homeless_pop_munging.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Number of CoCs</th>\n",
       "      <th>Overall Homeless, 2017</th>\n",
       "      <th>Sheltered ES Homeless, 2017</th>\n",
       "      <th>Sheltered TH Homeless, 2017</th>\n",
       "      <th>Sheltered SH Homeless, 2017</th>\n",
       "      <th>Sheltered Total Homeless, 2017</th>\n",
       "      <th>Unsheltered Homeless, 2017</th>\n",
       "      <th>Homeless Individuals, 2017</th>\n",
       "      <th>Sheltered ES Homeless Individuals, 2017</th>\n",
       "      <th>...</th>\n",
       "      <th>Homeless Parenting Youth Age 18-24, 2017</th>\n",
       "      <th>Sheltered ES Homeless Parenting Youth Age 18-24, 2017</th>\n",
       "      <th>Sheltered TH Homeless Parenting Youth Age 18-24, 2017</th>\n",
       "      <th>Sheltered Total Homeless Parenting Youth Age 18-24, 2017</th>\n",
       "      <th>Unsheltered Homeless Parenting Youth Age 18-24, 2017</th>\n",
       "      <th>Homeless Children of Parenting Youth, 2017</th>\n",
       "      <th>Sheltered ES Homeless Children of Parenting Youth, 2017</th>\n",
       "      <th>Sheltered TH Homeless Children of Parenting Youth, 2017</th>\n",
       "      <th>Sheltered Total Homeless Children of Parenting Youth, 2017</th>\n",
       "      <th>Unsheltered Homeless Children of Parenting Youth, 2017</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>AK</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1,845</td>\n",
       "      <td>1,017</td>\n",
       "      <td>534</td>\n",
       "      <td>0</td>\n",
       "      <td>1,551</td>\n",
       "      <td>294</td>\n",
       "      <td>1,354</td>\n",
       "      <td>792</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39</td>\n",
       "      <td>20</td>\n",
       "      <td>19</td>\n",
       "      <td>39</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>AL</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3,793</td>\n",
       "      <td>1,644</td>\n",
       "      <td>978</td>\n",
       "      <td>34</td>\n",
       "      <td>2,656</td>\n",
       "      <td>1,137</td>\n",
       "      <td>2,985</td>\n",
       "      <td>1,163</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>3.0</td>\n",
       "      <td>39</td>\n",
       "      <td>11</td>\n",
       "      <td>24</td>\n",
       "      <td>35</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>AR</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2,467</td>\n",
       "      <td>915</td>\n",
       "      <td>358</td>\n",
       "      <td>0</td>\n",
       "      <td>1,273</td>\n",
       "      <td>1,194</td>\n",
       "      <td>2,068</td>\n",
       "      <td>677</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>AZ</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8,947</td>\n",
       "      <td>3,841</td>\n",
       "      <td>1,904</td>\n",
       "      <td>36</td>\n",
       "      <td>5,781</td>\n",
       "      <td>3,166</td>\n",
       "      <td>6,488</td>\n",
       "      <td>2,541</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>37</td>\n",
       "      <td>44</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>112</td>\n",
       "      <td>55</td>\n",
       "      <td>57</td>\n",
       "      <td>112</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>CA</td>\n",
       "      <td>43.0</td>\n",
       "      <td>131,532</td>\n",
       "      <td>26,854</td>\n",
       "      <td>15,656</td>\n",
       "      <td>126</td>\n",
       "      <td>42,636</td>\n",
       "      <td>88,896</td>\n",
       "      <td>110,260</td>\n",
       "      <td>16,157</td>\n",
       "      <td>...</td>\n",
       "      <td>770</td>\n",
       "      <td>248</td>\n",
       "      <td>397</td>\n",
       "      <td>645</td>\n",
       "      <td>125.0</td>\n",
       "      <td>912</td>\n",
       "      <td>289</td>\n",
       "      <td>493</td>\n",
       "      <td>782</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 82 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  State  Number of CoCs Overall Homeless, 2017 Sheltered ES Homeless, 2017  \\\n",
       "0    AK             2.0                  1,845                       1,017   \n",
       "1    AL             8.0                  3,793                       1,644   \n",
       "2    AR             6.0                  2,467                         915   \n",
       "3    AZ             3.0                  8,947                       3,841   \n",
       "4    CA            43.0                131,532                      26,854   \n",
       "\n",
       "  Sheltered TH Homeless, 2017 Sheltered SH Homeless, 2017  \\\n",
       "0                         534                           0   \n",
       "1                         978                          34   \n",
       "2                         358                           0   \n",
       "3                       1,904                          36   \n",
       "4                      15,656                         126   \n",
       "\n",
       "  Sheltered Total Homeless, 2017 Unsheltered Homeless, 2017  \\\n",
       "0                          1,551                        294   \n",
       "1                          2,656                      1,137   \n",
       "2                          1,273                      1,194   \n",
       "3                          5,781                      3,166   \n",
       "4                         42,636                     88,896   \n",
       "\n",
       "  Homeless Individuals, 2017 Sheltered ES Homeless Individuals, 2017  ...  \\\n",
       "0                      1,354                                     792  ...   \n",
       "1                      2,985                                   1,163  ...   \n",
       "2                      2,068                                     677  ...   \n",
       "3                      6,488                                   2,541  ...   \n",
       "4                    110,260                                  16,157  ...   \n",
       "\n",
       "  Homeless Parenting Youth Age 18-24, 2017  \\\n",
       "0                                       22   \n",
       "1                                       23   \n",
       "2                                       10   \n",
       "3                                       81   \n",
       "4                                      770   \n",
       "\n",
       "  Sheltered ES Homeless Parenting Youth Age 18-24, 2017  \\\n",
       "0                                                 10      \n",
       "1                                                  6      \n",
       "2                                                  8      \n",
       "3                                                 37      \n",
       "4                                                248      \n",
       "\n",
       "  Sheltered TH Homeless Parenting Youth Age 18-24, 2017  \\\n",
       "0                                                 12      \n",
       "1                                                 14      \n",
       "2                                                  2      \n",
       "3                                                 44      \n",
       "4                                                397      \n",
       "\n",
       "  Sheltered Total Homeless Parenting Youth Age 18-24, 2017  \\\n",
       "0                                                 22         \n",
       "1                                                 20         \n",
       "2                                                 10         \n",
       "3                                                 81         \n",
       "4                                                645         \n",
       "\n",
       "  Unsheltered Homeless Parenting Youth Age 18-24, 2017  \\\n",
       "0                                                0.0     \n",
       "1                                                3.0     \n",
       "2                                                0.0     \n",
       "3                                                0.0     \n",
       "4                                              125.0     \n",
       "\n",
       "  Homeless Children of Parenting Youth, 2017  \\\n",
       "0                                         39   \n",
       "1                                         39   \n",
       "2                                         13   \n",
       "3                                        112   \n",
       "4                                        912   \n",
       "\n",
       "  Sheltered ES Homeless Children of Parenting Youth, 2017  \\\n",
       "0                                                 20        \n",
       "1                                                 11        \n",
       "2                                                 11        \n",
       "3                                                 55        \n",
       "4                                                289        \n",
       "\n",
       "  Sheltered TH Homeless Children of Parenting Youth, 2017  \\\n",
       "0                                                 19        \n",
       "1                                                 24        \n",
       "2                                                  2        \n",
       "3                                                 57        \n",
       "4                                                493        \n",
       "\n",
       "  Sheltered Total Homeless Children of Parenting Youth, 2017  \\\n",
       "0                                                 39           \n",
       "1                                                 35           \n",
       "2                                                 13           \n",
       "3                                                112           \n",
       "4                                                782           \n",
       "\n",
       "  Unsheltered Homeless Children of Parenting Youth, 2017  \n",
       "0                                                0.0      \n",
       "1                                                4.0      \n",
       "2                                                0.0      \n",
       "3                                                0.0      \n",
       "4                                              130.0      \n",
       "\n",
       "[5 rows x 82 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dependencies and Setup\n",
    "import pandas as pd\n",
    "\n",
    "# load file\n",
    "file_to_load = \"Resources/2017-PIT-Counts-by-State.csv\"\n",
    "\n",
    "# Read  File and store into Pandas data frame\n",
    "homeless_data = pd.read_csv(file_to_load)\n",
    "\n",
    "homeless_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STATE ID\n",
       "AK         1845\n",
       "AL         3793\n",
       "AR         2467\n",
       "AZ         8947\n",
       "CA       131532\n",
       "CO        10940\n",
       "CT         3388\n",
       "DC         7473\n",
       "DE          994\n",
       "FL        32190\n",
       "GA        10174\n",
       "GU          852\n",
       "HI         7220\n",
       "IA         2756\n",
       "ID         2037\n",
       "IL        10798\n",
       "IN         5438\n",
       "KS         2287\n",
       "KY         4025\n",
       "LA         3305\n",
       "MA        17565\n",
       "MD         7247\n",
       "ME         2280\n",
       "MI         9051\n",
       "MN         7668\n",
       "MO         6037\n",
       "MP          672\n",
       "MS         1472\n",
       "MT         1529\n",
       "NC         8962\n",
       "ND         1089\n",
       "NE         2501\n",
       "NH         1456\n",
       "NJ         8536\n",
       "NM         2482\n",
       "NV         7833\n",
       "NY        89503\n",
       "OH        10095\n",
       "OK         4199\n",
       "OR        13953\n",
       "PA        14138\n",
       "PR         3525\n",
       "RI         1180\n",
       "SC         3916\n",
       "SD          943\n",
       "TN         8309\n",
       "TX        23548\n",
       "UT         2852\n",
       "VA         6067\n",
       "VI          381\n",
       "VT         1225\n",
       "WA        21112\n",
       "WI         5027\n",
       "WV         1309\n",
       "WY          873\n",
       "Total    550996\n",
       "Name: 2017 Homeless Population, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get necessary columns\n",
    "homeless_2017 = homeless_data[[\"State\", \"Overall Homeless, 2017\"]]\n",
    "homeless_2017 = homeless_2017.rename(columns={\"State\": \"STATE ID\", \"Overall Homeless, 2017\": \"2017 Homeless Population\"})\n",
    "homeless_2017.dropna(inplace=True)\n",
    "homeless_2017 = homeless_2017.set_index(\"STATE ID\")\n",
    "\n",
    "homeless_2017_pd = pd.to_numeric(homeless_2017[\"2017 Homeless Population\"].str.replace(',',''), errors='coerce')\n",
    "homeless_2017_pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>Homeless Population (2017)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>139271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>58663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>122074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>201342</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  Region  Homeless Population (2017)\n",
       "0      1                      139271\n",
       "1      2                       58663\n",
       "2      3                      122074\n",
       "3      4                      201342"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Region1_sum = homeless_2017_pd[\"CT\"] + homeless_2017_pd[\"ME\"] + homeless_2017_pd[\"MA\"] + homeless_2017_pd[\"NH\"] + homeless_2017_pd[\"NJ\"] + homeless_2017_pd[\"NY\"] + homeless_2017_pd[\"PA\"] + homeless_2017_pd[\"RI\"] + homeless_2017_pd[\"VT\"]\n",
    "Region2_sum = homeless_2017_pd[\"IL\"] + homeless_2017_pd[\"IN\"] + homeless_2017_pd[\"IA\"] + homeless_2017_pd[\"KS\"] + homeless_2017_pd[\"MI\"] + homeless_2017_pd[\"MN\"] + homeless_2017_pd[\"MO\"] + homeless_2017_pd[\"NE\"] + homeless_2017_pd[\"ND\"] + homeless_2017_pd[\"OH\"] + homeless_2017_pd[\"SD\"]\n",
    "Region3_sum = homeless_2017_pd[\"AL\"] + homeless_2017_pd[\"AR\"] + homeless_2017_pd[\"DE\"] + homeless_2017_pd[\"DC\"] + homeless_2017_pd[\"FL\"] + homeless_2017_pd[\"GA\"] + homeless_2017_pd[\"KY\"] + homeless_2017_pd[\"LA\"] + homeless_2017_pd[\"MD\"] + homeless_2017_pd[\"MS\"] + homeless_2017_pd[\"NC\"] + homeless_2017_pd[\"OK\"] + homeless_2017_pd[\"SC\"] + homeless_2017_pd[\"TN\"] + homeless_2017_pd[\"TX\"]\n",
    "Region4_sum = homeless_2017_pd[\"AK\"] + homeless_2017_pd[\"AZ\"] + homeless_2017_pd[\"CA\"] + homeless_2017_pd[\"HI\"] + homeless_2017_pd[\"ID\"] + homeless_2017_pd[\"MT\"] + homeless_2017_pd[\"NV\"] + homeless_2017_pd[\"NM\"] + homeless_2017_pd[\"OR\"] + homeless_2017_pd[\"UT\"] + homeless_2017_pd[\"WA\"]\n",
    "\n",
    "homelessness_by_region = pd.DataFrame({\n",
    "    \"Region\" : [\"1\", \"2\", \"3\", \"4\"],\n",
    "    \"Homeless Population (2017)\": [Region1_sum, Region2_sum, Region3_sum, Region4_sum]\n",
    "})\n",
    "\n",
    "homelessness_by_region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Print to csv\n",
    "homeless_2017.to_csv(r'Resources/homelessness_by_state.csv')\n",
    "homelessness_by_region.to_csv(r'Resources/homelessness_by_region.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dividing by Regions\n",
    "region_1_states = ([\"CT\", \"ME\", \"MA\", \"NH\",\n",
    "                   \"NJ\", \"NY\", \"PA\", \"RI\", \"VT\"])\n",
    "\n",
    "region1 = []\n",
    "\n",
    "for a in region_1_states:\n",
    "    region1.append(homeless_2017.loc[a, \"2017 Homeless Population\"])\n",
    "\n",
    "Region1_homelessness = pd.DataFrame({\n",
    "    \"State ID\" : region_1_states,\n",
    "    \"Homeless Population (2017)\": region1\n",
    "})\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "region_2_states = ([\"IL\", \"IN\", \"IA\", \"KS\",\n",
    "                   \"MI\", \"MN\", \"MO\", \"NE\", \"ND\", \"OH\", \"SD\"])\n",
    "\n",
    "region2 = []\n",
    "\n",
    "for a in region_2_states:\n",
    "    region2.append(homeless_2017.loc[a, \"2017 Homeless Population\"])\n",
    "\n",
    "Region2_homelessness = pd.DataFrame({\n",
    "    \"State ID\" : region_2_states,\n",
    "    \"Homeless Population (2017)\": region2\n",
    "})\n",
    "\n",
    "  \n",
    "\n",
    "    \n",
    "region_3_states = ([\"AL\", \"AR\", \"DE\", \"DC\",\n",
    "                   \"FL\", \"GA\", \"KY\", \"LA\", \"MD\", \"MS\", \n",
    "                    \"NC\", \"OK\", \"SC\", \"TN\", \"TX\"])\n",
    "\n",
    "region3 = []\n",
    "\n",
    "for a in region_3_states:\n",
    "    region3.append(homeless_2017.loc[a, \"2017 Homeless Population\"])\n",
    "\n",
    "Region3_homelessness = pd.DataFrame({\n",
    "    \"State ID\" : region_3_states,\n",
    "    \"Homeless Population (2017)\": region3\n",
    "})\n",
    "   \n",
    "\n",
    "\n",
    "    \n",
    "region_4_states = ([\"AK\", \"AZ\", \"CA\", \"HI\",\n",
    "                   \"ID\", \"MT\", \"NV\", \"NM\", \"OR\", \"UT\", \n",
    "                    \"WA\"])\n",
    "\n",
    "region4 = []\n",
    "\n",
    "for a in region_4_states:\n",
    "    region4.append(homeless_2017.loc[a, \"2017 Homeless Population\"])\n",
    "\n",
    "Region4_homelessness = pd.DataFrame({\n",
    "    \"State ID\" : region_4_states,\n",
    "    \"Homeless Population (2017)\": region4\n",
    "})\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State ID</th>\n",
       "      <th>Homeless Population (2017)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>CT</td>\n",
       "      <td>3,388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>ME</td>\n",
       "      <td>2,280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>MA</td>\n",
       "      <td>17,565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>NH</td>\n",
       "      <td>1,456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>NJ</td>\n",
       "      <td>8,536</td>\n",
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       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>NY</td>\n",
       "      <td>89,503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>PA</td>\n",
       "      <td>14,138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>RI</td>\n",
       "      <td>1,180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>VT</td>\n",
       "      <td>1,225</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State ID Homeless Population (2017)\n",
       "0       CT                      3,388\n",
       "1       ME                      2,280\n",
       "2       MA                     17,565\n",
       "3       NH                      1,456\n",
       "4       NJ                      8,536\n",
       "5       NY                     89,503\n",
       "6       PA                     14,138\n",
       "7       RI                      1,180\n",
       "8       VT                      1,225"
      ]
     },
     "execution_count": 8,
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   "source": [
    "Region1_homelessness"
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       "   State ID Homeless Population (2017)\n",
       "0        IL                     10,798\n",
       "1        IN                      5,438\n",
       "2        IA                      2,756\n",
       "3        KS                      2,287\n",
       "4        MI                      9,051\n",
       "5        MN                      7,668\n",
       "6        MO                      6,037\n",
       "7        NE                      2,501\n",
       "8        ND                      1,089\n",
       "9        OH                     10,095\n",
       "10       SD                        943"
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   "source": [
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       "      <td>10</td>\n",
       "      <td>NC</td>\n",
       "      <td>8,962</td>\n",
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       "      <td>SC</td>\n",
       "      <td>3,916</td>\n",
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       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>TN</td>\n",
       "      <td>8,309</td>\n",
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       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>TX</td>\n",
       "      <td>23,548</td>\n",
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       "   State ID Homeless Population (2017)\n",
       "0        AL                      3,793\n",
       "1        AR                      2,467\n",
       "2        DE                        994\n",
       "3        DC                      7,473\n",
       "4        FL                     32,190\n",
       "5        GA                     10,174\n",
       "6        KY                      4,025\n",
       "7        LA                      3,305\n",
       "8        MD                      7,247\n",
       "9        MS                      1,472\n",
       "10       NC                      8,962\n",
       "11       OK                      4,199\n",
       "12       SC                      3,916\n",
       "13       TN                      8,309\n",
       "14       TX                     23,548"
      ]
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     "execution_count": 10,
     "metadata": {},
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   "source": [
    "Region3_homelessness"
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   "cell_type": "code",
   "execution_count": 11,
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   "outputs": [
    {
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       "      <td>UT</td>\n",
       "      <td>2,852</td>\n",
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       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>WA</td>\n",
       "      <td>21,112</td>\n",
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       "   State ID Homeless Population (2017)\n",
       "0        AK                      1,845\n",
       "1        AZ                      8,947\n",
       "2        CA                    131,532\n",
       "3        HI                      7,220\n",
       "4        ID                      2,037\n",
       "5        MT                      1,529\n",
       "6        NV                      7,833\n",
       "7        NM                      2,482\n",
       "8        OR                     13,953\n",
       "9        UT                      2,852\n",
       "10       WA                     21,112"
      ]
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     "execution_count": 11,
     "metadata": {},
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   ],
   "source": [
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