
              "      <td>70100.0</td>\n",
              "      <td>255000.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>325100.0</td>\n",
              "      <td>350500.0</td>\n",
              "      <td>20101018.0</td>\n",
              "      <td>6285.0</td>\n",
              "      <td>4680.0</td>\n",
              "      <td>1110</td>\n",
              "      <td>1110</td>\n",
              "      <td>...</td>\n",
              "      <td>32 STATION ST</td>\n",
              "      <td>SHARON</td>\n",
              "      <td>MA</td>\n",
              "      <td>02067</td>\n",
              "      <td>2019</td>\n",
              "      <td>2.578051e+03</td>\n",
              "      <td>2.437888</td>\n",
              "      <td>98.803573</td>\n",
              "      <td>71.631631</td>\n",
              "      <td>27.171941</td>\n",
              "      <td>1.184443e+06</td>\n",
              "      <td>40.572792</td>\n",
              "      <td>5.493047e+06</td>\n",
              "      <td>3.637660</td>\n",
              "      <td>236.643156</td>\n",
              "      <td>171.563992</td>\n",
              "      <td>65.079165</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>239.509129</td>\n",
              "      <td>65.749524</td>\n",
              "      <td>POINT (218112.614739474 854353.7222426279)</td>\n",
              "      <td>TRUXTON RONALD D AND AHUVA F</td>\n",
              "      <td>TRUXTON RONALD D AND AHUVA F</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>TRUXTON RONALD D AND AHUVA F</td>\n",
              "      <td>NaN</td>\n",
              "      <td>389.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>631600.0</td>\n",
              "      <td>1400000US25005631600</td>\n",
              "      <td>2.500563e+10</td>\n",
              "      <td>6316.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>1571486.0</td>\n",
              "      <td>23449.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>100.00</td>\n",
              "      <td>M</td>\n",
              "      <td>171 ROUTE 6A, SANDWICH, MA, 02563</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>171 ROUTE 6A</td>\n",
              "      <td>SANDWICH</td>\n",
              "      <td>MA</td>\n",
              "      <td>2563.0</td>\n",
              "      <td>2025SU000057</td>\n",
              "      <td>barnstable district</td>\n",
              "      <td>2020-11-09</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Sandwich</td>\n",
              "      <td>MA</td>\n",
              "      <td>171 Route 6A, Room 1 (Upstairs)</td>\n",
              "      <td>2563.0</td>\n",
              "      <td>2022847</td>\n",
              "      <td>261</td>\n",
              "      <td>Sandwich</td>\n",
              "      <td>F_932826_2736632</td>\n",
              "      <td>FEE</td>\n",
              "      <td>66</td>\n",
              "      <td>66-030-</td>\n",
              "      <td>1</td>\n",
              "      <td>116000.0</td>\n",
              "      <td>133400.0</td>\n",
              "      <td>5300.0</td>\n",
              "      <td>254700.0</td>\n",
              "      <td>300000.0</td>\n",
              "      <td>20041006.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1346.0</td>\n",
              "      <td>101</td>\n",
              "      <td>101</td>\n",
              "      <td>...</td>\n",
              "      <td>171 ROUTE 6A</td>\n",
              "      <td>SANDWICH</td>\n",
              "      <td>MA</td>\n",
              "      <td>02563</td>\n",
              "      <td>2011</td>\n",
              "      <td>1.233307e+04</td>\n",
              "      <td>0.109137</td>\n",
              "      <td>18.775621</td>\n",
              "      <td>10.928205</td>\n",
              "      <td>7.847415</td>\n",
              "      <td>4.097081e+05</td>\n",
              "      <td>99.108470</td>\n",
              "      <td>8.995918e+05</td>\n",
              "      <td>1.195690</td>\n",
              "      <td>215.127232</td>\n",
              "      <td>125.213147</td>\n",
              "      <td>89.914085</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1145.778535</td>\n",
              "      <td>171.797499</td>\n",
              "      <td>POINT (284312.402709826 834112.9964528072)</td>\n",
              "      <td>DELLEA SUSAN A</td>\n",
              "      <td>DELLEA SUSAN A</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>DELLEA SUSAN A</td>\n",
              "      <td>NaN</td>\n",
              "      <td>57.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>13300.0</td>\n",
              "      <td>1400000US25001013300</td>\n",
              "      <td>2.500101e+10</td>\n",
              "      <td>133.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>12813860.0</td>\n",
              "      <td>1665619.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>90.53</td>\n",
              "      <td>A</td>\n",
              "      <td>10 THACHER BROOK CIRCLE 8, ATTLEBORO, MA, 02703</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>10 Thacher Brook Circle  Apt 3</td>\n",
              "      <td>Attleboro</td>\n",
              "      <td>MA</td>\n",
              "      <td>2703.0</td>\n",
              "      <td>2034SU000043</td>\n",
              "      <td>attleboro district</td>\n",
              "      <td>2020-11-12</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Attleboro</td>\n",
              "      <td>MA</td>\n",
              "      <td>10 Thacher Brook Circle  Apt 3</td>\n",
              "      <td>2703.0</td>\n",
              "      <td>58944</td>\n",
              "      <td>16</td>\n",
              "      <td>Attleboro</td>\n",
              "      <td>M_218630_853510</td>\n",
              "      <td>TAX</td>\n",
              "      <td>53</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>2722000.0</td>\n",
              "      <td>13018200.0</td>\n",
              "      <td>431300.0</td>\n",
              "      <td>16171500.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>19850101.0</td>\n",
              "      <td>12204.0</td>\n",
              "      <td>11110.0</td>\n",
              "      <td>000</td>\n",
              "      <td>000</td>\n",
              "      <td>...</td>\n",
              "      <td>7 WELLS AVE SUITE 14</td>\n",
              "      <td>NEWTON</td>\n",
              "      <td>MA</td>\n",
              "      <td>02459</td>\n",
              "      <td>2019</td>\n",
              "      <td>1.202846e+06</td>\n",
              "      <td>0.010146</td>\n",
              "      <td>26.128661</td>\n",
              "      <td>7.213033</td>\n",
              "      <td>18.915628</td>\n",
              "      <td>9.857484e+04</td>\n",
              "      <td>1066.715831</td>\n",
              "      <td>5.856367e+05</td>\n",
              "      <td>4.941036</td>\n",
              "      <td>29198.248811</td>\n",
              "      <td>8060.417943</td>\n",
              "      <td>21137.830868</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>111748.020917</td>\n",
              "      <td>2501.159490</td>\n",
              "      <td>POINT (218724.8575637158 853790.9962384583)</td>\n",
              "      <td>ETON THAMES</td>\n",
              "      <td>ETON THAMES ASSOCIATION LIMITED</td>\n",
              "      <td>True</td>\n",
              "      <td>ETON THAMES ASSOCIATES LIMITED PARTNERSHIP</td>\n",
              "      <td>00ec9c</td>\n",
              "      <td>L86003423</td>\n",
              "      <td>00ec9c</td>\n",
              "      <td>NaN</td>\n",
              "      <td>390.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>631800.0</td>\n",
              "      <td>1400000US25005631800</td>\n",
              "      <td>2.500563e+10</td>\n",
              "      <td>6318.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>12001536.0</td>\n",
              "      <td>305704.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>100.00</td>\n",
              "      <td>A</td>\n",
              "      <td>75 CHARLES STREET 2, HYANNIS, MA, 02601</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>75 Charles Street #2</td>\n",
              "      <td>Hyannis</td>\n",
              "      <td>MA</td>\n",
              "      <td>2601.0</td>\n",
              "      <td>2025SU000065</td>\n",
              "      <td>barnstable district</td>\n",
              "      <td>2020-11-16</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Hyannis</td>\n",
              "      <td>MA</td>\n",
              "      <td>75 Charles Street #2</td>\n",
              "      <td>2601.0</td>\n",
              "      <td>84778</td>\n",
              "      <td>20</td>\n",
              "      <td>Barnstable</td>\n",
              "      <td>F_987792_2702297</td>\n",
              "      <td>FEE</td>\n",
              "      <td>309</td>\n",
              "      <td>309_256</td>\n",
              "      <td>1</td>\n",
              "      <td>90000.0</td>\n",
              "      <td>147900.0</td>\n",
              "      <td>36300.0</td>\n",
              "      <td>274200.0</td>\n",
              "      <td>865000.0</td>\n",
              "      <td>20070403.0</td>\n",
              "      <td>3260.0</td>\n",
              "      <td>2080.0</td>\n",
              "      <td>1110</td>\n",
              "      <td>1110</td>\n",
              "      <td>...</td>\n",
              "      <td>474 CRAIGVILLE BEACH ROAD</td>\n",
              "      <td>HYANNIS</td>\n",
              "      <td>MA</td>\n",
              "      <td>02647</td>\n",
              "      <td>2018</td>\n",
              "      <td>9.049301e+03</td>\n",
              "      <td>0.360249</td>\n",
              "      <td>40.872368</td>\n",
              "      <td>11.540806</td>\n",
              "      <td>29.331562</td>\n",
              "      <td>4.332268e+05</td>\n",
              "      <td>45.368098</td>\n",
              "      <td>1.319898e+06</td>\n",
              "      <td>2.046667</td>\n",
              "      <td>343.616939</td>\n",
              "      <td>97.024385</td>\n",
              "      <td>246.592554</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>840.707280</td>\n",
              "      <td>121.604951</td>\n",
              "      <td>POINT (301074.556216199 823658.6264352691)</td>\n",
              "      <td>HOSTETTER ADAM J AND DANIEL C JR</td>\n",
              "      <td>HOSTETTER ADAM J AND DANIEL C JR TRUST</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>HOSTETTER ADAM J AND DANIEL C JR TRUST</td>\n",
              "      <td>NaN</td>\n",
              "      <td>118.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>15300.0</td>\n",
              "      <td>1400000US25001015300</td>\n",
              "      <td>2.500102e+10</td>\n",
              "      <td>153.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>13212205.0</td>\n",
              "      <td>531166.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7918</th>\n",
              "      <td>7918</td>\n",
              "      <td>0</td>\n",
              "      <td>7918</td>\n",
              "      <td>NaN</td>\n",
              "      <td>U</td>\n",
              "      <td>0.00</td>\n",
              "      <td>A</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>248 Meadow Drive</td>\n",
              "      <td>Raynham</td>\n",
              "      <td>MA</td>\n",
              "      <td>2767.0</td>\n",
              "      <td>21H83SP00216TA</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-19</td>\n",
              "      <td>Efiled SP Summons and Complaint - Cause</td>\n",
              "      <td>Raynham</td>\n",
              "      <td>MA</td>\n",
              "      <td>248 Meadow Drive</td>\n",
              "      <td>2767.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>POINT (-inf -inf)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7919</th>\n",
              "      <td>7919</td>\n",
              "      <td>0</td>\n",
              "      <td>7919</td>\n",
              "      <td>NaN</td>\n",
              "      <td>U</td>\n",
              "      <td>0.00</td>\n",
              "      <td>A</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>202 Meadow Drive</td>\n",
              "      <td>Raynham</td>\n",
              "      <td>MA</td>\n",
              "      <td>2767.0</td>\n",
              "      <td>21H83SP00215TA</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-19</td>\n",
              "      <td>Efiled SP Summons and Complaint - Cause</td>\n",
              "      <td>Raynham</td>\n",
              "      <td>MA</td>\n",
              "      <td>202 Meadow Drive</td>\n",
              "      <td>2767.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>POINT (-inf -inf)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7920</th>\n",
              "      <td>7920</td>\n",
              "      <td>0</td>\n",
              "      <td>7920</td>\n",
              "      <td>NaN</td>\n",
              "      <td>U</td>\n",
              "      <td>0.00</td>\n",
              "      <td>A</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>27 Melville Street Apt 1</td>\n",
              "      <td>Fall River</td>\n",
              "      <td>MA</td>\n",
              "      <td>2724.0</td>\n",
              "      <td>21H83SP00228FR</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-20</td>\n",
              "      <td>Efiled SP Summons and Complaint - Non-payment ...</td>\n",
              "      <td>Fall River</td>\n",
              "      <td>MA</td>\n",
              "      <td>27 Melville Street Apt 1</td>\n",
              "      <td>2724.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>POINT (-inf -inf)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7921</th>\n",
              "      <td>7921</td>\n",
              "      <td>0</td>\n",
              "      <td>7921</td>\n",
              "      <td>NaN</td>\n",
              "      <td>U</td>\n",
              "      <td>0.00</td>\n",
              "      <td>A</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>617 Summer Street 3rd Floor</td>\n",
              "      <td>New Bedford</td>\n",
              "      <td>MA</td>\n",
              "      <td>2740.0</td>\n",
              "      <td>21H83SP00240NB</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-21</td>\n",
              "      <td>Efiled SP Summons and Complaint - Cause</td>\n",
              "      <td>New Bedford</td>\n",
              "      <td>MA</td>\n",
              "      <td>617 Summer Street 3rd Floor</td>\n",
              "      <td>2740.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>POINT (-inf -inf)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7922</th>\n",
              "      <td>7922</td>\n",
              "      <td>0</td>\n",
              "      <td>7922</td>\n",
              "      <td>NaN</td>\n",
              "      <td>U</td>\n",
              "      <td>0.00</td>\n",
              "      <td>A</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>50 Main Street 4108</td>\n",
              "      <td>North Easton</td>\n",
              "      <td>MA</td>\n",
              "      <td>2356.0</td>\n",
              "      <td>21H83SP00261TA</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-22</td>\n",
              "      <td>Efiled SP Summons and Complaint - Non-payment ...</td>\n",
              "      <td>North Easton</td>\n",
              "      <td>MA</td>\n",
              "      <td>50 Main Street 4108</td>\n",
              "      <td>2356.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>POINT (-inf -inf)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <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>5498 rows × 92 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      Unnamed: 0.1  Join_Count  TARGET_FID  ... LSAD       ALAND     AWATER\n",
              "0                0           1           0  ...   CT  44272760.0    54203.0\n",
              "1                1           1           1  ...   CT   1571486.0    23449.0\n",
              "2                2           1           2  ...   CT  12813860.0  1665619.0\n",
              "3                3           1           3  ...   CT  12001536.0   305704.0\n",
              "4                4           1           4  ...   CT  13212205.0   531166.0\n",
              "...            ...         ...         ...  ...  ...         ...        ...\n",
              "7918          7918           0        7918  ...  NaN         NaN        NaN\n",
              "7919          7919           0        7919  ...  NaN         NaN        NaN\n",
              "7920          7920           0        7920  ...  NaN         NaN        NaN\n",
              "7921          7921           0        7921  ...  NaN         NaN        NaN\n",
              "7922          7922           0        7922  ...  NaN         NaN        NaN\n",
              "\n",
              "[5498 rows x 92 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OEmUCsgGXKyz",
        "outputId": "bec8b0dc-dcc9-40b4-d460-4fb9e977584a"
      },
      "source": [
        "#show columns\n",
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Unnamed: 0.1', 'Join_Count', 'TARGET_FID', 'Loc_name', 'Status',\n",
              "       'Score', 'Match_type', 'Match_addr', 'User_fld', 'Addr_type',\n",
              "       'ARC_Street', 'ARC_City', 'ARC_State', 'ARC_ZIP', 'case_numbe',\n",
              "       'court_divi', 'file_date', 'initiating', 'property_a', 'property_1',\n",
              "       'property_2', 'property_3', 'mapc_id', 'muni_id', 'muni', 'parloc_id',\n",
              "       'poly_typ', 'map_num', 'mappar_id', 'loc_id_cnt', 'land_value',\n",
              "       'bldg_value', 'othr_value', 'total_valu', 'ls_price', 'ls_date',\n",
              "       'bldg_area', 'res_area', 'luc_1', 'luc_2', 'luc_adj_1', 'luc_adj_2',\n",
              "       'num_units', 'units_est', 'units_src', 'num_rooms', 'yr_built',\n",
              "       'site_addr', 'addr_str', 'addr_num', 'addr_zip', 'owner_name',\n",
              "       'owner_addr', 'owner_city', 'owner_stat', 'owner_zip', 'fy',\n",
              "       'lot_areaft', 'far', 'pct_imperv', 'pct_bldg', 'pct_pave', 'landv_pac',\n",
              "       'bldgv_psf', 'totv_pac', 'bldlnd_rat', 'sqm_imperv', 'sqm_bldg',\n",
              "       'sqm_pave', 'realesttyp', 'temp', 'st_area_sh', 'st_length_',\n",
              "       'geometry', 'CoreName', 'CleanName', 'Corp', 'EntityName', 'DataID',\n",
              "       'FEIN', 'Owner_Groups_All', 'Only_Groups', 'index_right', 'STATEFP',\n",
              "       'COUNTYFP', 'TRACTCE', 'AFFGEOID', 'GEOID', 'NAME', 'LSAD', 'ALAND',\n",
              "       'AWATER'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SPl5oJsEXQ3V",
        "outputId": "5f22f968-821a-4a3a-cb7a-a292595c5988"
      },
      "source": [
        "df['realesttyp'][df['realesttyp'] > 0].describe().round(1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    4648.0\n",
              "mean        3.6\n",
              "std         2.1\n",
              "min         1.0\n",
              "25%         2.0\n",
              "50%         4.0\n",
              "75%         4.0\n",
              "max        12.0\n",
              "Name: realesttyp, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "33MDKLCRXfHL"
      },
      "source": [
        "#pick out data with 'real estate' that are not common residential and analysis houses attributes(price, house size, year_built, year sold, and room numbers)."
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yjQ0GvdiXjUE"
      },
      "source": [
        "![image.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X0BqJ11PXhOo",
        "outputId": "7a845749-62aa-42c5-98fc-b6944d944946"
      },
      "source": [
        "df['realesttyp'][df['realesttyp'] > 6].describe().round(1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    337.0\n",
              "mean       9.6\n",
              "std        1.7\n",
              "min        7.0\n",
              "25%        8.0\n",
              "50%        9.0\n",
              "75%       11.0\n",
              "max       12.0\n",
              "Name: realesttyp, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BDUy_jRVYOSA",
        "outputId": "1cbf44ec-161e-4ff5-9b19-0c3017a83464"
      },
      "source": [
        "df['realesttyp'][df['realesttyp'] > 6].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8.0     113\n",
              "12.0     72\n",
              "9.0      72\n",
              "11.0     64\n",
              "7.0      15\n",
              "10.0      1\n",
              "Name: realesttyp, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CfW4CAh5YU55"
      },
      "source": [
        "df_non_residential = df[df['realesttyp'] > 6]"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "9iIoBD1FYbcW",
        "outputId": "a26964ba-c894-482f-c441-8dbf362a7f39"
      },
      "source": [
        "df_non_residential"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0.1</th>\n",
              "      <th>Join_Count</th>\n",
              "      <th>TARGET_FID</th>\n",
              "      <th>Loc_name</th>\n",
              "      <th>Status</th>\n",
              "      <th>Score</th>\n",
              "      <th>Match_type</th>\n",
              "      <th>Match_addr</th>\n",
              "      <th>User_fld</th>\n",
              "      <th>Addr_type</th>\n",
              "      <th>ARC_Street</th>\n",
              "      <th>ARC_City</th>\n",
              "      <th>ARC_State</th>\n",
              "      <th>ARC_ZIP</th>\n",
              "      <th>case_numbe</th>\n",
              "      <th>court_divi</th>\n",
              "      <th>file_date</th>\n",
              "      <th>initiating</th>\n",
              "      <th>property_a</th>\n",
              "      <th>property_1</th>\n",
              "      <th>property_2</th>\n",
              "      <th>property_3</th>\n",
              "      <th>mapc_id</th>\n",
              "      <th>muni_id</th>\n",
              "      <th>muni</th>\n",
              "      <th>parloc_id</th>\n",
              "      <th>poly_typ</th>\n",
              "      <th>map_num</th>\n",
              "      <th>mappar_id</th>\n",
              "      <th>loc_id_cnt</th>\n",
              "      <th>land_value</th>\n",
              "      <th>bldg_value</th>\n",
              "      <th>othr_value</th>\n",
              "      <th>total_valu</th>\n",
              "      <th>ls_price</th>\n",
              "      <th>ls_date</th>\n",
              "      <th>bldg_area</th>\n",
              "      <th>res_area</th>\n",
              "      <th>luc_1</th>\n",
              "      <th>luc_2</th>\n",
              "      <th>...</th>\n",
              "      <th>owner_addr</th>\n",
              "      <th>owner_city</th>\n",
              "      <th>owner_stat</th>\n",
              "      <th>owner_zip</th>\n",
              "      <th>fy</th>\n",
              "      <th>lot_areaft</th>\n",
              "      <th>far</th>\n",
              "      <th>pct_imperv</th>\n",
              "      <th>pct_bldg</th>\n",
              "      <th>pct_pave</th>\n",
              "      <th>landv_pac</th>\n",
              "      <th>bldgv_psf</th>\n",
              "      <th>totv_pac</th>\n",
              "      <th>bldlnd_rat</th>\n",
              "      <th>sqm_imperv</th>\n",
              "      <th>sqm_bldg</th>\n",
              "      <th>sqm_pave</th>\n",
              "      <th>realesttyp</th>\n",
              "      <th>temp</th>\n",
              "      <th>st_area_sh</th>\n",
              "      <th>st_length_</th>\n",
              "      <th>geometry</th>\n",
              "      <th>CoreName</th>\n",
              "      <th>CleanName</th>\n",
              "      <th>Corp</th>\n",
              "      <th>EntityName</th>\n",
              "      <th>DataID</th>\n",
              "      <th>FEIN</th>\n",
              "      <th>Owner_Groups_All</th>\n",
              "      <th>Only_Groups</th>\n",
              "      <th>index_right</th>\n",
              "      <th>STATEFP</th>\n",
              "      <th>COUNTYFP</th>\n",
              "      <th>TRACTCE</th>\n",
              "      <th>AFFGEOID</th>\n",
              "      <th>GEOID</th>\n",
              "      <th>NAME</th>\n",
              "      <th>LSAD</th>\n",
              "      <th>ALAND</th>\n",
              "      <th>AWATER</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>92.63</td>\n",
              "      <td>A</td>\n",
              "      <td>159 BROOKLINE ROAD 8, TOWNSEND, MA, 01469</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>159  Brookline Road 5</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>2048SU000012</td>\n",
              "      <td>ayer district</td>\n",
              "      <td>2020-11-10</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>159  Brookline Road 5</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>821985</td>\n",
              "      <td>299</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>M_185312_938643</td>\n",
              "      <td>FEE</td>\n",
              "      <td>38</td>\n",
              "      <td>38 9 0</td>\n",
              "      <td>1</td>\n",
              "      <td>83300.0</td>\n",
              "      <td>563900.0</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>650900.0</td>\n",
              "      <td>195500.0</td>\n",
              "      <td>20090831.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>301</td>\n",
              "      <td>301</td>\n",
              "      <td>...</td>\n",
              "      <td>15 SCALES LANE</td>\n",
              "      <td>TOWNSEND</td>\n",
              "      <td>MA</td>\n",
              "      <td>01469</td>\n",
              "      <td>2019</td>\n",
              "      <td>100017.345642</td>\n",
              "      <td>0.044572</td>\n",
              "      <td>31.934645</td>\n",
              "      <td>4.924409</td>\n",
              "      <td>27.010236</td>\n",
              "      <td>36279.187142</td>\n",
              "      <td>126.491700</td>\n",
              "      <td>2.834829e+05</td>\n",
              "      <td>6.813926</td>\n",
              "      <td>2967.338976</td>\n",
              "      <td>457.571717</td>\n",
              "      <td>2509.767258</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9291.917091</td>\n",
              "      <td>436.954349</td>\n",
              "      <td>POINT (185305.2413596544 938650.9030090374)</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1171.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>301101.0</td>\n",
              "      <td>1400000US25017301101</td>\n",
              "      <td>2.501730e+10</td>\n",
              "      <td>3011.01</td>\n",
              "      <td>CT</td>\n",
              "      <td>44272760.0</td>\n",
              "      <td>54203.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>MAD_ADDR_GEOG</td>\n",
              "      <td>M</td>\n",
              "      <td>92.63</td>\n",
              "      <td>A</td>\n",
              "      <td>159 BROOKLINE ROAD 8, TOWNSEND, MA, 01469</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>159 Brookline Road 9</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>2048SU000010</td>\n",
              "      <td>ayer district</td>\n",
              "      <td>2020-11-10</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>159 Brookline Road 9</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>821985</td>\n",
              "      <td>299</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>M_185312_938643</td>\n",
              "      <td>FEE</td>\n",
              "      <td>38</td>\n",
              "      <td>38 9 0</td>\n",
              "      <td>1</td>\n",
              "      <td>83300.0</td>\n",
              "      <td>563900.0</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>650900.0</td>\n",
              "      <td>195500.0</td>\n",
              "      <td>20090831.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>301</td>\n",
              "      <td>301</td>\n",
              "      <td>...</td>\n",
              "      <td>15 SCALES LANE</td>\n",
              "      <td>TOWNSEND</td>\n",
              "      <td>MA</td>\n",
              "      <td>01469</td>\n",
              "      <td>2019</td>\n",
              "      <td>100017.345642</td>\n",
              "      <td>0.044572</td>\n",
              "      <td>31.934645</td>\n",
              "      <td>4.924409</td>\n",
              "      <td>27.010236</td>\n",
              "      <td>36279.187142</td>\n",
              "      <td>126.491700</td>\n",
              "      <td>2.834829e+05</td>\n",
              "      <td>6.813926</td>\n",
              "      <td>2967.338976</td>\n",
              "      <td>457.571717</td>\n",
              "      <td>2509.767258</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9291.917091</td>\n",
              "      <td>436.954349</td>\n",
              "      <td>POINT (185305.2413596544 938650.9030090374)</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1171.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>301101.0</td>\n",
              "      <td>1400000US25017301101</td>\n",
              "      <td>2.501730e+10</td>\n",
              "      <td>3011.01</td>\n",
              "      <td>CT</td>\n",
              "      <td>44272760.0</td>\n",
              "      <td>54203.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>11</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>MAD_ADDR_GEOG</td>\n",
              "      <td>M</td>\n",
              "      <td>92.63</td>\n",
              "      <td>A</td>\n",
              "      <td>159 BROOKLINE ROAD 8, TOWNSEND, MA, 01469</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>159 Brookline Road Cabin 2</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>2048SU000009</td>\n",
              "      <td>ayer district</td>\n",
              "      <td>2020-11-10</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>159 Brookline Road Cabin 2</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>821985</td>\n",
              "      <td>299</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>M_185312_938643</td>\n",
              "      <td>FEE</td>\n",
              "      <td>38</td>\n",
              "      <td>38 9 0</td>\n",
              "      <td>1</td>\n",
              "      <td>83300.0</td>\n",
              "      <td>563900.0</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>650900.0</td>\n",
              "      <td>195500.0</td>\n",
              "      <td>20090831.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>301</td>\n",
              "      <td>301</td>\n",
              "      <td>...</td>\n",
              "      <td>15 SCALES LANE</td>\n",
              "      <td>TOWNSEND</td>\n",
              "      <td>MA</td>\n",
              "      <td>01469</td>\n",
              "      <td>2019</td>\n",
              "      <td>100017.345642</td>\n",
              "      <td>0.044572</td>\n",
              "      <td>31.934645</td>\n",
              "      <td>4.924409</td>\n",
              "      <td>27.010236</td>\n",
              "      <td>36279.187142</td>\n",
              "      <td>126.491700</td>\n",
              "      <td>2.834829e+05</td>\n",
              "      <td>6.813926</td>\n",
              "      <td>2967.338976</td>\n",
              "      <td>457.571717</td>\n",
              "      <td>2509.767258</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9291.917091</td>\n",
              "      <td>436.954349</td>\n",
              "      <td>POINT (185305.2413596544 938650.9030090374)</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1171.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>301101.0</td>\n",
              "      <td>1400000US25017301101</td>\n",
              "      <td>2.501730e+10</td>\n",
              "      <td>3011.01</td>\n",
              "      <td>CT</td>\n",
              "      <td>44272760.0</td>\n",
              "      <td>54203.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>17</td>\n",
              "      <td>1</td>\n",
              "      <td>17</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>89.91</td>\n",
              "      <td>M</td>\n",
              "      <td>159 BROOKLINE ROAD 8, TOWNSEND, MA, 01469</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>159 BROOKINE ROAD 8</td>\n",
              "      <td>TOWNSEND</td>\n",
              "      <td>MA</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>2048SU000011</td>\n",
              "      <td>ayer district</td>\n",
              "      <td>2020-11-10</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>MA</td>\n",
              "      <td>159 Brookine Road 8</td>\n",
              "      <td>1469.0</td>\n",
              "      <td>821985</td>\n",
              "      <td>299</td>\n",
              "      <td>Townsend</td>\n",
              "      <td>M_185312_938643</td>\n",
              "      <td>FEE</td>\n",
              "      <td>38</td>\n",
              "      <td>38 9 0</td>\n",
              "      <td>1</td>\n",
              "      <td>83300.0</td>\n",
              "      <td>563900.0</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>650900.0</td>\n",
              "      <td>195500.0</td>\n",
              "      <td>20090831.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>4458.0</td>\n",
              "      <td>301</td>\n",
              "      <td>301</td>\n",
              "      <td>...</td>\n",
              "      <td>15 SCALES LANE</td>\n",
              "      <td>TOWNSEND</td>\n",
              "      <td>MA</td>\n",
              "      <td>01469</td>\n",
              "      <td>2019</td>\n",
              "      <td>100017.345642</td>\n",
              "      <td>0.044572</td>\n",
              "      <td>31.934645</td>\n",
              "      <td>4.924409</td>\n",
              "      <td>27.010236</td>\n",
              "      <td>36279.187142</td>\n",
              "      <td>126.491700</td>\n",
              "      <td>2.834829e+05</td>\n",
              "      <td>6.813926</td>\n",
              "      <td>2967.338976</td>\n",
              "      <td>457.571717</td>\n",
              "      <td>2509.767258</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9291.917091</td>\n",
              "      <td>436.954349</td>\n",
              "      <td>POINT (185305.2413596544 938650.9030090374)</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>KING DANA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1171.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>301101.0</td>\n",
              "      <td>1400000US25017301101</td>\n",
              "      <td>2.501730e+10</td>\n",
              "      <td>3011.01</td>\n",
              "      <td>CT</td>\n",
              "      <td>44272760.0</td>\n",
              "      <td>54203.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>18</td>\n",
              "      <td>1</td>\n",
              "      <td>18</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>92.63</td>\n",
              "      <td>M</td>\n",
              "      <td>20 ROUTE 6A 1, SANDWICH, MA, 02563</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>20  ROUTE 6A, COTTAGE 6</td>\n",
              "      <td>SANDWICH</td>\n",
              "      <td>MA</td>\n",
              "      <td>2563.0</td>\n",
              "      <td>2025SU000058</td>\n",
              "      <td>barnstable district</td>\n",
              "      <td>2020-11-16</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Sandwich</td>\n",
              "      <td>MA</td>\n",
              "      <td>20  Route 6A, Cottage 6</td>\n",
              "      <td>2563.0</td>\n",
              "      <td>2025497</td>\n",
              "      <td>261</td>\n",
              "      <td>Sandwich</td>\n",
              "      <td>F_924051_2741057</td>\n",
              "      <td>FEE</td>\n",
              "      <td>86</td>\n",
              "      <td>86-082-</td>\n",
              "      <td>1</td>\n",
              "      <td>229700.0</td>\n",
              "      <td>92300.0</td>\n",
              "      <td>2200.0</td>\n",
              "      <td>324200.0</td>\n",
              "      <td>295000.0</td>\n",
              "      <td>20010102.0</td>\n",
              "      <td>252.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>302</td>\n",
              "      <td>302</td>\n",
              "      <td>...</td>\n",
              "      <td>87 CLARK STREET</td>\n",
              "      <td>BELMONT</td>\n",
              "      <td>MA</td>\n",
              "      <td>02478</td>\n",
              "      <td>2011</td>\n",
              "      <td>42433.585329</td>\n",
              "      <td>0.005939</td>\n",
              "      <td>30.291307</td>\n",
              "      <td>6.395003</td>\n",
              "      <td>23.896304</td>\n",
              "      <td>235797.468500</td>\n",
              "      <td>366.269841</td>\n",
              "      <td>3.328060e+05</td>\n",
              "      <td>0.411406</td>\n",
              "      <td>1194.146155</td>\n",
              "      <td>252.104291</td>\n",
              "      <td>942.041864</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3942.209303</td>\n",
              "      <td>270.144073</td>\n",
              "      <td>POINT (281657.2065987953 835485.7006546175)</td>\n",
              "      <td>ROZZI PANFILO E</td>\n",
              "      <td>ROZZI PANFILO E</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ROZZI PANFILO E</td>\n",
              "      <td>NaN</td>\n",
              "      <td>57.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>13300.0</td>\n",
              "      <td>1400000US25001013300</td>\n",
              "      <td>2.500101e+10</td>\n",
              "      <td>133.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>12813860.0</td>\n",
              "      <td>1665619.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7773</th>\n",
              "      <td>7773</td>\n",
              "      <td>1</td>\n",
              "      <td>7773</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>90.90</td>\n",
              "      <td>A</td>\n",
              "      <td>300 BEAL STREET, HINGHAM, MA, 02043</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>300 Beal Street Apt. #1307</td>\n",
              "      <td>Hingham</td>\n",
              "      <td>MA</td>\n",
              "      <td>2043.0</td>\n",
              "      <td>21H83SP00219PL</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-19</td>\n",
              "      <td>Efiled SP Summons and Complaint - Non-payment ...</td>\n",
              "      <td>Hingham</td>\n",
              "      <td>MA</td>\n",
              "      <td>300 Beal Street Apt. #1307</td>\n",
              "      <td>2043.0</td>\n",
              "      <td>2113621</td>\n",
              "      <td>131</td>\n",
              "      <td>Hingham</td>\n",
              "      <td>F_811743_2914906</td>\n",
              "      <td>FEE</td>\n",
              "      <td>046</td>\n",
              "      <td>1310460000000170</td>\n",
              "      <td>1</td>\n",
              "      <td>667100.0</td>\n",
              "      <td>2695600.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3362700.0</td>\n",
              "      <td>783835.0</td>\n",
              "      <td>19871022.0</td>\n",
              "      <td>24888.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>340</td>\n",
              "      <td>340</td>\n",
              "      <td>...</td>\n",
              "      <td>230 BEAL STREET</td>\n",
              "      <td>HINGHAM</td>\n",
              "      <td>MA</td>\n",
              "      <td>02043</td>\n",
              "      <td>2011</td>\n",
              "      <td>527034.774221</td>\n",
              "      <td>0.047223</td>\n",
              "      <td>28.483937</td>\n",
              "      <td>5.331766</td>\n",
              "      <td>23.152171</td>\n",
              "      <td>55136.543965</td>\n",
              "      <td>108.309225</td>\n",
              "      <td>2.779297e+05</td>\n",
              "      <td>4.040774</td>\n",
              "      <td>13946.683669</td>\n",
              "      <td>2610.609914</td>\n",
              "      <td>11336.073755</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>48963.328831</td>\n",
              "      <td>1085.285968</td>\n",
              "      <td>POINT (247385.3420107772 888554.9238538529)</td>\n",
              "      <td>HINGHAM MUTUAL FIRE INSURANCE</td>\n",
              "      <td>HINGHAM MUTUAL FIRE INSURANCE COMPANY</td>\n",
              "      <td>True</td>\n",
              "      <td>HINGHAM MUTUAL FIRE INSURANCE COMPANY</td>\n",
              "      <td>007scy</td>\n",
              "      <td>41442510</td>\n",
              "      <td>007scy</td>\n",
              "      <td>NaN</td>\n",
              "      <td>396.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>501102.0</td>\n",
              "      <td>1400000US25023501102</td>\n",
              "      <td>2.502350e+10</td>\n",
              "      <td>5011.02</td>\n",
              "      <td>CT</td>\n",
              "      <td>11379311.0</td>\n",
              "      <td>2794461.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7776</th>\n",
              "      <td>7776</td>\n",
              "      <td>1</td>\n",
              "      <td>7776</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>97.89</td>\n",
              "      <td>A</td>\n",
              "      <td>34 CHURCH AVENUE G11, WAREHAM, MA, 02571</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>34 Church Avenue Unit G11</td>\n",
              "      <td>Wareham</td>\n",
              "      <td>MA</td>\n",
              "      <td>2571.0</td>\n",
              "      <td>21H83SP00232PL</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-21</td>\n",
              "      <td>Efiled SP Summons and Complaint - Cause</td>\n",
              "      <td>Wareham</td>\n",
              "      <td>MA</td>\n",
              "      <td>34 Church Avenue Unit G11</td>\n",
              "      <td>2571.0</td>\n",
              "      <td>863899</td>\n",
              "      <td>310</td>\n",
              "      <td>Wareham</td>\n",
              "      <td>M_265089_834087</td>\n",
              "      <td>FEE</td>\n",
              "      <td>47</td>\n",
              "      <td>47_1164</td>\n",
              "      <td>1</td>\n",
              "      <td>422500.0</td>\n",
              "      <td>2837000.0</td>\n",
              "      <td>32800.0</td>\n",
              "      <td>3292300.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>19010101.0</td>\n",
              "      <td>1272.0</td>\n",
              "      <td>1272.0</td>\n",
              "      <td>9970</td>\n",
              "      <td>9970</td>\n",
              "      <td>...</td>\n",
              "      <td>57 SANDWICH RD APT 51</td>\n",
              "      <td>WAREHAM</td>\n",
              "      <td>MA</td>\n",
              "      <td>02571</td>\n",
              "      <td>2018</td>\n",
              "      <td>280196.456768</td>\n",
              "      <td>0.004540</td>\n",
              "      <td>32.470278</td>\n",
              "      <td>9.886796</td>\n",
              "      <td>22.583482</td>\n",
              "      <td>65682.843432</td>\n",
              "      <td>2230.345912</td>\n",
              "      <td>5.118287e+05</td>\n",
              "      <td>6.792426</td>\n",
              "      <td>8452.367749</td>\n",
              "      <td>2573.640808</td>\n",
              "      <td>5878.726941</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>26031.111444</td>\n",
              "      <td>783.252407</td>\n",
              "      <td>POINT (265102.4580198713 834064.073377282)</td>\n",
              "      <td>WAREHAM HOUSING</td>\n",
              "      <td>WAREHAM HOUSING AUTHORITY</td>\n",
              "      <td>True</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WAREHAM HOUSING AUTHORITY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>700.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>545400.0</td>\n",
              "      <td>1400000US25023545400</td>\n",
              "      <td>2.502355e+10</td>\n",
              "      <td>5454.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>16031870.0</td>\n",
              "      <td>17982421.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7782</th>\n",
              "      <td>7782</td>\n",
              "      <td>1</td>\n",
              "      <td>7782</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>97.89</td>\n",
              "      <td>A</td>\n",
              "      <td>3221 CRANBERRY HIGHWAY 2, BUZZARDS BAY, MA, 02532</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>3221 Cranberry  Highway Apt 2</td>\n",
              "      <td>Buzzards Bay</td>\n",
              "      <td>MA</td>\n",
              "      <td>2532.0</td>\n",
              "      <td>21H83SP00238PL</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-21</td>\n",
              "      <td>Efiled SP Summons and Complaint - Non-payment ...</td>\n",
              "      <td>Buzzards Bay</td>\n",
              "      <td>MA</td>\n",
              "      <td>3221 Cranberry  Highway Apt 2</td>\n",
              "      <td>2532.0</td>\n",
              "      <td>865891</td>\n",
              "      <td>310</td>\n",
              "      <td>Wareham</td>\n",
              "      <td>M_272697_833536</td>\n",
              "      <td>FEE</td>\n",
              "      <td>6</td>\n",
              "      <td>6_B</td>\n",
              "      <td>1</td>\n",
              "      <td>101900.0</td>\n",
              "      <td>144500.0</td>\n",
              "      <td>45900.0</td>\n",
              "      <td>292300.0</td>\n",
              "      <td>310000.0</td>\n",
              "      <td>20150318.0</td>\n",
              "      <td>2764.0</td>\n",
              "      <td>1616.0</td>\n",
              "      <td>9970</td>\n",
              "      <td>9970</td>\n",
              "      <td>...</td>\n",
              "      <td>866 MAIN ST</td>\n",
              "      <td>OSTERVILLE</td>\n",
              "      <td>MA</td>\n",
              "      <td>02655</td>\n",
              "      <td>2018</td>\n",
              "      <td>11171.314366</td>\n",
              "      <td>0.247419</td>\n",
              "      <td>61.115259</td>\n",
              "      <td>22.635396</td>\n",
              "      <td>38.479863</td>\n",
              "      <td>397335.877804</td>\n",
              "      <td>52.279305</td>\n",
              "      <td>1.139757e+06</td>\n",
              "      <td>1.868499</td>\n",
              "      <td>634.283871</td>\n",
              "      <td>234.921147</td>\n",
              "      <td>399.362724</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1037.849473</td>\n",
              "      <td>130.972409</td>\n",
              "      <td>POINT (272695.0788932797 833534.2319701619)</td>\n",
              "      <td>3221 CRANBERRY</td>\n",
              "      <td>3221 CRANBERRY LLC</td>\n",
              "      <td>True</td>\n",
              "      <td>3221 CRANBERRY LLC</td>\n",
              "      <td>00nmbc</td>\n",
              "      <td>001164582</td>\n",
              "      <td>00nmbc</td>\n",
              "      <td>NaN</td>\n",
              "      <td>500.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>545300.0</td>\n",
              "      <td>1400000US25023545300</td>\n",
              "      <td>2.502355e+10</td>\n",
              "      <td>5453.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>7010779.0</td>\n",
              "      <td>3081500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7793</th>\n",
              "      <td>7793</td>\n",
              "      <td>1</td>\n",
              "      <td>7793</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>100.00</td>\n",
              "      <td>A</td>\n",
              "      <td>23 PRINCE STREET 2229, PLYMOUTH, MA, 02360</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>23 Prince Street #2229</td>\n",
              "      <td>Plymouth</td>\n",
              "      <td>MA</td>\n",
              "      <td>2360.0</td>\n",
              "      <td>21H83SP00245PL</td>\n",
              "      <td>southeast</td>\n",
              "      <td>2021-01-22</td>\n",
              "      <td>Efiled SP Summons and Complaint - Cause</td>\n",
              "      <td>Plymouth</td>\n",
              "      <td>MA</td>\n",
              "      <td>23 Prince Street #2229</td>\n",
              "      <td>2360.0</td>\n",
              "      <td>611195</td>\n",
              "      <td>239</td>\n",
              "      <td>Plymouth</td>\n",
              "      <td>F_878648_2817002</td>\n",
              "      <td>FEE</td>\n",
              "      <td>007</td>\n",
              "      <td>007-000-002A-007</td>\n",
              "      <td>1</td>\n",
              "      <td>1289700.0</td>\n",
              "      <td>4236000.0</td>\n",
              "      <td>15900.0</td>\n",
              "      <td>5541600.0</td>\n",
              "      <td>3857992.0</td>\n",
              "      <td>19831222.0</td>\n",
              "      <td>62166.0</td>\n",
              "      <td>62166.0</td>\n",
              "      <td>908</td>\n",
              "      <td>908</td>\n",
              "      <td>...</td>\n",
              "      <td>P O BOX 3537</td>\n",
              "      <td>PLYMOUTH</td>\n",
              "      <td>MA</td>\n",
              "      <td>02361</td>\n",
              "      <td>2019</td>\n",
              "      <td>422865.938018</td>\n",
              "      <td>0.147011</td>\n",
              "      <td>19.948482</td>\n",
              "      <td>8.646516</td>\n",
              "      <td>11.301966</td>\n",
              "      <td>132853.765104</td>\n",
              "      <td>68.140141</td>\n",
              "      <td>5.708478e+05</td>\n",
              "      <td>3.296813</td>\n",
              "      <td>7836.863649</td>\n",
              "      <td>3396.828274</td>\n",
              "      <td>4440.035375</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>39285.531561</td>\n",
              "      <td>1107.390220</td>\n",
              "      <td>POINT (267813.8975972697 858509.3329508735)</td>\n",
              "      <td>PLYMOUTH HOUSING</td>\n",
              "      <td>PLYMOUTH HOUSING AUTHORITY</td>\n",
              "      <td>True</td>\n",
              "      <td>PLYMOUTH HOUSING ASSOCIATES LIMITED PARTNERSHIP</td>\n",
              "      <td>00eg9k</td>\n",
              "      <td>L88029754</td>\n",
              "      <td>00eg9k</td>\n",
              "      <td>NaN</td>\n",
              "      <td>64.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>530200.0</td>\n",
              "      <td>1400000US25023530200</td>\n",
              "      <td>2.502353e+10</td>\n",
              "      <td>5302.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>3222349.0</td>\n",
              "      <td>5772766.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7810</th>\n",
              "      <td>7810</td>\n",
              "      <td>1</td>\n",
              "      <td>7810</td>\n",
              "      <td>MAD_ADDR_POST</td>\n",
              "      <td>M</td>\n",
              "      <td>100.00</td>\n",
              "      <td>A</td>\n",
              "      <td>278 OAKLAND STREET, SPRINGFIELD, MA, 01108</td>\n",
              "      <td>NaN</td>\n",
              "      <td>PointAddress</td>\n",
              "      <td>278  Oakland Street</td>\n",
              "      <td>Springfield</td>\n",
              "      <td>MA</td>\n",
              "      <td>1108.0</td>\n",
              "      <td>2123SU000004</td>\n",
              "      <td>springfield district</td>\n",
              "      <td>2021-01-19</td>\n",
              "      <td>Summary Process - Residential (c239)</td>\n",
              "      <td>Springfield</td>\n",
              "      <td>MA</td>\n",
              "      <td>278  Oakland Street</td>\n",
              "      <td>1108.0</td>\n",
              "      <td>754392</td>\n",
              "      <td>281</td>\n",
              "      <td>Springfield</td>\n",
              "      <td>F_367669_2860548</td>\n",
              "      <td>FEE</td>\n",
              "      <td>9210</td>\n",
              "      <td>09210-0052</td>\n",
              "      <td>1</td>\n",
              "      <td>21800.0</td>\n",
              "      <td>119800.0</td>\n",
              "      <td>1550.0</td>\n",
              "      <td>141600.0</td>\n",
              "      <td>120000.0</td>\n",
              "      <td>20140430.0</td>\n",
              "      <td>6151.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>325</td>\n",
              "      <td>325</td>\n",
              "      <td>...</td>\n",
              "      <td>35 CENTER ST</td>\n",
              "      <td>CHICOPEE</td>\n",
              "      <td>MA</td>\n",
              "      <td>01013</td>\n",
              "      <td>2019</td>\n",
              "      <td>7089.375451</td>\n",
              "      <td>0.867636</td>\n",
              "      <td>100.000043</td>\n",
              "      <td>53.564450</td>\n",
              "      <td>46.435593</td>\n",
              "      <td>133948.047556</td>\n",
              "      <td>19.476508</td>\n",
              "      <td>8.700479e+05</td>\n",
              "      <td>5.566514</td>\n",
              "      <td>658.624531</td>\n",
              "      <td>352.788453</td>\n",
              "      <td>305.836078</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>658.624741</td>\n",
              "      <td>116.920233</td>\n",
              "      <td>POINT (112064.6756619396 871901.7021886426)</td>\n",
              "      <td>CUSANO MARC J TRUSTEE</td>\n",
              "      <td>CUSANO MARC J TRUSTEE</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>CUSANO MARC J TRUSTEE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>310.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>802200.0</td>\n",
              "      <td>1400000US25013802200</td>\n",
              "      <td>2.501380e+10</td>\n",
              "      <td>8022.00</td>\n",
              "      <td>CT</td>\n",
              "      <td>584327.0</td>\n",
              "      <td>11319.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>337 rows × 92 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      Unnamed: 0.1  Join_Count  TARGET_FID  ... LSAD       ALAND      AWATER\n",
              "0                0           1           0  ...   CT  44272760.0     54203.0\n",
              "6                6           1           6  ...   CT  44272760.0     54203.0\n",
              "11              11           1          11  ...   CT  44272760.0     54203.0\n",
              "17              17           1          17  ...   CT  44272760.0     54203.0\n",
              "18              18           1          18  ...   CT  12813860.0   1665619.0\n",
              "...            ...         ...         ...  ...  ...         ...         ...\n",
              "7773          7773           1        7773  ...   CT  11379311.0   2794461.0\n",
              "7776          7776           1        7776  ...   CT  16031870.0  17982421.0\n",
              "7782          7782           1        7782  ...   CT   7010779.0   3081500.0\n",
              "7793          7793           1        7793  ...   CT   3222349.0   5772766.0\n",
              "7810          7810           1        7810  ...   CT    584327.0     11319.0\n",
              "\n",
              "[337 rows x 92 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OkbTFsqzZArn",
        "outputId": "cf320653-72ab-4374-d839-4405b803d9c9"
      },
      "source": [
        "df_non_residential['ARC_City'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Worcester       90\n",
              "Framingham      31\n",
              "Dorchester      11\n",
              "Lowell           9\n",
              "New Bedford      8\n",
              "                ..\n",
              "NEW BEDFORD      1\n",
              "Foxboro          1\n",
              "Mattapan         1\n",
              "TOWNSEND         1\n",
              "South Hadley     1\n",
              "Name: ARC_City, Length: 90, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JIEYbkbS1yyx",
        "outputId": "e15b6416-f02c-4b51-8914-b19614e2c801"
      },
      "source": [
        "df_non_residential['initiating'].value_counts()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Efiled SP Summons and Complaint - Non-payment of Rent    230\n",
              "Summary Process - Residential (c239)                      44\n",
              "Efiled SP Summons and Complaint - Cause                   43\n",
              "SP Summons and Complaint - Non-payment of Rent            11\n",
              "Efiled SP Summons and Complaint - No Cause                 4\n",
              "SP Transfer- No Cause                                      1\n",
              "Efiled SP Summons and Complaint - Foreclosure              1\n",
              "SP Summons and Complaint - Cause                           1\n",
              "SP Summons and Complaint - No Cause                        1\n",
              "SP Transfer - Non-payment of Rent                          1\n",
              "Name: initiating, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zwu7vT9P2fV_",
        "outputId": "fe976d4c-9623-437c-8f83-f833101ba701"
      },
      "source": [
        "df_non_residential['initiating'][df['realesttyp'] == 12].value_counts()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Efiled SP Summons and Complaint - Non-payment of Rent    46\n",
              "Efiled SP Summons and Complaint - Cause                  22\n",
              "Summary Process - Residential (c239)                      2\n",
              "SP Summons and Complaint - Cause                          1\n",
              "SP Summons and Complaint - Non-payment of Rent            1\n",
              "Name: initiating, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hy-mjz4V2sJD",
        "outputId": "e5dc1745-a931-441e-cf1c-172945b186bb"
      },
      "source": [
        "df_non_residential['initiating'][df['realesttyp'] == 9].value_counts()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Efiled SP Summons and Complaint - Non-payment of Rent    51\n",
              "Summary Process - Residential (c239)                     11\n",
              "Efiled SP Summons and Complaint - Cause                   6\n",
              "Efiled SP Summons and Complaint - No Cause                2\n",
              "SP Summons and Complaint - Non-payment of Rent            2\n",
              "Name: initiating, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xNjcz4EFZXBO",
        "outputId": "7cb55413-e418-4f09-bcf0-338927dc261c"
      },
      "source": [
        "df_non_residential['num_rooms'][df['realesttyp'] == 7].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0    14\n",
              "9.0     1\n",
              "Name: num_rooms, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cK8LzxYec-Lk",
        "outputId": "f2738048-6b2c-478c-a4e2-0812f839f772"
      },
      "source": [
        "df_non_residential['num_rooms'][df['realesttyp'] == 8].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0      80\n",
              "12.0      6\n",
              "14.0      6\n",
              "7.0       4\n",
              "1.0       3\n",
              "3.0       2\n",
              "17.0      1\n",
              "96.0      1\n",
              "19.0      1\n",
              "112.0     1\n",
              "26.0      1\n",
              "6.0       1\n",
              "94.0      1\n",
              "23.0      1\n",
              "16.0      1\n",
              "10.0      1\n",
              "86.0      1\n",
              "21.0      1\n",
              "Name: num_rooms, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tjIj_WGJdDBw",
        "outputId": "fb8baabf-6e2a-41db-ee16-68cbe5fb3193"
      },
      "source": [
        "df_non_residential['num_rooms'][df['realesttyp'] == 9].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0      65\n",
              "26.0      4\n",
              "24.0      2\n",
              "100.0     1\n",
              "Name: num_rooms, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vZEKtMlqdKsW",
        "outputId": "a6760a34-a878-4025-aeaa-cc70506ce977"
      },
      "source": [
        "df_non_residential['num_rooms'][df['realesttyp'] == 10].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0    1\n",
              "Name: num_rooms, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DtM-rI3FdNho",
        "outputId": "17d887b2-3489-44c1-bc3d-e8aab90eb5a3"
      },
      "source": [
        "df_non_residential['num_rooms'][df['realesttyp'] == 11].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0    64\n",
              "Name: num_rooms, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yBJrqwWWdjnE",
        "outputId": "d254573f-7b62-465e-b040-c9d10da0422e"
      },
      "source": [
        "df_non_residential['num_units'][df['realesttyp'] == 11].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0    60\n",
              "1.0     3\n",
              "5.0     1\n",
              "Name: num_units, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ycXKQrLFdP6h",
        "outputId": "25cab315-4a40-4c81-9e65-a7122690ec85"
      },
      "source": [
        "df_non_residential['num_rooms'][df['realesttyp'] == 12].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0      53\n",
              "16.0      5\n",
              "3.0       2\n",
              "531.0     2\n",
              "20.0      2\n",
              "39.0      1\n",
              "12.0      1\n",
              "30.0      1\n",
              "8.0       1\n",
              "6.0       1\n",
              "895.0     1\n",
              "240.0     1\n",
              "24.0      1\n",
              "Name: num_rooms, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "srv1BOJDdpTz",
        "outputId": "84a823f5-083d-46b0-90ce-8f4558adee46"
      },
      "source": [
        "df_non_residential['num_units'][df['realesttyp'] == 12].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0      56\n",
              "173.0     2\n",
              "1.0       2\n",
              "96.0      2\n",
              "177.0     2\n",
              "150.0     2\n",
              "82.0      1\n",
              "71.0      1\n",
              "40.0      1\n",
              "250.0     1\n",
              "60.0      1\n",
              "117.0     1\n",
              "Name: num_units, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UKLvqqeCPTyk"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ff4_ZZA5Aszu"
      },
      "source": [
        "# Census Visualizations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fdrSphDQjF63"
      },
      "source": [
        "# data is now our pandas DataFrame containing all of the data from our csv file\n",
        "census = pd.read_csv(ROOT_FOLDER + \"MA_geographic.csv\",index_col=0)"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "id": "I5037Mb8BUVc",
        "outputId": "27da42a1-e815-4a42-8f77-397806ecf962"
      },
      "source": [
        "census"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Eviction Numbers</th>\n",
              "      <th>Estimate!!Total:</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!White alone</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!Black or African American alone</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!American Indian and Alaska Native alone</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!Asian alone</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!Native Hawaiian and Other Pacific Islander alone</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!Some other race alone</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!Two or more races:</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!Two or more races:!!Two races including Some other race</th>\n",
              "      <th>Estimate!!Total:!!Not Hispanic or Latino:!!Two or more races:!!Two races excluding Some other race, and three or more races</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!White alone</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!Black or African American alone</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!American Indian and Alaska Native alone</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!Asian alone</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!Native Hawaiian and Other Pacific Islander alone</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!Some other race alone</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!Two or more races:</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!Two or more races:!!Two races including Some other race</th>\n",
              "      <th>Estimate!!Total:!!Hispanic or Latino:!!Two or more races:!!Two races excluding Some other race, and three or more races</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Muni</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Worcester</th>\n",
              "      <td>576</td>\n",
              "      <td>185143</td>\n",
              "      <td>144633</td>\n",
              "      <td>102148</td>\n",
              "      <td>22594</td>\n",
              "      <td>712</td>\n",
              "      <td>13675</td>\n",
              "      <td>111</td>\n",
              "      <td>1096</td>\n",
              "      <td>4297</td>\n",
              "      <td>426</td>\n",
              "      <td>3871</td>\n",
              "      <td>40510</td>\n",
              "      <td>25894</td>\n",
              "      <td>2010</td>\n",
              "      <td>412</td>\n",
              "      <td>20</td>\n",
              "      <td>0</td>\n",
              "      <td>9131</td>\n",
              "      <td>3043</td>\n",
              "      <td>1240</td>\n",
              "      <td>1803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Boston</th>\n",
              "      <td>483</td>\n",
              "      <td>684379</td>\n",
              "      <td>548622</td>\n",
              "      <td>304524</td>\n",
              "      <td>155096</td>\n",
              "      <td>1376</td>\n",
              "      <td>65613</td>\n",
              "      <td>365</td>\n",
              "      <td>5278</td>\n",
              "      <td>16370</td>\n",
              "      <td>1849</td>\n",
              "      <td>14521</td>\n",
              "      <td>135757</td>\n",
              "      <td>56931</td>\n",
              "      <td>17555</td>\n",
              "      <td>641</td>\n",
              "      <td>594</td>\n",
              "      <td>53</td>\n",
              "      <td>40240</td>\n",
              "      <td>19743</td>\n",
              "      <td>2933</td>\n",
              "      <td>16810</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fall River</th>\n",
              "      <td>354</td>\n",
              "      <td>89388</td>\n",
              "      <td>79968</td>\n",
              "      <td>69030</td>\n",
              "      <td>4729</td>\n",
              "      <td>124</td>\n",
              "      <td>1680</td>\n",
              "      <td>0</td>\n",
              "      <td>741</td>\n",
              "      <td>3664</td>\n",
              "      <td>249</td>\n",
              "      <td>3415</td>\n",
              "      <td>9420</td>\n",
              "      <td>3025</td>\n",
              "      <td>509</td>\n",
              "      <td>0</td>\n",
              "      <td>45</td>\n",
              "      <td>43</td>\n",
              "      <td>5485</td>\n",
              "      <td>313</td>\n",
              "      <td>111</td>\n",
              "      <td>202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>New Bedford</th>\n",
              "      <td>293</td>\n",
              "      <td>95239</td>\n",
              "      <td>75413</td>\n",
              "      <td>57575</td>\n",
              "      <td>6051</td>\n",
              "      <td>27</td>\n",
              "      <td>1476</td>\n",
              "      <td>25</td>\n",
              "      <td>6820</td>\n",
              "      <td>3439</td>\n",
              "      <td>1528</td>\n",
              "      <td>1911</td>\n",
              "      <td>19826</td>\n",
              "      <td>2908</td>\n",
              "      <td>585</td>\n",
              "      <td>51</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>14755</td>\n",
              "      <td>1527</td>\n",
              "      <td>969</td>\n",
              "      <td>558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Springfield</th>\n",
              "      <td>171</td>\n",
              "      <td>154139</td>\n",
              "      <td>84838</td>\n",
              "      <td>48145</td>\n",
              "      <td>28543</td>\n",
              "      <td>312</td>\n",
              "      <td>3927</td>\n",
              "      <td>11</td>\n",
              "      <td>417</td>\n",
              "      <td>3483</td>\n",
              "      <td>204</td>\n",
              "      <td>3279</td>\n",
              "      <td>69301</td>\n",
              "      <td>49469</td>\n",
              "      <td>3735</td>\n",
              "      <td>366</td>\n",
              "      <td>230</td>\n",
              "      <td>0</td>\n",
              "      <td>12033</td>\n",
              "      <td>3468</td>\n",
              "      <td>1210</td>\n",
              "      <td>2258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Stow</th>\n",
              "      <td>1</td>\n",
              "      <td>7133</td>\n",
              "      <td>6929</td>\n",
              "      <td>6307</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>250</td>\n",
              "      <td>0</td>\n",
              "      <td>211</td>\n",
              "      <td>160</td>\n",
              "      <td>54</td>\n",
              "      <td>106</td>\n",
              "      <td>204</td>\n",
              "      <td>203</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Halifax</th>\n",
              "      <td>1</td>\n",
              "      <td>7842</td>\n",
              "      <td>7791</td>\n",
              "      <td>7543</td>\n",
              "      <td>182</td>\n",
              "      <td>7</td>\n",
              "      <td>28</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>31</td>\n",
              "      <td>0</td>\n",
              "      <td>31</td>\n",
              "      <td>51</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>51</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Boxborough</th>\n",
              "      <td>1</td>\n",
              "      <td>5561</td>\n",
              "      <td>5279</td>\n",
              "      <td>4080</td>\n",
              "      <td>41</td>\n",
              "      <td>0</td>\n",
              "      <td>1000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>158</td>\n",
              "      <td>0</td>\n",
              "      <td>158</td>\n",
              "      <td>282</td>\n",
              "      <td>173</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>94</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Wilmington</th>\n",
              "      <td>1</td>\n",
              "      <td>23377</td>\n",
              "      <td>23145</td>\n",
              "      <td>20338</td>\n",
              "      <td>949</td>\n",
              "      <td>0</td>\n",
              "      <td>1448</td>\n",
              "      <td>0</td>\n",
              "      <td>24</td>\n",
              "      <td>386</td>\n",
              "      <td>102</td>\n",
              "      <td>284</td>\n",
              "      <td>232</td>\n",
              "      <td>76</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>146</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Nahant</th>\n",
              "      <td>1</td>\n",
              "      <td>3502</td>\n",
              "      <td>3449</td>\n",
              "      <td>3341</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>78</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>53</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>33</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>243 rows × 22 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             Eviction Numbers  ...  Estimate!!Total:!!Hispanic or Latino:!!Two or more races:!!Two races excluding Some other race, and three or more races\n",
              "Muni                           ...                                                                                                                         \n",
              "Worcester                 576  ...                                               1803                                                                      \n",
              "Boston                    483  ...                                              16810                                                                      \n",
              "Fall River                354  ...                                                202                                                                      \n",
              "New Bedford               293  ...                                                558                                                                      \n",
              "Springfield               171  ...                                               2258                                                                      \n",
              "...                       ...  ...                                                ...                                                                      \n",
              "Stow                        1  ...                                                  0                                                                      \n",
              "Halifax                     1  ...                                                  0                                                                      \n",
              "Boxborough                  1  ...                                                 15                                                                      \n",
              "Wilmington                  1  ...                                                  0                                                                      \n",
              "Nahant                      1  ...                                                  2                                                                      \n",
              "\n",
              "[243 rows x 22 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "k4zA5Wn1B9bP",
        "outputId": "6940d65d-a974-4338-b496-bf005c6f1c13"
      },
      "source": [
        "#Worcester\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = {'White': 102148, 'Black or African American': 22594, 'American Indian and Alaska Native': 712, 'Asian': 13675, 'Native Hawaiian and Other Pacific Islander': 111, 'Hispanic or Latino': 40510}\n",
        "names = list(data.keys())\n",
        "values = list(data.values())\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.bar(range(len(data)), values, tick_label=names)\n",
        "plt.show()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "pmS6za72Xcy4",
        "outputId": "aacf1dfa-b294-49a8-bd39-82004cd1f3ce"
      },
      "source": [
        "# Data to plot\n",
        "labels = []\n",
        "sizes = []\n",
        "data = {'White': 102148, 'Black or African American': 22594, 'American Indian and Alaska Native': 712, 'Asian': 13675, 'Native Hawaiian and Other Pacific Islander': 111, 'Hispanic or Latino': 40510, 'other': 5393}\n",
        "for x, y in data.items():\n",
        "    labels.append(x)\n",
        "    sizes.append(y)\n",
        "\n",
        "# Plot\n",
        "plt.pie(sizes, labels=labels)\n",
        "plt.title(\"Worcester\")\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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jUiDsjc80Zn8TxuyuOOgATG7Ym58xxjQvEnQAJjcsIRpjTPNslGmBsIRojDHNs4RYIKwrwJg8NExWrxiwcfObA0qGhbuGS+yDa4A2oduDjsHkhiVEY/LEXqxZ+bXIk0vPCb/SZ9vbuun+zUfuoyL7dIv0WjGwZJ/lg0qjW/p1GdKlNNJzSIjQPiJiU3Tlxn1BB2BywxKiMQEazLpVV0ZqFn8uPKlvTzaNEmGIgi6fMXgeI4gjsGlH3V5vbZy311sb5+3cLiJFG/uVDH1rcEl0/YCSvaVncb++ESneV0S6Bng6nVVD0AGY3LCEaEyODWT96q9GYos+H57YqzcbR4vsfp/b2+91fUXqQycAbza1jx1a333VltrRq7bUJi+O9yrq/9bA0uHvDyodvr1P8eCuJeFue4ckZLVp22dH0AGY3LCEaEwO9KNuzVcj/110fvjFHn35aLQIJ6VarwEaPprWs2sEEGjQ1h0mVFe/Zt+6+jX7Lt0wY+fCLqGuaweUDHt7UOm+H/UvGRrpHuk9ICyRfUXEBoukxxJigbCEaEyW9GHDuq9EnlrwhfAL3fqxYYwIJ7a0zcJV3SdFtoVO8Q/jmYhjW3xzv+WbX++3fPPrO5eFCG3v02XwkkGl0TUDS/bZ0at4QM8uodKoiPTJxDE7mc1BB2BywxKiaWwDoIAN2GiDXmz88MuRp+d9Mfx81wHUpZUEE7bD9h1TenRL+qfMSEJMJU68eO22FQev3bbi4IVM3rm8a6TXikEl+7w3qDS6qW+XIV26RnruZQN4WNvWDUWkN/BFVf2Tf3wKcL2qnpGh2EwGWUI0u6mtKtserYitAQYEHUtH0YNNdZeGn513ceS5kkGsb1USTDZ9bY+JfbfIJxOPRbOXEJuyuekBPLWDS6LrBpTsTY/ifv2KCmsAT5sTItAbuBr4UyYCEZGIqloXbpZYQjSpLMcSYrO6s3nDl8IT5n0p8lzxENaOEeGE9uxvq8iW4snde+y+VOP50FD3A3hGNR7A07Oo/1uDSoe/P6hk+LY+XQZ3Kwl3GxaS0JCAwsymNemuKCLXAZf7h/cAxwL7i8hsYAIQA7qLyCPAKGAGcLGqqogcCdwCdPfHvExVV4rIi8Bs4ATgH8DNGTkrswdLiCaV5cDhQQeRb7qxZeNF4efnXhJ5NjKUNWNE+Fim9v2/up6T9t0kn0peJkgrx9TkVGhD/Zp9NzQawFMcKl03sGTvtweVRjf0LxnWWQbwpNVC9Anty8AxuE8yU4GLgVGqOtavcwruf+tQYAXwCvAxEZkK3AacraqrReQC4JfsSq7FqjouY2dkUrKEaFJ5L+gA8kVXtm76QviFOZeFnw7vLavHiHB8po/xkciG3pO69kjxVIe7/217fEvf5Ztf75tiAM/rg0qHfzCwZJ+GXsUDe3UJlQ7vIAN41gyrOjHdSjUnAI+q6iYAEfkPpOw+n6aqy/06s4Eo8CGuxTjBX64NAyuTtqluU/SmVSwhmlSWBx1AkErYtuX88IuzLw8/LcNl1WHZSILJYpt6vXrYR7u3DgFEyecWYtr8AJ6D1m5bcdBCXt25vGuk58qBJfu8O6g0urlfl71KukZ6Dg4RGp5nA3iy8eFwW9LPDbj3YQEWqOpxTWyzKQtxmEYsIZpUCi4hdmH71vPCE+dcHn4qvp+sPEyEpt6YMurDUGj9kIldu0vKi4X5cQ0xWzbv2DCkduP8IbUb5+9cFpGijf26DH1rUOnw9QNL9pEexX37FEmXfUWkW0BhtuZ/YRJwn4hU4X5x5wCXAuVpbLsEGCAix6nqq76L+SBVXdDqiE2bWUI0qRREQiymfts54Ulzvhp+ascB8t5oEY7JdQwPb+099aQP2aN1CCB0jhZia+zQ+u6rttaOXrW1NnlxvGdR/9pBpfusHFQS3d6ny6CuJeHuuRrAk3YLUVVnish9wDS/6B5VnSEir4jIfOAp3KCaVNtuF5HzgFtFpBfuvfn3gCXEHLKEaFLptAmxiB3bzw6/MueKcGz7QbJ8tAhHBxXLB+HwBwe+VNJNmpyGTXJ+20WeCm2oXxPdUL8munTDzJ0Li0Ol6waU7P324NLhfgBPn/5hieyX4QE8TZbPS0VVb8GNFE1e9sVGq72Y9Nw1ST/Phj0rGKnqKa2JwbSdJUSTSqdKiBF21J8RmjLnykjNtpHyzigRjgo6JoC/7ugz88y1nNrU853lGmK2bI9v6fve5tf7vtdoAE/vLoOWDCqJrh5Uuk9Dr+KBPf0Anr5tPIy10AqIJUSzh9qqsk3Ritg6oK1vIoEL07DjM6Fpc66KPLnlEKk9NCTk1ZD1dyOR5WOeLe4qbjRhEzr3NcRsiBMvXrdt5cHrtq08eFFd0gCecM/3B5YmBvAMKXYDeMLDRaSluSYtIRYQS4imKTOg6dZLPgoRbzgtNH3uVZEnN46Wtw4JiR4ZdExNuZM+Cy76gI83t461EDNnc8OGwbUb5w9OHsATlqJN/bvs9dag0uj6ASV7a8+ifn2KQl32SxrAswmoDSJeEwxLiKYpr9IBEqIQj58amjn3qsgTG8bKskNConlfUGBZUaT22OeLSgSavdaV5zfmd3gNWt9t1da3R63a+nby4njPon61A0uGrxxQMmzp8bdfab+DAmIJ0TRlStABNEWIx8eHZs+7OvJE3eGydGRYXBWQjuLWcL83vrYi9fRPjdibce6FNtSvjW6oXxt946OZc47nyqDjMTlkCdE0ZSp5NeuF6kmhufO+EXn8w3Gy5KCw6JigI2qL+cXFS09+LhwRKG5p3SCKe5vdzGh5FdOZWEI0KdVWla2LVsReBw4OLgrVE0LzF1wdfnzt0aHFB0UkflhwsWTGzcV9l393eXo3/RfifYh5xhJigbGEaJozhQAS4rGhBQuvDj+x+vjQggMiEh+V6+Nny7SSLgs+/VxYBC1JZ/08aZoXqm3A/BbXMp2KJUTTnCm40lNZd5QsXnx15PH3TwjNP6BIGg7JxTFz7bcl/dZV1mr690Bal2mQXi6vrqkPOgiTW5YQTXOyOrDmCHl9yTcij79/UmhutEgaRgAjsnm8IL3YtXT2WROkQdC0a3JaCzFQzwQdgMk9S4imOfOAjbgJSzNijCxbenXksRXjQ3P2KZYdBxPoNcrcubmkz9ablrXuvki7DzFQlhALkCVE06TaqrKGaEVsOjC+Pfs5RGqXXRN5bPknQrOGdZH6A4EDMxNhx1DTretr5z4vWwVNNedhk2xQTWBWllfXzA06CJN7lhBNS56jDQnxYHnnrWsij719amjG3iVSvz+wf+ZDy38K+vuufeTWJa0vGGAtxMBMCDoAEwxLiKYl/wF+mc6KB8ry2m9EHnv7tNBre5XK9gOBfbMbWv6r7tF96vn/Y6tAr9ZuK3YVMSjWXVqgLCGaZtVWlS2OVsQW08SAl31lxTvXRB5/6zOhaYO7yraDgWhOA8xjcYjf0a1Xjz8t0IPasr2lw0Ao1kIsWJYQTToeBX6QeDBc3l9+dfiJZWXhKQO7y9aRwD7BhZa//tKr56vn/4/6EBzaph1Yl2kQZpZX16wOOggTDEuIJh2PDpPVl349/PjSs8Kv9u8hWw4FhgUdVD6rh/p7u/UccM+8eJ+27sNaiIH4V9ABmOBYQjQtqq0qm64/6bVVhJODjqWjuL1Pr1fPf1E1pLSpuxRsUE0A4sADQQdhgtPS5JjGACDCw0HH0FFsE7Y+1K3HPqfO0nbdY2mTP+Xcc+XVNe8FHYQJjiVEk64Hgw6go/hN3z5TPz9R3wkrg9uzH+syzbm/BR2ACZYlRJOeyrqFwOygw8h3m0Q2Plra7aDTp+sB7d2XtRBzagNu8JgpYJYQTWv8PegA8t3P+/d97dzJ+kZY2au9+7IWYk79q7y6ZkvQQZhgWUI0rXEv8FHQQeSrupDUPV1SOvqsKRrNxP7E2oi5ZN2lxhKiaYXKujpcUjQp3NC/36zPTmFxJM7emdifpcOceRN4OeggTPAsIZrW+j3QEHQQ+WZNOLR6YknJEee+Eh+aqX2KWq9pjvyhvLrGPn4YS4imlSrranH1TU2S7w/ov7BsOvOK4pkrXWe1THNiDXBP0EGY/GAJ0bTFzUEHkE9WRMIrp3UpPvqCifF23WbRmHWZ5sQfyqtrNgcdhMkPlhBN61XWTQUmBx1Gvigf2P+N02Yyu7ghs1NcWfsw6z4Cbg86CJM/LCGatrJWIvBWUeTt+UVFx1z8QrxvpvdtCTHr7iyvrvkw6CBM/rCEaNrqMWBZ0EEE7bqB/Zd/fC6zuuygXWXaUrFBNVm1Dfhd0EGY/GIJ0bRNZV0c+EXQYQRpUXHRsjeKio699Ll4z6BjMa12X3l1zcqggzD5xRKiaY+/AzODDiIo1w3sv/rEBTqrtJ6R2di/qFgLMTu2A/8XdBAm/1hCNG3nWonfCTqMIMzsUrxoeSRyzOXPxrtk6xg2yjRrfl9eXfNm0EGY/GMJ0bRPZd1ECvC+xOsH9t907BKd3W0bo7N1DLFxNdnwPgXe1W+aZgnRZMJ3cd1QBeHl0pK5qyORcVc8Fc/q/49gXaZZUFFeXWP1eE1KlhBN+1XWvQn8IegwcqViQL/4EUvjc3psZUw2jxOyLtNMm4bN2GKaYQnRZMovgA+CDiLbnu7WdUZdODz2qv/Gs17P1bpMM0qBb1rNUtMcS4gmMyrrNgA3Bh1GtlX271s6+q34/N6bOSLrB1PLhxn09/LqmmlBB2HymyVEk0n3ANODDiJbHunebeqmUOiQb9TEt+bieNZCzJgNQEXQQZj8ZwnRZE5lXQNwEbAp6FAyLQ7xqn59+o58Rxf23ci4XBxTrIWYKd8sr655P+ggTP6zhGgyq7JuKVAedBiZ9veePaZsC4UOvObJhpyNUBT7/8yEf5ZX19hAGpMW+4czmVdZdxfwZNBhZMoO2HFr39577b9CX++/gaNzdVxrIbbbe8BVQQdhOg5LiCZbvkonGXV6Z+9er9aLRK99omFtLq/ric0Q3B4KXFpeXbM+6EBMx2EJ0WRHZd0HwFeCDqO9tsP2e3r33C/6vi4bvJ5jcnlsUfv/bIc/lFfXPB90EKZjsX84kz2VdTXAXUGH0R639O39aoPI0GufaHg/19f0bPqnNpuPjSo1bWAJ0WTbdcCSoINoiy0imx/q2eOQYau1duhajs318e22izbZAlxUXl2zLehATMdjCdFkV2XdZuA8oMPVj/xVvz7TVGTAtU80LBcI5z4Cq2XaSgpcUl5dMzfoQEzHZAnRZF9l3Xzc/YnxoENJ14aQ1D3evduYwev03eEf5L51CDYfYhvcWF5d80jQQZiOyxKiyY3KuieBHwYdRrp+0r/fLBXpc+0TDbUCkSBisC7TVnmovLrGpnUy7WIJ0eROZd1NwN+CDqMl60Khtc91LT1ywIe6Yv+VuR1ZuhsbVJOuKXSCEc0meJYQTa5dATwXdBDN+cGAfvMR6fHNJxveECgOKg5rIablHeCz5dU1Oakvazo3S4gmtyrr6oHPAXOCDiWVVeHwqsmlJUf33aCrDl6eu6o0qYiK/X82byNwZnl1zaqgAzGdQ1b+4USkQURmi8gcEZkpIsf75VERmd/Gfb4oIlkrquzjfbjRsmtFZJGIPJhi/XEicmu24kk6zu9F5D2R7L05ishVInJJtva/BzdV1OnAuzk7ZpquH9h/CSKl19TEFwuUBBmLtRCbtQU420aUmkzK1pvsFlUdq6pjgB8Av87ScVpNRPYYPi8iI3HD6k8UkW5JT10NnKqqFzVaP6Kqr6nqtVmONQScg0scJ2fpGBFVvVNVc1sAubJuBXAqrt5kXngnElk+u0vxcb026upD39ZAW4cAgoRwtxKY3W0Bziivrvlf0IGYziUXXTI9gT3qCfrW4iTfgtzZivTPfV9E5vkWZlWj7UIicp+I7DGiTEQ+ISKz/Lb3ikgXv7xWRG4SkZnA51PEeCFwP/AscLbf5k5gP+ApEfmOiFSKyP0i8gpwv4icIiI1ft3uIvJXf9y5IvI5v/wOEXlNRBaIyE+T4qwVkZ/6854nIiOaeO1OARYAd/gYE9tXisjf/Ov3toicKyL/5/f1tIgU+fWOFJGXRGSGiDwjIkP88hd9y/M14Ft+f9f75w4QkeeSWoFdTlYAABj4SURBVPf7+/N7PinexGsU9S3ou/05PisipU2cy54q65YAJwFvp71NFl03sH8tIkVXx+ILBNI/jywRjYeAhqDjyDNbcN2klgxNxmUrIZb6LsjFuEljf55inQ9wra8jgAuAWwFE5DO4pHSMb2H+X9I2EeBBYKmq3pC8MxEpAe4DLlDV0X7dryetslZVj1DV3bpFvQuAh4F/4BOPql4FrADGq+rv/HqHAJ9U1Qsbbf9joE5VR6vqYUDin/VHqjoOOAw4WUQOS9pmjT/3O4DrU8SEj+UfwKNAWSLRefsDHwfOAh4AXvDnvSVp3duA81T1SOBe4JdJ2xer6jhVvbnRMR8E/uhf++OBlcBW4Bwf73jgZpGd98gd6Nc/FPgQd30wfZV1bwInAm+0arsMW1JU9OaS4qLjemzWdWPf1JzMd9gSIS5YQky2BTjLapSabMl2l+kI4NPA35PeQBOKgLtFZB7wL1yyAfgk8FdV3QygquuStrkLmK+qv2RPBwNvqerr/vHfcK2PhOpUgfrrkmtU9R3geeBwEenbxHk9oapbUiz/JPDHxANVTbSIz/et0lnAoUnnCPAf/30GEE0RVzHuOttjqroBmAqclrTKU6paD8zDdfc+7ZfP8/s7GBgFTBCR2cANwLCk7fd4PUSkBzBUVR/157HV/x4E+JWIzMWNEB0KDPKbvaWqs5s7lxZV1r2L+10tbPW2GVI+qP8qRMJfeyo+V6B7UHEkE42DJcSErbhrhnk9Qtl0bFnvMlXVV4H+wIBGT30HWAWMAcaR3vD2ycB43xpsraZmcb8QGCEitcAyXBdvU62ctGeCF5F9cS2/T/hWY4zdB2kkai02kPrG79OA3sA8H9sJJHWbJrZX1ThQr6qJa01xvz8BFvgPJmN96/VTbTkXXJWZAcCRqjoW93tLnEtyzcimzqVllXUrcV3Es1tYM+Pmdile8nYkcmy3LVp31Ot6eK6P3yTXZboj6DDywFZcy3BC0IGYzi3rCdFfHwsDaxs91QtY6d/Qv8SuWpETgC+LSFe/fXJr7S/Af4F/ikjjN94lQFREDvCPvwS81EJsIeB8YLSqRlU1iuuubdwl2pIJwDeS9tsHl1g3AXUiMgj4TCv3eSHw1aS49gVOTbwuaVgCDBCR43xMRSJyaHMbqOpHwHIR+azfpos/Xi/gA1WtF5HxwPBWnkt6KutW47qBp2Vl/00oH9i/DhH56jPxWeLONS+IxoUOVO4uS9YBp1kyNLmQ7WuIs3Fdc5eqauOunz8Bl4rIHGAEvsWiqk8DTwCv+e13u76mqrfguiDvl6RbEVR1K/Bl4F++GzYO3NlCnCcC76nqiqRlE4FDEgNQ0vQLoI+IzPfnM15V5/g4FwMPAa+kuzOfhD6Na1UCoKqbgJeBM9PZh6puxxXVvsnHNBt3TbAlXwKu9d2jk4HBuOuK4/zreok/p+yorFuP64Ju9sNMpkwt6bLg/Ujk6NJt+tHxi3RsLo6ZLhtUw5vAceXVNRODDsQUBtnV02ZMHqnsVQT8jqSWdzacvM/QmevC4SOurml48ZR5eko2j9VadT2jr7+yb6Q36MCgYwnAFFw36eqgAzGFwyphmPxUWVdPZd01wGW4a0gZ93zX0lnrwuEjiut180nzdFQ2jtEevsu0EFuI9wPjLRmaXAukir8xaaus+xuVvebjRuXuk8ld39C/XwTg0ufi00NZKnzQHqIaorCuIcaB75dX1/w26EBMYbIWosl/lXUzgCPZdX9nuz3evdv0jeHQ6KIduvUTc3RkpvabURoXkEJpIa4ByiwZmiBZQjQdQ2XdGuBTQONCAq2moL/o16cnwEUvxKeGlLy8RldAo0yfBkaXV9c83eKanohsbPT4MhG53f+cs9q8IvIzEflklo9RKyL901x3rIicnvT4LBGpyF50nYt1mZqOo7KuAbieyl7TcRV++rRlNw/17D5layh0XKRBt582Qw/KaIwZJMTDIJ35PsQtwPfKq2tuz+ROVbWl0eWZPNaNmdyfuNrC7fmdj8Xd1/1fAFV9Ajdq36TBWoim46msq8ZV/flPS6s21gANt/TtMwjg/InxKWGlNbfX5JSoduYu01nAuEwnQ9hZ6zdRm/daEVnoaww/nPT8/SLyqogsFZEr/PJW1+wVV1f5PP/zUSIy2dcBnuYrPyXHJSLyG3971jwRucAvP0VcXeInSLNak4gc7eOf5Y95sK9u9TPgAn/b2wWNWs73icitfv03k+JOGVchshai6Zgq694HPkdlr3NxZfMGp7PZPb17vrpd5IRwg9afOU33y2qM7dRJu0zjwG+BH5dX12xvx35K/X3KCX1J3RKqAPZV1W0i0jtp+WHAsUA3YJaIxHD1lc9R1Q2+i3KKT1LgavZeqKpXiMg/cdWsHkjszCejalwt5eki0hPXAk52Lq4FNwZXvWu6iCTusTwCGKWqb6V5/ouBE1V1h++y/ZWqfk5EbgTGqeo1Pq7LGm03BFf1agTu9XqkqbhUdWWasXQalhBNx1ZZ9x8qe72Au7b45eZWrYf6O3v3Gg5w7uT4lHCcE3MRYtvFwyCd6UbhRcDXy6trMlF0YYsvIwjsfONPVZR9LvCgiDwGPJa0/HFfl3iLiLwAHI0rhPErETkJl7hbU7P3YFzlrekAvv5wYycA//BFSlaJyEvAUcAGYForkiG4ikp/E5EDcVOEFbWwfsJjvjrYQl9Bq7m4Cq6r1bpMTcdXWbeeyrrLcYNumnxTubVP71d3iOwdimvDOZM1o7dwZIN0nlGmHwLfBg7LUDJsjTJcD8IRuJZPohHQ+IOGkouavU1rTW1hcDMIvaCqo3DVq9Kt75x8HjYBdSOWEE3nUVk3ARgN3ALUJz+1VWTL33v1OAjgzKk6JRLPUj3WDBLVMNKhu0zjwN3AQeXVNX8or67J6QAhX9pxb1V9Afg+rlWVmMnkbBEpEZF+uKLy02lfzd4lwBAROcofu4fsWW95Eu76XlhEBuBmeGlr3d5e7Jpc+7Kk5R8BPfZYu3mZjKtDsy5T07lU1m0CyqnsdQdu/sfPA3JT397T4iIni2r8/EnxvB1IsxvXQuyoXaavANeWV9fMDDCGMPCAiPTCtYZuVdUPxc1ENxd4AXfN7OequkJEHgSe9DV7X6MVNXtVdbsfjHKbH3CzBVeTN/n2kEeB44A5uBbp91T1fWl6gvBkc0Uk8eHon7h5Yv8mIjeQVPPYn1OFv7766zTDTxlXmtt2KlbL1HRulb3GbRT52fHDhx2tIv1OnxaffNnz8XSKnAdue1G3dc8dGn0H3ZpXRcdb8BZwQ3l1zUNBB9IUEakENqqqFQEwu7EuU9O5Vda91v0nH56uIhegOunCl+KN5+XMW6IaBukoXabzgYuBA/M5GRrTHGshmoKyaMTIE3FD8U9vad2g1YdLN0wYfcBSdPORQcfSjCnAr4Ca8uoaezMxHZpdQzQFZeTiRZOASYtGjBwNfA/4Ann6fyDEQxDK1xbis8Cvy6trXgw6EGMyxVqIpqAtGjFyOPA14Iu0blRh1jWEirc8c9gh89CPjg46Fm898A/gnvLqmllBB2NMpllCNAZYNGKkAMfjEuP5uNGHgWoIRbY9O2b0bI1vOCbAMHYAzwD3AU+WV9dsa351YzqutAbViMhnRUTTHB7cJiIyTkRuzeL+TxGRmlZuk1wTMetV7dOMKSoi85t5/tsistUPNU8sa/W5p3OsNLZVEflm0rLbU5SSarzdZ0XkkKTHOXndRy5epCMXL3pl5OJF38CVtyoDHmT3YfM5JRoPBTioZi5QDgwrr645o7y65hFLhqazS/fayYXAy/77TzIdhLgK76/h7v3JS5muap9FF+JuMj4X+GvAsXwAfEtE7lLVdOtWfhaowRc5DuJ1H7l40Q7cbAH/XTRiZFfgLFzL8dOkXyKr3dwo01CuunDqcfcOPgP8t7y6Zm6OjmtM3mixhSgi3XG17r6CG4CQWH6KiLwkIo/7yulVInKRr/I+T0T29+sNEJF/i8h0//UxvzxRcf4V4P7kVoy4qvN/9fuZKyKf88vvEJHXxFWc/2lSLLUi8lPZVaW+2ZasP/a9IvKij/3apOd+JCKvi8jLuPqEieXJVe1v9OcyX0T+LP5OX7+/m/xr8LqI7FErU9pWUf9IcRX05wDfaOa89sdV4rgBlxhTrbNHlXy//FAf92z/mh/YaLv9/DZHNbWPFFYDzwOXpojjCv8azvF/H11F5Hhc8vmNj2P/xOsuIp8WkX8lbZ/89/IpH89MEfmX/5vNiJGLF20euXjRwyMXLzoLV0D8fOBPwAL2LP+VYRrKcnWtZbhzORvoV15dM768uqbKkqEpVOm0EM8GnlbV10VkrYgcqaoz/HNjgJHAOuBN4B5VPVpEvgV8E1e/8A/A71T1ZRHZB/cJNDFD+SHACaq6RUROSTrmj4E6VR0NICKJee9+pKrrRCQMPC8ih6lq4p93jaoeISJXA9cDX23hvEYA43FljpaIyB24CvhfwFV+jwAzcYV8G7tdVX/mY7sfOAN40j8X8a/B6bjWdOPuvq20vqL+X4FrVHWiiPymmXP6AvAwrhTTwSIySFVXNVpnjyr5/jhXAX9Q1QfFVe4P4wsb+4T3MHCZqs4RV8k/1T5SuQl4SkTubbT8P6p6t9//L4CvqOpt/rWoUdVH/HOJ9Z8D/iwi3VR1E3AB8LB/DW8APqmqm0Tk+8B1uGlwMmrk4kXrgH/5LxaNGNkfV+bqJFwx5MOB0kwdz515xrpMt+OS+GxcD8KE8uqaNzK0b2M6hXQS4oW4pAbuTfFCdiWJ6YkpQkRkGW4oNsA8XLIBlxAOSXpj65n0Cf4JX3G+sU+S1BpV1fX+x/NF5Eof9xBcQk0kxMTceDNw3YUtianqNmCbiHyAe/M/EXhUVTf7c2qq2vt4Efke0BU37cwCdiXE5DiiKbYVWlFRX9yUNb1VNTFNzP3AZ5qI60Jcso2LyL9xZcsazzfXVJX8V4EficgwXLJa6n9nA4DHgXNVdWEL+9iDqr4pIlNxXY7JRvlE2BvXqn2mqX34/ewQkaeBM0XkEdw1vu8BJ+P+Dl7x8Rb7c8m6kYsXrcH9vv8DsGjEyAhwKG7WhaNwH7qG4X7H6RZfbqRNpdvW4xJf8tei8uqa+ma3MqbANZsQRaQv8HFgtIgortWgIvJdv0ryRfZ40uN40r5DwLGqurXRvqEVFd5FZF9cy+8oVV0vIvex+5tM4tjpVqJvU/V6ESnBdTONU9V3xZWBak0cyRX160WklqYr6qfd2hCR0bgW5oSkxPAWeybERJX8c0QkCrwIoKoP+cRVBvxXRL6Ga/XXAe/gus0XNrePZvwKN+9a8kwH9wGf9S3Oy3AFllvyMHANrkfiNVX9yHdXT1DVlF3EueSvPc7xX39Jfm7RiJH9cIlxKLuSZPL3Abi/l7D/CgFhIbRN3WwR2/zXVlxX9ApgZarv5dU16zHGtFpLSeA84H5V/Vpigbi5slozj9yzuO7T3/jtxya1gpoyAXet7Nt+mz5AT1wCrRM3j9dnaPmNuLUmAveJyK9xr82ZwF2N1kkkrzW+pXse7s0+Xa2qqO+LEX8oIieo6su4hJrKhUClqu4s6Csib4lI4/2nrJIvIvsBb6rqrb5r+zBcQtwOnAM8IyIbVfWhpvbRzDksFpGFuNdzul/cA1gpIkX+nBL7a65a/0vAvcAVuOQIrlLKH0XkAFV9Q0S6AUNV9fWW4sqlkYsXrQXWsqtHI73tshOOMSaFlgbVXIirhJ7s3zQxYKMJ1wLj/ECNhbhrVS35BdBH3KCVOcB4VZ0DzMJdA3sINyIuo1R1Jm7W6znAU+x6805e50PclDbzcd18e6zTggdxr8c84BLSq6j/Zdyb/myaHmXxBfb8XT1KUtez93/Ar0VkFrt/IDofmO+PMQr4e+IJf83uDOA7InJWM/tozi9xLaGEHwNTcb/H5NfgYeC7fsDO/sk78BOY1uA+DNX4ZatxSfkfIjIX112atduDjDGdl92Yb4wxxmCzXZhOStIsJiEi//UDl4wxBc5aiKZTEpFqYC/gf6qa8WISxpjOx1qIptORFMUkRGSIiEz0N/zPF180QVxRh/7+58dEZIa4wghXJu1vo4j8UlwRgSl+UJcxppOxhGg6o53FJIC1InIk7j7IZ1R1LK6gRKqRzper6pG4+wivFZF+fnk3YIqqjsGNRL4i62eQxHf93pz0+Hp/u09z25wirvJP4vFVInJJBmLZWd83adnODxWZJkm1bEXkHkmqcxsUaaY2sIicIK7i02L/lfzBqnGd3hdFZFwG46qVXdW9nhWRwW3Yx87XWEQ+L6561gvSylrTLZ2bJFX+aq9Mvo55OQ+cMe2UqpjEE8C9/jaPx5q49edaETnH/7w37r7OtbhbTxJvgDOAU7MVeBO2AeeKyK9VdU2a25yCK0w+GUBV78xSbFmVXMtWVVuqPhUon4Aewt1fO9N/SHhGRN5T1RiN6vS281gRVd2R4qnxqrpGRH4F/BA3yj9tjV7jrwBX+Nu9II9rTbeGiIT9iPU9WAvRdCpJxSTu8UUPvou7pWQSrsTae7h7TS9ptN0puApJx/mW4Cx23XNar7sutqddxCGDdgB/Br7T+AkROVNEpvrbVJ4TkUG+WMJVuNtkZovIiYmWnYiMEJFpSdtH/S1AiZq5L/lu42dEZEhrA03V7exbGrf4n78lIm/6n/cTV8u4ufrAyTWEd7YEpB11jf05T/LrzEy0pH3L70URecS37h5MiuPTftlMmq6E9Q3gPn/7Fv7Dy/eACklRp9dv83lpVPtYRMIi8hv/eswVVyQjEd8kcRW0WkqqE4EDpOnaxWER+a1/veeKn5Um8RqLyI24yw5/8bG0WGs6FX+c+/xx5olIqr/hVtWGFpFSEXlYXOv1UZIKmEgTdY3938VN/vf3+abitYRoOptEMYnhqhpV1b1xFXtOAlb5+qn3AEc02q4XsF5VN/s30WNzGnXL/ghcJEnTenkv4ypBHY5rDX9PVWuBO3E1hMeq6qTEyqq6GCgWV/kJXE3YanEt59uA83y38b24e0dTSSTa2eLuW90r6blU3c6T2FXM40RcN/ZQ/3OiJOHtqnqUqo7CvcGd0cLr8SNVHYcrIHGyiByW9NwaVT0CuANX3aqxD4BT/ToXAMldgYfjCoIcAuwHfExcdaq7cYUljsQVeU/lUPasffwacKiqTsb1UnzX/06W+ecjqnq0P2Zi8NdXcLWcj8KVALwi6fd1BPAtVT2oiRgSzsCV0EzULj4cuBFXNQrgSlxpybGqehju/uidfK3m14CLVPW77G5nrWm/7f+aiWMsrlDGKF+bOtUMPM397lO9Pl8HNqvqSL/sSADZva7xET7+65L2tVZVj1DVh2mCdZmazuZCXEHxZP/GlYrbJCL1uK7ExtfTngauEpFFwBJcBZy84YvB/x3XBZZc/3cYLqENYVe5vpb8E5cIqvz3C3Azu4xiV+m/MK4UXCq/U9XfJh6Ia4kn7NHtrKpTfKuih1/2EO4Dyonsqv07XpquD5xKe+oaFwG3i8hYXIs/OblMU9Xl/rxm45LGRlyd4aV++QO4hJIJqWoffwo4THZdY+uF677f7uNr7nf8gog04F6LG2i67vAngTsT3a6quq4VMTdVazqVN4H9ROQ2IMauetfJmvvdp3p9TsJ/iFHVueIKcoD7ENtcXePqlk7MEqLpVFR1fIplt7J7KyD5uWjSw5RF01W1e9LPj9C6Un2Z9HvcDCzJn7JvA25R1SfEdftWprGfauBfIvIfQH0h99HAAlU9rq3Bye7dzptF5EV2dTtPxlVcWoJrMV4OHAeUS8v1gRsfp711jb8DrMINrgrh6sM23ra57ZuyENdaeTxp2ZG4N/impIpVgG+q6m4F7/3r21L95/HJ15lF5Pe0ru5wRvnfzxjgNFw3/vm4330ivvbWhk7WUl3jFmtnW5epMR2E/xT/T1yXWkJyXdnkeSebrAnru+sacF1fiU/NS4ABInIcgIgUicihrQyxuW7nSbgkNhF3fXY8sE1V60hdH7g5qeoatzbOlaoaB76Eaw03ZzFu5pnEdb+m3nD/CFzmW5747uKbcKUOofk6vcmeAb7uu7ERkYPE1ehti6bqDk8AviYiEX+Mvq3YZ6LWNH7bPk2t6LsxQ6r6b1yLtfGlitb+7sH9DX3R738UrtscXK/Ox0TkAP9cNxFpqWt5N5YQjelYbgaSb3GoxLX2ZgDJI1CfBM7x1/lSFeOvBi7GJVhUdTvuzegmcfWDZwPHp9iuOU8DEd/tXMXu3c6TcN2lE/0Iv3dx1z9bXR84A3WN/wRc6s9zBC20HNTN1HMlEPODMj5oYr2VuNf0bhFZjGsV36uqie6/Juv0NnIPrrU5U0Tm4yYYaGtvXlN1h+/BzWIz178Ojadna84etaabWXco8KLvfn4A+EHyk22sDX0H0N3/nf0Mf902E3WNrVKNMcYYg7UQjTHGGMASojHGGANYQjTGGGMAS4jGGGMMYAnRGGOMASwhGmOMMYAlRGOMMQaA/weFUiVmAVIkQQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "o53FOyE7w9q9",
        "outputId": "34d9ca2f-5177-4377-f168-2d739b85e297"
      },
      "source": [
        "#Boston\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = {'White': 304524, 'Black or African American': 155096, 'American Indian and Alaska Native': 1376, 'Asian': 65613\t, 'Native Hawaiian and Other Pacific Islander': 365, 'Hispanic or Latino': 135757}\n",
        "names = list(data.keys())\n",
        "values = list(data.values())\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.bar(range(len(data)), values, tick_label=names)\n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "clpWz8gjX2wB",
        "outputId": "70562920-6022-4595-8b56-1f52a3f6aee4"
      },
      "source": [
        "# Data to plot\n",
        "labels = []\n",
        "sizes = []\n",
        "data = {'White': 304524, 'Black or African American': 155096, 'American Indian and Alaska Native': 1376, 'Asian': 65613\t, 'Native Hawaiian and Other Pacific Islander': 365, 'Hispanic or Latino': 135757, 'other': 21648}\n",
        "for x, y in data.items():\n",
        "    labels.append(x)\n",
        "    sizes.append(y)\n",
        "\n",
        "# Plot\n",
        "plt.pie(sizes, labels=labels)\n",
        "plt.title(\"Boston\")\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "o1VpmDUQx1Ro",
        "outputId": "a98f9c24-629f-48c8-c78a-8e1c763ccd32"
      },
      "source": [
        "#Fall River\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = {'White': 69030, 'Black or African American': 4729, 'American Indian and Alaska Native': 124, 'Asian': 13675, 'Native Hawaiian and Other Pacific Islander': 0, 'Hispanic or Latino': 9420, 'other': 4405}\n",
        "names = list(data.keys())\n",
        "values = list(data.values())\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.bar(range(len(data)), values, tick_label=names)\n",
        "plt.show()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "C0sI3j4BYKCJ",
        "outputId": "abdd709a-a247-4ba4-dddd-ff4297f77a5f"
      },
      "source": [
        "# Data to plot\n",
        "labels = []\n",
        "sizes = []\n",
        "\n",
        "data = {'White': 69030, 'Black or African American': 4729, 'Asian': 13675, 'Hispanic or Latino': 9420, 'other': 4123}\n",
        "for x, y in data.items():\n",
        "    labels.append(x)\n",
        "    sizes.append(y)\n",
        "\n",
        "# Plot\n",
        "plt.pie(sizes, labels=labels)\n",
        "plt.title(\"Fall River\")\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vHWySUnMy3UN"
      },
      "source": [
        "Plots on top three cities based on density"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "PvXNh4FAyvK6",
        "outputId": "152f2ee1-a4ce-4c41-d313-bf5c1a4ac779"
      },
      "source": [
        "#Fall River\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = {'White': 69030, 'Black or African American': 4729, 'American Indian and Alaska Native': 124, 'Asian': 13675, 'Native Hawaiian and Other Pacific Islander': 0, 'Hispanic or Latino': 9420}\n",
        "names = list(data.keys())\n",
        "values = list(data.values())\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.bar(range(len(data)), values, tick_label=names)\n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "id": "fj65B1GyzJXG",
        "outputId": "f8b6863c-1520-483f-c3e7-df95a15cd879"
      },
      "source": [
        "#Worcester\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = {'White': 102148, 'Black or African American': 22594, 'American Indian and Alaska Native': 712, 'Asian': 13675, 'Native Hawaiian and Other Pacific Islander': 111, 'Hispanic or Latino': 40510}\n",
        "names = list(data.keys())\n",
        "values = list(data.values())\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.bar(range(len(data)), values, tick_label=names)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<BarContainer object of 6 artists>"
            ]
          },
          "metadata": {},
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "id": "hVVVk9wrzKRb",
        "outputId": "7934e9fa-c65a-4305-b43a-a7a525f5830c"
      },
      "source": [
        "#New Bedford\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = {'White': 57575, 'Black or African American': 6051, 'American Indian and Alaska Native': 27, 'Asian': 1476, 'Native Hawaiian and Other Pacific Islander': 25, 'Hispanic or Latino': }\n",
        "names = list(data.keys())\n",
        "values = list(data.values())\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.bar(range(len(data)), values, tick_label=names)\n",
        "plt.show()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "gHqalJ4CYRy9",
        "outputId": "f522d7e4-a81b-4a51-9539-28d94ee98acf"
      },
      "source": [
        "# Data to plot\n",
        "labels = []\n",
        "sizes = []\n",
        "data = {'White': 57575, 'Black or African American': 6051, 'Asian': 1476, 'Hispanic or Latino': 19826, 'other': 10259}\n",
        "for x, y in data.items():\n",
        "    labels.append(x)\n",
        "    sizes.append(y)\n",
        "\n",
        "# Plot\n",
        "plt.pie(sizes, labels=labels)\n",
        "plt.title(\"New Bedford\")\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Eb4wV/LhZwfcnK/jGQL7XAfzGCr4/WcE3xo7w45brdQDTIjaG76FcaqrP3rxiYqTtCXaE6aHdolVeZ/AbK/j+JF4HyFZ92Lzuwcg9SzpMDZzx4XHfmbm29+kjEMnxOleWesXrAH5jQzr+tN3rANnonEDZ/KkFN+RWLdJaQQr6ffTPUScse3IBqtu8zpalarwO4DdW8P3JCkxKqf4u78+Txuc9NPCtg9qs6L4qd3D0lZ6b5g0+texXOwO1+z/2MmGWqvU6gN9YwfcnK/gp0oHdldMKrp99fs6UUTVCJLys47aA0j12mbZVGw8fOe3WPm32bJzhVc4sVe11AL+xgu9PNqSTAoPkkw/nFYzdfohsGQrwuy6dpg+fL0fXt2xOZH+708p+eVqv9TMnoRpJbdKstdXrAH5jBd+f7Ag/ya7LeXXqq/l3Hp4ntUcAVAYC29esbpdbUMOxja13fMWzo46veHoeqpWpSZrVNnodwG/sKh1/soKfJPlU73sp/5dlJwZWjIx9/qc9ui288g1t1ixjvTbMHtJh5/9WzR582+ZITl69nwhMQmzyOoDf2BG+P9mQThIcIevXzC+4ekXdYr8iL3fV+h35vbvsZEhzt9Vuz4YjRky/tcdBVVtmJT6pcdkRfpys4PuTHeEn2DcDU+d8kH9Tu3ayt7Dua9f27LH+h29H1kuc9z/k1u7rcNqsO4f22Dh3IqqauLQG2Ddu/BgbNouTDen4kx3hJ4gQiTyS98fJXw2UjRI5sKBPanPQwsrqnOOO+7S2oGXbR/ove3L02l7Lyir6frcfItYWIzFsOKcF7Ajfn+wIPwE6s2PrrILr5n0tp2x0fcVeQX/Wo1v+5e9HFgk0a/y+IX3Wzxw6dM5vNkukemVrtmM+YwW/Bazg+9NWwIYIWmGYLFs2u+Daqh6yvcFx+Sc6Hjx9L3LsyCV6XCL22X732qNGTgt1Ldi7rSwR28tyG7wO4EdW8H0oXFK0D/if1zn8KpT7j8nP5//6mFyJHNLQMlUie/7UueNRX5utZTlK70TtO7d278HDZ95+SrdNC2xcv3U+8TqAH1nB969lXgfwm4PYV/VW/q1Tx+a+eYZI473U7+zWpSwi0vvCqZFOic4hIAOXPj76uI9fmIXqrkRvP0ss9TqAH1nB9y/7hY/D0fLpqvkFV6/uF1g9oqll1+fkrH+rXdtTTlweWdRmP8cnK9Oha6ecesrc+9ZLpGZVsvaRwZZ4HcCPrOD7lx3hN9PFOe/Pejf/lk5tZH+zxuKv69n9E0Ta/WBCZE+ys3XYtfqYEdNv65i/r3JOsveVYazgt4AVfP+yI/wmBIjUPpV336R7c58YKkLH5qyzoCC/4sP8vOE9t+qants5JdkZAfJq9nQ6fcYvTu66ZcmkVOwvA3w6bvwYuzS5Bazg+9dSwJp0NaAH2zbNKbhm8Zk5C+u9vr4h1/fsXoVI4EdvR5YLpGxiE0EDJy7+86hjPnl5OqpJ/2Thc3aw00JW8H0qXFK0G6jwOkc6OiOwcNGMgutqu8jOQfGs96/27cq25eSc1Gaf7hwQ1pOSla8xh6/5YPjgeQ+slkjtai/27xM2nNNCVvD9bbbXAdLN3blPTno6777jc0R7xbNeNVTf061Ld4CLJ0XmiYcTxXfcGe57+ozb2uXt3znPqwxpzgp+C1nB9zcr+K52VO16P/+mGZflvjtKJP6WIfd36TyjWuRIUY2cPV+PTEbGeORX7+4yYvptJ3beWmHj+geyiWZayAq+v1nBBwpl1fJ5BVdvPCqw/rSWrF8ZCGx//uD2AwC+tEBn50Y4PLEJW0bQnJMWPTzq6OWvTkO1yus8aWLtuPFjbCizhazg+9tCYL/XIbz0g5z/TP9P/m09C6TmqJZu46Ye3RaqSGeASyZGDkpcusQ4YvW7p588//dhidR+6nWWNPCB1wH8zAq+j7ktFqZ6ncMLudRUP59/96Q78v4+XIT2Ld3O8rzccNlBBcMB+q7W8g57OTFxKROn044VhafP+EVBXvWuBV5n8dh7XgfwMyv4/vdvrwOkWh82r5tbMLbi1ED5qNZu69qePTYgkgdw1Vu1aT1Han71zm6nT7+tf8ftn0z2OouH3vc6gJ9Zwfe/17wOkEpfDsyeP7XghtyOsmdAa7c1sW2bBWvzcocBdN2h6w/dzNDWJ0yugEZyBy948IwjV745FdV9XudJseXjxo+xNhStYAXf58IlRf8D5nudI/lU788dP+kveQ8ODIh2b/XWQH/Wvetnk5p8f0LkQ4G81m43VY5c9d8RJy38wydoZJ3XWVLIju5byQp+Zsjoo/wO7K6cWnBD2YW5k0eJJObu18c6Hjy9KhAoBMiv1qrBH2urPzGkWuftH59w+oxf5OZW71nkdZYUsfH7VrKCnxkytuAPkk8+nFcwdvuhsnlYorZZJbLn0c4dP7uq5/xpkTkB6JKo7adSwf4d3UdMv7Xw4B0rp3idJcn2A295HcLvrOBngHBJ0SJghdc5Eu26nFenvpp/5+F5UntEIrd7R7cusyMizqQmqlpUpn0Suf1UC2gkb8i8B0YesertKahm6mW6E2zS8tazgp85MuZqnXyq9/07//YpN+e9NEKENonc9vqcnPVvt2v72bSGI5bp3Pxajk7kPrxy9MrXR5646JEP0UgmTv/3otcBMoEV/MyREcM6h8uGNfMKrl5+YmDFyGRsP9rrPvr4svcize6k6Qddt5UPGD7zDs2pqcqkjpL7aMUBjYh0EpFrYx6PFpE3E5LMZ6zgZ45pwCavQ7TGuYFpcybm39iuvexNyixT0V730cfB9bq8824GJ2NfXjpo3/ZeI6eFjumw83+ZMq7/xrjxY3a0Yv1OwLVNLtVMIhJ3r6Z0YQU/Q4RLimqBN7zO0RJCJPJo3kOTHsp75OSA0DlZ+4n2uo8+vuqt2rXJ2pfXAlpTcMrc+0Yetvq9yahWe52nlZ6JZ2ERuUlElrhfPwFKgKNFZIGI3O8u1l5EXhaRChF5TkTEXXewiEwSkbki8ra453pEZKKIPCQic4AbEvnmUsm3f6lMvZ4Evu91iHh0ZsfWtwtCK3rI9lbfNdsYt9f9ZzdWHbxbtxy9LjUzWnnp2OWvnNF5+0cLF/W/ug8SaPX9Cx7YBPy3uQuLyGDge8AwQIBZwHeB/qo6yF1mNHAScAKwFufT8ekiMgt4GDhXVTeJyEXAPXz+/1S+qg7Bx+wIP4OES4qm4fyC+8JQKV82u+DaPT1ke1L/J3J73feIfe7KdyOLBdKuUVoydNuy5MTTZt1VnVOz14/zID83bvyYmjiWHwG8qqq7VXUX8ApQ3/mgMlVdo6oRYAEQBPoC/YF3RGQBcDtwaMw6L7TkDaQTK/iZ53deB2iOW3P/OeWF/LuPzpXIoU0v3Tq/7dp5RrVIMPo4t1b3Dy/XpJwnSFdt9m7tM2L6rUe127V2mtdZ4hAB/pSkbce2pajFGe0QYKmqDnK/Bqjql2OW252kLCljBT/zvAKEvQ7RkIPYV/VW/q1Tr8l9Y6QIBU2v0TrbA4HtL3RoPzD2ua/P0tkBpUdD62SqnEjNQcPm3HP6IZ9OmoxqPEfNXnlt3Pgxy+NcZwrwTRFpK87VWOfhDNl0aMa6HwLdReQ0ABHJE5ET4tx/WrOCn2Hck7d/8DpHfY6WT1fNL7h6db/A6hGp2udNPbotUpFOsc+dNz3SNVX7T0d9P37xjP5LH1+MRrZ4naUJD8S7gqrOA/4GlOEMbz6hqnOBae5J3PsbWXc/cAFwn4gsxBnqGd7Q8n4kqup1BpNgwVBpB2A10NHrLFEX57w/697cJ/qJpC7T8rzc8DcP6X1ItP0xwOCPIwtufTkS1+TmmWpPm25ryob8fHckp6Cv11nqMWPc+DEZVWzTgR3hZ6BwSdFO4DGvcwAEiNQ+lXffpHtznxiaymIPcG3PHhtjiz3A9ydEsq2lcIPaVm0+dOS00GFt96yf7nWWesR9dG+aZgU/c/0R8PT66x5s2zSn4JrFZ+YsHCVCSu9ofd/pdf+F/vZ9tuiqbjsy/1LMeORE9rc9tezu4b3XTpuEaq3XeVzLyZA7x9ONFfwMFS4pWoOH/UdGBhYtnlFwXW0X2Zny4ZMIRELdux5wyeVV/60Ni/3O16vwo3+MOmHZUwtQ3e51FuChcePHRLwOkYnslz+z/d6Lnf4y96nJz+SV9MsR7eXF/h/rdPCMqkCgX+xzbfdqZeHqzGujkEg9N80dfGrZr3YEavd/7GGMT3FuIDRJYAU/g4VLiuYBE1K1v3ZU7Xo//6YZV+S+c4aIN7NHVYns+XOnjgd0v7z0g8gCoeWTnWeLtlUbDx857dY+bao2zfQowu3jxo/Z49G+M54V/Mx3AykYyy+UVcvnFYzdcFRg/WnJ3ldjbu/edXZE5AufLAIRrR2zSDOiBXIq5ET2tzttVvGpPdfPmohzJ2qqLCDOvjkmPlbwM1y4pKgCeCiZ+/h+zn+n/yf/tp4FUu1pUV2fk7N+Qts2B5yU/fI8LcuJkPQ7ejPNCRXPjC6seGYuqqmaeOSnNnafXFbws8OvcMZGEyqXmurn8++efGfes8NFvB8uGdez+3JE2tZ9/qLJEc+z+VXvDWWnDJ19z9ZApDreO17jVTpu/BibpDzJrOBngXBJ0S7gp4ncZh82r5tbMLbi1ED5GYncbkvNK8gv/yim131U/3Bkabt9+G6C8nTSfs+6I0dMu7XHQXu3JKsxXy1wS5K2bWJYwc8S4ZKiF4CEHEF9OTB7/tSCG3I7yp60KaQ39Oy+D7eneawfvB2xeVATILd2X4fTZt45tMfGuRNJ/O35j48bP6Y8wds09bCCn12uo1UncFXvzx0/6S95Dw4MiKZNb/WXO7Qr256Tc8D1/t2369o+Wxla3zomfgLSf9mTo/t99I8yVHcmaLNbgDsTtC3TBCv4WSRcUlROCxurdWB35dSCG8ouzJ08SoScBEdrsWqo/k3XLvV2vvzh25GPxCb5Sbg+66YPO2XOvRslUrMyAZsbN278GF9PzeknVvCzzy+J8wTuIPnkw7kFY7cfKpuHJSlTi9XtdR9VsF93D1qhJ6U+UXbosPvTo0dMC3Up2Lttdis289K48WN8P6mIn1jBzzLuCdybm7v8uJzXpr6af+fh+VJ7RBJjtUh9ve6jvj0lMlfSqFtoJsqrreo4fOYdg7ttWjipBeP6G0ngxOKmeazgZ6FwSdHzNDFPaD7V+17Lv2PKLXkvjhChTYqixaW+XvcAqOpX5uphHkTKOoIGBi59bNRxH784C2dKwea6Ztz4MZuTFszUywp+9roCZwLnAxwuG9bMK7h6+aDA8vrmAk0Ly/Nyw7MPKqj3rt7Ri3V2Xi1HpjpTNjt07eRTh8y9b51EalY1Y/F/jBs/5pWkhzIHsIKfpcIlRZuA7+BcA/2ZcwPT5kzMv7Fde9mb1nO+1tfrPurSDyKe9PHJdgfvWn3siOm3dczfVzm3kcXWAT9OVSbzRVbws1i4pGgSzl24CJHII3l/mPRQ3iMnB4TOHkdrVH297qOO+VQ/7LgHO1nrkbyaPZ1On/GLQV22LJ1Yz8sR4Ipx48dsTXEs47KCb37dg23/nllw3byinFmjRNL7d6KhXvdRV71Va5f4eUzQnEGLHx19zCcvT0c1tvPlnePGj3nHs2Amvf/nNskXLimKlB007qqest2T3vXx+kung6fX7XUf1WmXbjpio81olS4OX/PB8MHzHlgtkdo1wOvAb7zOlO2s4BsortwInAfs9TpKY/aI7B7fqeMxDb3+vXciSwUKUpnJNK7jznDf4TNvXwtcPm78mES3ZDBxsoJvHMWVc4CxXsdozO3du86p2+s+KrdG9w37UE9IdSbTpO0F+3dcNm78GOtplAas4JvPFVc+jTP5edpZl5Oz7p16et1HnTcjUhZQ0qa/jwGcK8C+XVhR/pHXQYzDCr6p60bgn16HqGtcr+4r6ut1H/WNmd7Mn2sadX1hRbmdpE0jVvDNFxVXRoDLcU6ypYW5BQXlH+cd2Os+6tSKyPyCGo5NZSbTpF8UVpQ/6nUI80VW8M2BiitrgG8D73kdBeCGnt3q7XUfdcW7kZpU5jFNurewotyuyElDVvBN/Yor9wHnAtO9jPFihxyAyAIAAA58SURBVPazKuvpdR912EZd2WUnQ1KZyTTq4cKK8p97HcLUzwq+aVhx5W7ga8B8L3ZfDdX3du3c6Nj8VW/VrhZo8OjfpNRTwA1ehzANs4JvGldcWQmcA6R8Crr7unaeXiPSYFvm9nt023Gf2tF9mngJ+FFhRblda5/GrOCbphVXbgLOAlakapfbA4FtL3Zof2Jjy1z+fmShQINX7piUeR64tLCivLbJJY2nrOCb5imuXAucToqGd27s0W1xvb3uXYGI1oxcon1TkcU06vfAdworylsxV7JJFSv4pvmKK9cDo4B3k7mbT/LyVs5poNd91Ndma1mO0juZOUyjFLi5sKL8pzaM4x9W8E18iit34pzIfS5Zu7i2V/dNDfW6j7pwaqTBo3+TdPtxhnB+53UQEx8r+CZ+xZXVwGW4vfQT6b22beavy62/133Uicsji9rsJ60naMlgO4CvFlaUp93d2KZpVvBNyxRXKsWVdwGXkKAumxGI3Na9a5Pz5/5gQmRPU8uYpFgFjCqsKH/f6yCmZazgm9YprnweZ1x/XWs31Viv+6ieW3VNz+3W894DbwAnFVaUL/A6iGm5Jgu+iNSKyAIRWSgi80RkuPt8UESWtGSnIjJRRJJ2/bSb9/k6z10vIuUicsDYs4gMEZGkd4kUkYdE5FMRSdofWhEZKyKXJ2v79SquLAMGAy1ulNVUr/uoH70dWS6Q09L9mLjVALcC5xZWlG/zOoxpndxmLFOlqoMAROQc4F6cIzrPiUiOqtbWea4QpyCMFJF2qrrbfela4CxVXVNn+VxVnQPMSXLWAM4kI6txfn4fJGEfuao6PtHbbZbiynUUdzwHuB4oARqchrA+bq/7Rn+v2uzTnQPCavPVps6nwEWFFeXTvA5iEiPeI82DgQP+yrtH+1PcTwCffQpwX7tVRBa7nxBK6qwXEJG/iciv69nml0RkvrvukyJS4D4fFpH7RGQecGE9GS8BngUm4PSCQUTGA0cB/xWRG0WkWESeFZFpwLMiMlpE3nSXbS8iT7n7XSQi57vP/1lE5ojIUhH5ZUzOsIj80n3fi0WkoSGJ0cBS4M9uxuj6xSLytPvzWyUi3xKR37rbekvcq1VEZLCITBKRuSLytoj0dp+f6H5ymAPc4G7vZve1Y0Tk3ZhPZ0e77++9mLzRn1HQ/QT0uPseJ4hIk+PpX+CM6/8BGAIsbO5qTfW6j7p4UmSeOL+DJvnexhnCsWKfQZpT8Nu4QyQVwBPA3fUssxE4W1VPBi7CnURDRL6KU3SHqeqJwG9j1snFubTvY1W9PXZjInIQ8DfgIlUd4C57TcwiW1T1ZFX9wrCN6yKcO//+iVtYVXUssBY4U1UfdJc7HueI/5I6698BVKrqAFUdCERPUP1CVYcAA4FRIjIwZp3N7nv/M3BzPZlws/wTeBUoki9edng0MAb4BvB34AP3fVfFLPswcIGqDgaeBO6JWT9fVYeoat3L5J4DHnF/9sNxxtn3Aue5ec8Efiefd6I81l3+BGA7cH4D76VxxZVLgaHAA0CkqcXH9eq+vLFe9wCiGjl7vh7ZojwmHnuAW4CvFVaU24TwGaY5Bb9KVQepaj/gK8AzMQUiKg94XEQW4/TUiF4ydxbwlLoz16vq1ph1/gIsUdV7OFBfYKWqRmfKeRo4I+b1F+oL6p4X2Kyq/8Np7XuSiHRp4H29rqpV9Tx/FvBI9IGqRj/RfNv9VDEfOCHmPQK84v47FwjWkysf59r111R1BzALpz9N1H9VtRpYjDMc9Zb7/GJ3e32B/sA7IrIAuB04NGb9A34eItIBOERVX3Xfx173v4MAvxGRRTg3UB0C9HRXW6mq0ZNy9b6XZiuu3E9x5S3Al3CGserl9ro/vanNfWmBzs6NcHiL85jmeAfoX1hR/kBhRXmTf6iN/zRnDP8zqjpDRLrBAVPJ3QhsAE7E+SPSnMv0pgNnisjvVDXey/p2N/D8JUA/EQm7jw/GOUp9PI5tHEBEjsQ5cj9FVbeJyN/44hj1PvffWur/mZ4DdAIWu38r2+Icvb8Zu76qRkSkWlWjdy5G3O0JsFRVG7r7tNnvBbgU57/fYFWtdn9W0feyL2a5WiC+IZ36FFdOpLjjQJxPKN+t+/INPbvtb6zXfdQlEyNxnRMwcdkM3FRYUf6s10FMcsU1hu+OT+cAW+q81BFYp6oRnBtyoldRvAN8T9yP63WOtv8K/Ad4UUTqFskPgaCIRK/auAyY1ES2AM6kHQNUNaiqQZzhpLpDNk15BxgXs93OOH84dgOVItIT+Gqc27wE+GFMriOBs6WJYYwYHwLdReQ0N1OeiDQ6Ybeq7gTWiMg33XUK3P11BDa6xf5MoMFulAlTXLmd4srLcE5Wfza2/4LT677RBmkAfVdreYe9NLmcaZFngUIr9tkhnjH8BThDB1fUvTIGeBS4QkQWAv1wjzhV9S2cqfLmuOt/YXxbVX+PM0TyrMRcquge8X8PeMkdJooATV19MhL4VFXXxjw3GTg+eoKzmX4NdBaRJe77OVNVF7o5K4B/AM0+keUW2a8ApdHn3CuHpgJfb842VHU/cAFwn5tpAc6YfFMuA653h2+mA71wxvWHuD/Xy933lBrFlZNxLt+8dj+sK2mi133UVW/Vbm16KROnpcCXCyvKLy+sKN/sdRiTGvL56IExqXPLI0d1eqt9uzuA64D8hpbrukPXP/pIbVdxzhOZ1gsDdwF/t3H67GMF33hqwNMDjgSKcc4tHHBD1S0v10485WMdneJYmWgDzqfXxworyvd7HcZ4wwq+SQsDnh7QF+eS2ItxC39+tVY980BtVQAautLKNK0S53LoPxRWlMdzct9kICv4Jq0MeHrAMcDPgMsumVg7+7wZOtLrTD61Gue+kPHWEsFEWcE3aWnA0wN6PPxozWU9K/kp2EQncZiMc+PjazbloKnLCr5Ja+X9CvOAbwE/xpli0RyoCufqq4cLK8oXeR3GpC8r+MY3yvsVHoszxn8xZP0EKIpzqe1LwLOFFeV26appkhV8cwD3Zq1XgUJVbfA6fRH5D/AdVd2esnCu8n6FA/m8+GdLj51okX8R+FdhRfmnHucxPmMF3xxARF4A+gDvq+pdXudpSnm/wlNxbkw7C6e5XZOtGnykFpiBcyRvRd60ihV88wUi0h6nlcOZwBuq2te9U/kFnBYTucA1qjrF7cMzRFU3i8hrwGE4fXn+oKqPudvbBfwB+D+cseZzVXVDsvKX9yvsitOKeoz71egMWmkoAizB6dL6PjCpsKJ8h7eRTKawgm++QEQuBcao6g9EZDrOydLRwEGqeo+I5ABtVXVnnYLfRVW3uj30ZwOjVHWLiCjwDVV9Q0R+C+xQ1QPmP0iW8n6FvXH+eJ2G03G0P9AtVftvhnU4bQ5m4rTsmFFYUV7pbSSTqeLqlmmywiU4R+TgzCtwCU4/pCfdvvyvxbRQjnW9iJznfn8YTm/9LcB+Pu8KOhc4O1nB61NYUb4Op//RP6LPlfcr7MHnxb8/TrvrIE4X0WS0cKgBVuD0LSqP/deKu0klK/jmM2430zHAAPfIPAfnROEtOPMRFAF/E5Hfq+ozMeuNxhk/P01V94jIRD5vuRzb7rmh9tEpVVhRvpHPh0w+U96vUIDOQA+cOQJ6ut/3wGkVLTgNB6P/Rr8XYAdOm+Et7lfs99usb41JB57/z2fSygXAs6p6dfQJEZmEU+ynqurj4kw1eTLwTMx6HYFtbrHvB5yaytCJUlhRrsBW9yt1XUSNSREr+CbWJcB9dZ77F850k7tFpBrYhdNWOdZbwFgRKcc54TszyTmNMS1gJ22NSXMisktV28c8vhLnZPl1IjIW2BM7xJbEHL8CJqvqu0ncRxj3QoBmLDsI6KOq/3EffwM4XlVLkpXP7+wI3xgfU9WmJgZK5L7uTOT2RCRXVWtasYlBwBCcmfNQ1ddxLjAwDYhrikNjTHoRkWIRudn9/noRWSYii0Tk+ZjXnxWRGSLysYj8yH2+vYi8JyLzRGSxiJzrPh8UkXIReVxElorIBPdSW0TkbyJygfv9KSIyXUQWikiZiHSok0tE5H535rjFInKR+/xoEZkiIq8Dy5r5Hoe6+ee7++wrIvnAr4CL3Bn5LhKRK0XkTzFZ/+guvyImd725soUd4RuT/tq4U4RGdaH+I9kQcKSq7hORTjHPD8Q5kd4OmC8ipcBG4DxV3SEi3YCZbhEG55LaS1T1RyLyInA+8Pfoxtxi+wJwkarOFpGDcW6qi/UtnCPwE3Hue5gtIpPd104G+qvqyma+/wpgpKrWiMhZwG9U9XwRuRN3aMvNdWWd9XoDI3BuvnsdeLmhXKq6rplZfM0KvjHpr0pVB0UfRMfw61luEfCce9fzazHP/1tVq4AqEfkAGIozx/JvROQMnLt7D8G5DBVgZcy9FnNx7lGI1RdYp6qzAVS1vjuBRwD/dOe/3uBe7XUKzuWrZXEUe3CuAntaRI7FuUy4ufdKvKaqEWCZiETfW0O5smIoyIZ0jMkcRcAjOEfQs0UkekBX98oMxZlSsjsw2P1jsoHP753YF7NsMu6diHfmrbuBD1S1P/B1Ps/ZlNj3kUn9lVrMCr4xGUBEAsBhqvoBcCvOUXH0yp5zReQgEYn2GZrtvr5RVatF5EzgiDh29yHQW0ROcffdIeaPS9QUnPH1HBHpjnMvR1kL315HINo07sqY53cCHQ5YunGJzOU7NqRjTGbIAf4uIh1xjmb/qKrbRQScoZ4PcMas71bVtSLyHPCGiCwG5hDHjWaqut892fmwe0K3CudO610xi72K079oIc4nip+p6nr3xrymLBKR6J3JL+LMyfu0iNyOMxQV9QEQcs9v3NvM+PXmaua6vmfX4RuTwUSkGNilqg94ncV4z4Z0jDEmS9gRvjHGZAk7wjfGmCxhBd8YY7KEFXxjjMkSVvCNMSZLWME3xpgsYQXfGGOyxP8DD6ZkwIHxbE4AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}