DUG_FoodAccessResearch.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bc5fc9a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import fiona\n",
    "import folium\n",
    "import geopandas as gpd\n",
    "import geoplot\n",
    "pd.options.display.float_format = '{:,.4f}'.format\n",
    "os.chdir(r'G:\\My Drive\\~DUG analysis')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0cc8f92",
   "metadata": {},
   "source": [
    "\n",
    "## Food Access data from the census bureau:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b2198bf5",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CensusTract</th>\n",
       "      <th>State</th>\n",
       "      <th>County</th>\n",
       "      <th>Urban</th>\n",
       "      <th>Pop2010</th>\n",
       "      <th>OHU2010</th>\n",
       "      <th>GroupQuartersFlag</th>\n",
       "      <th>NUMGQTRS</th>\n",
       "      <th>PCTGQTRS</th>\n",
       "      <th>LILATracts_1And10</th>\n",
       "      <th>...</th>\n",
       "      <th>TractSeniors</th>\n",
       "      <th>TractWhite</th>\n",
       "      <th>TractBlack</th>\n",
       "      <th>TractAsian</th>\n",
       "      <th>TractNHOPI</th>\n",
       "      <th>TractAIAN</th>\n",
       "      <th>TractOMultir</th>\n",
       "      <th>TractHispanic</th>\n",
       "      <th>TractHUNV</th>\n",
       "      <th>TractSNAP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001020100</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>1912</td>\n",
       "      <td>693</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>221.0000</td>\n",
       "      <td>1,622.0000</td>\n",
       "      <td>217.0000</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>45.0000</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>102.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1001020200</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>2170</td>\n",
       "      <td>743</td>\n",
       "      <td>0</td>\n",
       "      <td>181.0000</td>\n",
       "      <td>8.3410</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>214.0000</td>\n",
       "      <td>888.0000</td>\n",
       "      <td>1,217.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>55.0000</td>\n",
       "      <td>75.0000</td>\n",
       "      <td>89.0000</td>\n",
       "      <td>156.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1001020300</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>3373</td>\n",
       "      <td>1256</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>439.0000</td>\n",
       "      <td>2,576.0000</td>\n",
       "      <td>647.0000</td>\n",
       "      <td>17.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>117.0000</td>\n",
       "      <td>87.0000</td>\n",
       "      <td>99.0000</td>\n",
       "      <td>172.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1001020400</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>4386</td>\n",
       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>904.0000</td>\n",
       "      <td>4,086.0000</td>\n",
       "      <td>193.0000</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>74.0000</td>\n",
       "      <td>85.0000</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>98.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1001020500</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>10766</td>\n",
       "      <td>4082</td>\n",
       "      <td>0</td>\n",
       "      <td>181.0000</td>\n",
       "      <td>1.6812</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1,126.0000</td>\n",
       "      <td>8,666.0000</td>\n",
       "      <td>1,437.0000</td>\n",
       "      <td>296.0000</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>48.0000</td>\n",
       "      <td>310.0000</td>\n",
       "      <td>355.0000</td>\n",
       "      <td>230.0000</td>\n",
       "      <td>339.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72526</th>\n",
       "      <td>56043000200</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Washakie County</td>\n",
       "      <td>0</td>\n",
       "      <td>3326</td>\n",
       "      <td>1317</td>\n",
       "      <td>0</td>\n",
       "      <td>57.0000</td>\n",
       "      <td>1.7138</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>593.0000</td>\n",
       "      <td>3,106.0000</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>27.0000</td>\n",
       "      <td>172.0000</td>\n",
       "      <td>309.0000</td>\n",
       "      <td>61.0000</td>\n",
       "      <td>64.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72527</th>\n",
       "      <td>56043000301</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Washakie County</td>\n",
       "      <td>1</td>\n",
       "      <td>2665</td>\n",
       "      <td>1154</td>\n",
       "      <td>0</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>0.3752</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>399.0000</td>\n",
       "      <td>2,377.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>23.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>40.0000</td>\n",
       "      <td>220.0000</td>\n",
       "      <td>446.0000</td>\n",
       "      <td>88.0000</td>\n",
       "      <td>41.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72528</th>\n",
       "      <td>56043000302</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Washakie County</td>\n",
       "      <td>1</td>\n",
       "      <td>2542</td>\n",
       "      <td>1021</td>\n",
       "      <td>0</td>\n",
       "      <td>73.0000</td>\n",
       "      <td>2.8718</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>516.0000</td>\n",
       "      <td>2,312.0000</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>182.0000</td>\n",
       "      <td>407.0000</td>\n",
       "      <td>23.0000</td>\n",
       "      <td>64.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72529</th>\n",
       "      <td>56045951100</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Weston County</td>\n",
       "      <td>0</td>\n",
       "      <td>3314</td>\n",
       "      <td>1322</td>\n",
       "      <td>0</td>\n",
       "      <td>252.0000</td>\n",
       "      <td>7.6041</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>499.0000</td>\n",
       "      <td>3,179.0000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>47.0000</td>\n",
       "      <td>62.0000</td>\n",
       "      <td>91.0000</td>\n",
       "      <td>47.0000</td>\n",
       "      <td>34.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72530</th>\n",
       "      <td>56045951300</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Weston County</td>\n",
       "      <td>1</td>\n",
       "      <td>3894</td>\n",
       "      <td>1699</td>\n",
       "      <td>0</td>\n",
       "      <td>61.0000</td>\n",
       "      <td>1.5665</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>650.0000</td>\n",
       "      <td>3,706.0000</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>126.0000</td>\n",
       "      <td>125.0000</td>\n",
       "      <td>34.0000</td>\n",
       "      <td>110.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72531 rows × 147 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       CensusTract    State           County  Urban  Pop2010  OHU2010  \\\n",
       "0       1001020100  Alabama   Autauga County      1     1912      693   \n",
       "1       1001020200  Alabama   Autauga County      1     2170      743   \n",
       "2       1001020300  Alabama   Autauga County      1     3373     1256   \n",
       "3       1001020400  Alabama   Autauga County      1     4386     1722   \n",
       "4       1001020500  Alabama   Autauga County      1    10766     4082   \n",
       "...            ...      ...              ...    ...      ...      ...   \n",
       "72526  56043000200  Wyoming  Washakie County      0     3326     1317   \n",
       "72527  56043000301  Wyoming  Washakie County      1     2665     1154   \n",
       "72528  56043000302  Wyoming  Washakie County      1     2542     1021   \n",
       "72529  56045951100  Wyoming    Weston County      0     3314     1322   \n",
       "72530  56045951300  Wyoming    Weston County      1     3894     1699   \n",
       "\n",
       "       GroupQuartersFlag  NUMGQTRS  PCTGQTRS  LILATracts_1And10  ...  \\\n",
       "0                      0    0.0000    0.0000                  0  ...   \n",
       "1                      0  181.0000    8.3410                  1  ...   \n",
       "2                      0    0.0000    0.0000                  0  ...   \n",
       "3                      0    0.0000    0.0000                  0  ...   \n",
       "4                      0  181.0000    1.6812                  0  ...   \n",
       "...                  ...       ...       ...                ...  ...   \n",
       "72526                  0   57.0000    1.7138                  0  ...   \n",
       "72527                  0   10.0000    0.3752                  0  ...   \n",
       "72528                  0   73.0000    2.8718                  0  ...   \n",
       "72529                  0  252.0000    7.6041                  0  ...   \n",
       "72530                  0   61.0000    1.5665                  0  ...   \n",
       "\n",
       "       TractSeniors  TractWhite  TractBlack  TractAsian  TractNHOPI  \\\n",
       "0          221.0000  1,622.0000    217.0000     14.0000      0.0000   \n",
       "1          214.0000    888.0000  1,217.0000      5.0000      0.0000   \n",
       "2          439.0000  2,576.0000    647.0000     17.0000      5.0000   \n",
       "3          904.0000  4,086.0000    193.0000     18.0000      4.0000   \n",
       "4        1,126.0000  8,666.0000  1,437.0000    296.0000      9.0000   \n",
       "...             ...         ...         ...         ...         ...   \n",
       "72526      593.0000  3,106.0000      6.0000     15.0000      0.0000   \n",
       "72527      399.0000  2,377.0000      5.0000     23.0000      0.0000   \n",
       "72528      516.0000  2,312.0000     11.0000     10.0000      1.0000   \n",
       "72529      499.0000  3,179.0000     15.0000     10.0000      1.0000   \n",
       "72530      650.0000  3,706.0000      6.0000     10.0000      2.0000   \n",
       "\n",
       "       TractAIAN  TractOMultir  TractHispanic  TractHUNV  TractSNAP  \n",
       "0        14.0000       45.0000        44.0000     6.0000   102.0000  \n",
       "1         5.0000       55.0000        75.0000    89.0000   156.0000  \n",
       "2        11.0000      117.0000        87.0000    99.0000   172.0000  \n",
       "3        11.0000       74.0000        85.0000    21.0000    98.0000  \n",
       "4        48.0000      310.0000       355.0000   230.0000   339.0000  \n",
       "...          ...           ...            ...        ...        ...  \n",
       "72526    27.0000      172.0000       309.0000    61.0000    64.0000  \n",
       "72527    40.0000      220.0000       446.0000    88.0000    41.0000  \n",
       "72528    26.0000      182.0000       407.0000    23.0000    64.0000  \n",
       "72529    47.0000       62.0000        91.0000    47.0000    34.0000  \n",
       "72530    44.0000      126.0000       125.0000    34.0000   110.0000  \n",
       "\n",
       "[72531 rows x 147 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fara=pd.read_excel('FoodAccessResearchAtlasData2019.xlsx',sheet_name='Food Access Research Atlas',header=0)\n",
    "fara"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "23fc11e0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Field</th>\n",
       "      <th>LongName</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CensusTract</td>\n",
       "      <td>Census tract</td>\n",
       "      <td>Census tract number</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>State</td>\n",
       "      <td>State</td>\n",
       "      <td>State name</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>County</td>\n",
       "      <td>County</td>\n",
       "      <td>County name</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Urban</td>\n",
       "      <td>Urban tract</td>\n",
       "      <td>Flag for urban tract</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POP2010</td>\n",
       "      <td>Population, tract total</td>\n",
       "      <td>Population count from 2010 census</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>TractAIAN</td>\n",
       "      <td>Tract American Indian and Alaska Native popula...</td>\n",
       "      <td>Total count of American Indian and Alaska Nati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>TractOMultir</td>\n",
       "      <td>Tract Other/Multiple race population, number</td>\n",
       "      <td>Total count of Other/Multiple race population ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>TractHispanic</td>\n",
       "      <td>Tract Hispanic or Latino population, number</td>\n",
       "      <td>Total count of Hispanic or Latino population i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>TractHUNV</td>\n",
       "      <td>Tract housing units without a vehicle, number</td>\n",
       "      <td>Total count of housing units without a vehicle...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>TractSNAP</td>\n",
       "      <td>Tract housing units receiving SNAP benefits, n...</td>\n",
       "      <td>Total count of housing units receiving SNAP be...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>147 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Field                                           LongName  \\\n",
       "0      CensusTract                                       Census tract   \n",
       "1            State                                              State   \n",
       "2           County                                             County   \n",
       "3            Urban                                        Urban tract   \n",
       "4          POP2010                            Population, tract total   \n",
       "..             ...                                                ...   \n",
       "142      TractAIAN  Tract American Indian and Alaska Native popula...   \n",
       "143   TractOMultir       Tract Other/Multiple race population, number   \n",
       "144  TractHispanic        Tract Hispanic or Latino population, number   \n",
       "145      TractHUNV      Tract housing units without a vehicle, number   \n",
       "146      TractSNAP  Tract housing units receiving SNAP benefits, n...   \n",
       "\n",
       "                                           Description  \n",
       "0                                  Census tract number  \n",
       "1                                           State name  \n",
       "2                                          County name  \n",
       "3                                 Flag for urban tract  \n",
       "4                    Population count from 2010 census  \n",
       "..                                                 ...  \n",
       "142  Total count of American Indian and Alaska Nati...  \n",
       "143  Total count of Other/Multiple race population ...  \n",
       "144  Total count of Hispanic or Latino population i...  \n",
       "145  Total count of housing units without a vehicle...  \n",
       "146  Total count of housing units receiving SNAP be...  \n",
       "\n",
       "[147 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fara_variables = pd.read_excel('FoodAccessResearchAtlasData2019.xlsx',sheet_name='Variable Lookup',header=0)\n",
    "fara_variables"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c627350",
   "metadata": {},
   "source": [
    "\n",
    "# DUG garden locations\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "04b14aab",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Description</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36th &amp; Lafayette Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0k-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.97074 39.76709 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Academia Sandoval School Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0k-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-105.01513 39.76585 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Agape Community Gardens on Williams (Not open ...</td>\n",
       "      <td>&lt;img src=\"https://doc-10-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.96636 39.75920 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Allison Gardens at Semper Farm</td>\n",
       "      <td>&lt;img src=\"https://doc-0c-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-105.07087 39.86480 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Anythink Commerce City Library Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0g-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.91309 39.82675 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>Market Station Community Garden</td>\n",
       "      <td>Address&lt;br&gt;1661 Market St., Denver CO 80202&lt;br...</td>\n",
       "      <td>POINT Z (-104.99773 39.75054 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>Nome Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0c-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.85148 39.73447 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>East Middle School Community Garden</td>\n",
       "      <td>Address&lt;br&gt;1275 Fraser Street&lt;br&gt;&lt;br&gt;Micro Net...</td>\n",
       "      <td>POINT Z (-104.81309 39.73409 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>Mountain View International Garden</td>\n",
       "      <td>Address&lt;br&gt;10700 E. Evans Ave. Aurora&lt;br&gt;&lt;br&gt;M...</td>\n",
       "      <td>POINT Z (-104.86325 39.67809 0.00000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>South Lakewood Elementary Community Garden</td>\n",
       "      <td>Address&lt;br&gt;8425 W 1st Ave, Lakewood&lt;br&gt;&lt;br&gt;Mic...</td>\n",
       "      <td>POINT Z (-105.09255 39.71899 0.00000)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>188 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Name  \\\n",
       "0                    36th & Lafayette Community Garden   \n",
       "1            Academia Sandoval School Community Garden   \n",
       "2    Agape Community Gardens on Williams (Not open ...   \n",
       "3                       Allison Gardens at Semper Farm   \n",
       "4      Anythink Commerce City Library Community Garden   \n",
       "..                                                 ...   \n",
       "183                    Market Station Community Garden   \n",
       "184                              Nome Community Garden   \n",
       "185                East Middle School Community Garden   \n",
       "186                 Mountain View International Garden   \n",
       "187         South Lakewood Elementary Community Garden   \n",
       "\n",
       "                                           Description  \\\n",
       "0    <img src=\"https://doc-0k-7o-mymaps.googleuserc...   \n",
       "1    <img src=\"https://doc-0k-7o-mymaps.googleuserc...   \n",
       "2    <img src=\"https://doc-10-7o-mymaps.googleuserc...   \n",
       "3    <img src=\"https://doc-0c-7o-mymaps.googleuserc...   \n",
       "4    <img src=\"https://doc-0g-7o-mymaps.googleuserc...   \n",
       "..                                                 ...   \n",
       "183  Address<br>1661 Market St., Denver CO 80202<br...   \n",
       "184  <img src=\"https://doc-0c-7o-mymaps.googleuserc...   \n",
       "185  Address<br>1275 Fraser Street<br><br>Micro Net...   \n",
       "186  Address<br>10700 E. Evans Ave. Aurora<br><br>M...   \n",
       "187  Address<br>8425 W 1st Ave, Lakewood<br><br>Mic...   \n",
       "\n",
       "                                  geometry  \n",
       "0    POINT Z (-104.97074 39.76709 0.00000)  \n",
       "1    POINT Z (-105.01513 39.76585 0.00000)  \n",
       "2    POINT Z (-104.96636 39.75920 0.00000)  \n",
       "3    POINT Z (-105.07087 39.86480 0.00000)  \n",
       "4    POINT Z (-104.91309 39.82675 0.00000)  \n",
       "..                                     ...  \n",
       "183  POINT Z (-104.99773 39.75054 0.00000)  \n",
       "184  POINT Z (-104.85148 39.73447 0.00000)  \n",
       "185  POINT Z (-104.81309 39.73409 0.00000)  \n",
       "186  POINT Z (-104.86325 39.67809 0.00000)  \n",
       "187  POINT Z (-105.09255 39.71899 0.00000)  \n",
       "\n",
       "[188 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read in the DUG garden location from GoogleMap .kml\n",
    "fiona.drvsupport.supported_drivers['KML'] = 'rw'\n",
    "DUG_locs = gpd.read_file('Denver Urban Gardens Community Gardens.kml', driver='KML')\n",
    "DUG_locs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5a6296f",
   "metadata": {},
   "source": [
    "\n",
    "# Census Tract data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3d7a63f5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATEFP10</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>TRACTCE10</th>\n",
       "      <th>GEOID10</th>\n",
       "      <th>NAME10</th>\n",
       "      <th>NAMELSAD10</th>\n",
       "      <th>MTFCC10</th>\n",
       "      <th>FUNCSTAT10</th>\n",
       "      <th>ALAND10</th>\n",
       "      <th>AWATER10</th>\n",
       "      <th>INTPTLAT10</th>\n",
       "      <th>INTPTLON10</th>\n",
       "      <th>geometry</th>\n",
       "      <th>CensusTract</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>08</td>\n",
       "      <td>051</td>\n",
       "      <td>963900</td>\n",
       "      <td>08051963900</td>\n",
       "      <td>9639</td>\n",
       "      <td>Census Tract 9639</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>4262312145</td>\n",
       "      <td>41657300</td>\n",
       "      <td>+38.6285818</td>\n",
       "      <td>-107.2733857</td>\n",
       "      <td>POLYGON ((-107.12846 38.81786, -107.12928 38.8...</td>\n",
       "      <td>8051963900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>08</td>\n",
       "      <td>051</td>\n",
       "      <td>963700</td>\n",
       "      <td>08051963700</td>\n",
       "      <td>9637</td>\n",
       "      <td>Census Tract 9637</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>14502053</td>\n",
       "      <td>0</td>\n",
       "      <td>+38.5443371</td>\n",
       "      <td>-106.9270259</td>\n",
       "      <td>POLYGON ((-106.95269 38.55070, -106.95230 38.5...</td>\n",
       "      <td>8051963700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>08</td>\n",
       "      <td>051</td>\n",
       "      <td>963600</td>\n",
       "      <td>08051963600</td>\n",
       "      <td>9636</td>\n",
       "      <td>Census Tract 9636</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>3267477045</td>\n",
       "      <td>10725478</td>\n",
       "      <td>+38.6738961</td>\n",
       "      <td>-106.7096262</td>\n",
       "      <td>POLYGON ((-106.51828 38.95152, -106.51670 38.9...</td>\n",
       "      <td>8051963600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>08</td>\n",
       "      <td>051</td>\n",
       "      <td>963800</td>\n",
       "      <td>08051963800</td>\n",
       "      <td>9638</td>\n",
       "      <td>Census Tract 9638</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>844937722</td>\n",
       "      <td>789243</td>\n",
       "      <td>+38.8767371</td>\n",
       "      <td>-106.9086087</td>\n",
       "      <td>POLYGON ((-106.77386 38.72978, -106.77400 38.7...</td>\n",
       "      <td>8051963800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>08</td>\n",
       "      <td>021</td>\n",
       "      <td>974900</td>\n",
       "      <td>08021974900</td>\n",
       "      <td>9749</td>\n",
       "      <td>Census Tract 9749</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>2716323548</td>\n",
       "      <td>8848645</td>\n",
       "      <td>+37.2224342</td>\n",
       "      <td>-106.2441010</td>\n",
       "      <td>POLYGON ((-105.91019 37.22490, -105.91184 37.2...</td>\n",
       "      <td>8021974900</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1244</th>\n",
       "      <td>08</td>\n",
       "      <td>005</td>\n",
       "      <td>081000</td>\n",
       "      <td>08005081000</td>\n",
       "      <td>810</td>\n",
       "      <td>Census Tract 810</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>2372419</td>\n",
       "      <td>0</td>\n",
       "      <td>+39.7177635</td>\n",
       "      <td>-104.8179019</td>\n",
       "      <td>POLYGON ((-104.82687 39.71730, -104.82687 39.7...</td>\n",
       "      <td>8005081000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1245</th>\n",
       "      <td>08</td>\n",
       "      <td>005</td>\n",
       "      <td>080300</td>\n",
       "      <td>08005080300</td>\n",
       "      <td>803</td>\n",
       "      <td>Census Tract 803</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>2526565</td>\n",
       "      <td>0</td>\n",
       "      <td>+39.6749395</td>\n",
       "      <td>-104.8564219</td>\n",
       "      <td>POLYGON ((-104.86015 39.68204, -104.85898 39.6...</td>\n",
       "      <td>8005080300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1246</th>\n",
       "      <td>08</td>\n",
       "      <td>005</td>\n",
       "      <td>080400</td>\n",
       "      <td>08005080400</td>\n",
       "      <td>804</td>\n",
       "      <td>Census Tract 804</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>2418363</td>\n",
       "      <td>0</td>\n",
       "      <td>+39.6639878</td>\n",
       "      <td>-104.8501606</td>\n",
       "      <td>POLYGON ((-104.84359 39.65845, -104.84377 39.6...</td>\n",
       "      <td>8005080400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1247</th>\n",
       "      <td>08</td>\n",
       "      <td>005</td>\n",
       "      <td>080800</td>\n",
       "      <td>08005080800</td>\n",
       "      <td>808</td>\n",
       "      <td>Census Tract 808</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>918778</td>\n",
       "      <td>0</td>\n",
       "      <td>+39.6993916</td>\n",
       "      <td>-104.8390190</td>\n",
       "      <td>POLYGON ((-104.82995 39.69662, -104.83047 39.6...</td>\n",
       "      <td>8005080800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1248</th>\n",
       "      <td>08</td>\n",
       "      <td>005</td>\n",
       "      <td>080900</td>\n",
       "      <td>08005080900</td>\n",
       "      <td>809</td>\n",
       "      <td>Census Tract 809</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>1683181</td>\n",
       "      <td>0</td>\n",
       "      <td>+39.7066413</td>\n",
       "      <td>-104.8371258</td>\n",
       "      <td>POLYGON ((-104.82884 39.70408, -104.82886 39.7...</td>\n",
       "      <td>8005080900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1249 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     STATEFP10 COUNTYFP10 TRACTCE10      GEOID10 NAME10         NAMELSAD10  \\\n",
       "0           08        051    963900  08051963900   9639  Census Tract 9639   \n",
       "1           08        051    963700  08051963700   9637  Census Tract 9637   \n",
       "2           08        051    963600  08051963600   9636  Census Tract 9636   \n",
       "3           08        051    963800  08051963800   9638  Census Tract 9638   \n",
       "4           08        021    974900  08021974900   9749  Census Tract 9749   \n",
       "...        ...        ...       ...          ...    ...                ...   \n",
       "1244        08        005    081000  08005081000    810   Census Tract 810   \n",
       "1245        08        005    080300  08005080300    803   Census Tract 803   \n",
       "1246        08        005    080400  08005080400    804   Census Tract 804   \n",
       "1247        08        005    080800  08005080800    808   Census Tract 808   \n",
       "1248        08        005    080900  08005080900    809   Census Tract 809   \n",
       "\n",
       "     MTFCC10 FUNCSTAT10     ALAND10  AWATER10   INTPTLAT10    INTPTLON10  \\\n",
       "0      G5020          S  4262312145  41657300  +38.6285818  -107.2733857   \n",
       "1      G5020          S    14502053         0  +38.5443371  -106.9270259   \n",
       "2      G5020          S  3267477045  10725478  +38.6738961  -106.7096262   \n",
       "3      G5020          S   844937722    789243  +38.8767371  -106.9086087   \n",
       "4      G5020          S  2716323548   8848645  +37.2224342  -106.2441010   \n",
       "...      ...        ...         ...       ...          ...           ...   \n",
       "1244   G5020          S     2372419         0  +39.7177635  -104.8179019   \n",
       "1245   G5020          S     2526565         0  +39.6749395  -104.8564219   \n",
       "1246   G5020          S     2418363         0  +39.6639878  -104.8501606   \n",
       "1247   G5020          S      918778         0  +39.6993916  -104.8390190   \n",
       "1248   G5020          S     1683181         0  +39.7066413  -104.8371258   \n",
       "\n",
       "                                               geometry  CensusTract  \n",
       "0     POLYGON ((-107.12846 38.81786, -107.12928 38.8...   8051963900  \n",
       "1     POLYGON ((-106.95269 38.55070, -106.95230 38.5...   8051963700  \n",
       "2     POLYGON ((-106.51828 38.95152, -106.51670 38.9...   8051963600  \n",
       "3     POLYGON ((-106.77386 38.72978, -106.77400 38.7...   8051963800  \n",
       "4     POLYGON ((-105.91019 37.22490, -105.91184 37.2...   8021974900  \n",
       "...                                                 ...          ...  \n",
       "1244  POLYGON ((-104.82687 39.71730, -104.82687 39.7...   8005081000  \n",
       "1245  POLYGON ((-104.86015 39.68204, -104.85898 39.6...   8005080300  \n",
       "1246  POLYGON ((-104.84359 39.65845, -104.84377 39.6...   8005080400  \n",
       "1247  POLYGON ((-104.82995 39.69662, -104.83047 39.6...   8005080800  \n",
       "1248  POLYGON ((-104.82884 39.70408, -104.82886 39.7...   8005080900  \n",
       "\n",
       "[1249 rows x 14 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_tracts2010 = gpd.read_file(r'G:\\My Drive\\~DUG analysis\\tl_2010_08_tract10/tl_2010_08_tract10.shp')\n",
    "census_tracts2010['CensusTract']=census_tracts2010['GEOID10'].astype('int64')\n",
    "census_tracts2010"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c2ece795",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True    1242\n",
       "Name: CensusTract, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#confirm that all the Food Access Research Atlas tracts are in the shapefile we got from the census\n",
    "fara[fara['State']=='Colorado']['CensusTract'].isin(census_tracts2010['CensusTract']).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "aa9e6d39",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CensusTract</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8051963900</th>\n",
       "      <td>POLYGON ((-107.12846 38.81786, -107.12928 38.8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8051963700</th>\n",
       "      <td>POLYGON ((-106.95269 38.55070, -106.95230 38.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8051963600</th>\n",
       "      <td>POLYGON ((-106.51828 38.95152, -106.51670 38.9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8051963800</th>\n",
       "      <td>POLYGON ((-106.77386 38.72978, -106.77400 38.7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8021974900</th>\n",
       "      <td>POLYGON ((-105.91019 37.22490, -105.91184 37.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005081000</th>\n",
       "      <td>POLYGON ((-104.82687 39.71730, -104.82687 39.7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080300</th>\n",
       "      <td>POLYGON ((-104.86015 39.68204, -104.85898 39.6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080400</th>\n",
       "      <td>POLYGON ((-104.84359 39.65845, -104.84377 39.6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080800</th>\n",
       "      <td>POLYGON ((-104.82995 39.69662, -104.83047 39.6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080900</th>\n",
       "      <td>POLYGON ((-104.82884 39.70408, -104.82886 39.7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1249 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      geometry\n",
       "CensusTract                                                   \n",
       "8051963900   POLYGON ((-107.12846 38.81786, -107.12928 38.8...\n",
       "8051963700   POLYGON ((-106.95269 38.55070, -106.95230 38.5...\n",
       "8051963600   POLYGON ((-106.51828 38.95152, -106.51670 38.9...\n",
       "8051963800   POLYGON ((-106.77386 38.72978, -106.77400 38.7...\n",
       "8021974900   POLYGON ((-105.91019 37.22490, -105.91184 37.2...\n",
       "...                                                        ...\n",
       "8005081000   POLYGON ((-104.82687 39.71730, -104.82687 39.7...\n",
       "8005080300   POLYGON ((-104.86015 39.68204, -104.85898 39.6...\n",
       "8005080400   POLYGON ((-104.84359 39.65845, -104.84377 39.6...\n",
       "8005080800   POLYGON ((-104.82995 39.69662, -104.83047 39.6...\n",
       "8005080900   POLYGON ((-104.82884 39.70408, -104.82886 39.7...\n",
       "\n",
       "[1249 rows x 1 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#prep the census data to merge with the DUG x,y location data\n",
    "census_tracts_for_merge=census_tracts2010[['geometry','CensusTract']]\n",
    "census_tracts_for_merge.set_index('CensusTract',inplace=True)\n",
    "census_tracts_for_merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "91f474c1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Geographic 2D CRS: EPSG:4269>\n",
       "Name: NAD83\n",
       "Axis Info [ellipsoidal]:\n",
       "- Lat[north]: Geodetic latitude (degree)\n",
       "- Lon[east]: Geodetic longitude (degree)\n",
       "Area of Use:\n",
       "- name: North America - onshore and offshore: Canada - Alberta; British Columbia; Manitoba; New Brunswick; Newfoundland and Labrador; Northwest Territories; Nova Scotia; Nunavut; Ontario; Prince Edward Island; Quebec; Saskatchewan; Yukon. Puerto Rico. United States (USA) - Alabama; Alaska; Arizona; Arkansas; California; Colorado; Connecticut; Delaware; Florida; Georgia; Hawaii; Idaho; Illinois; Indiana; Iowa; Kansas; Kentucky; Louisiana; Maine; Maryland; Massachusetts; Michigan; Minnesota; Mississippi; Missouri; Montana; Nebraska; Nevada; New Hampshire; New Jersey; New Mexico; New York; North Carolina; North Dakota; Ohio; Oklahoma; Oregon; Pennsylvania; Rhode Island; South Carolina; South Dakota; Tennessee; Texas; Utah; Vermont; Virginia; Washington; West Virginia; Wisconsin; Wyoming. US Virgin Islands. British Virgin Islands.\n",
       "- bounds: (167.65, 14.92, -40.73, 86.45)\n",
       "Datum: North American Datum 1983\n",
       "- Ellipsoid: GRS 1980\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_tracts2010.crs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93123498",
   "metadata": {},
   "source": [
    "\n",
    "# Combine things\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "cb3bf59c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CensusTract</th>\n",
       "      <th>State</th>\n",
       "      <th>County</th>\n",
       "      <th>Urban</th>\n",
       "      <th>Pop2010</th>\n",
       "      <th>OHU2010</th>\n",
       "      <th>GroupQuartersFlag</th>\n",
       "      <th>NUMGQTRS</th>\n",
       "      <th>PCTGQTRS</th>\n",
       "      <th>LILATracts_1And10</th>\n",
       "      <th>...</th>\n",
       "      <th>TractSeniors</th>\n",
       "      <th>TractWhite</th>\n",
       "      <th>TractBlack</th>\n",
       "      <th>TractAsian</th>\n",
       "      <th>TractNHOPI</th>\n",
       "      <th>TractAIAN</th>\n",
       "      <th>TractOMultir</th>\n",
       "      <th>TractHispanic</th>\n",
       "      <th>TractHUNV</th>\n",
       "      <th>TractSNAP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001020100</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>1912</td>\n",
       "      <td>693</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>221.0000</td>\n",
       "      <td>1,622.0000</td>\n",
       "      <td>217.0000</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>45.0000</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>102.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1001020200</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>2170</td>\n",
       "      <td>743</td>\n",
       "      <td>0</td>\n",
       "      <td>181.0000</td>\n",
       "      <td>8.3410</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>214.0000</td>\n",
       "      <td>888.0000</td>\n",
       "      <td>1,217.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>55.0000</td>\n",
       "      <td>75.0000</td>\n",
       "      <td>89.0000</td>\n",
       "      <td>156.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1001020300</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>3373</td>\n",
       "      <td>1256</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>439.0000</td>\n",
       "      <td>2,576.0000</td>\n",
       "      <td>647.0000</td>\n",
       "      <td>17.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>117.0000</td>\n",
       "      <td>87.0000</td>\n",
       "      <td>99.0000</td>\n",
       "      <td>172.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1001020400</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>4386</td>\n",
       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>904.0000</td>\n",
       "      <td>4,086.0000</td>\n",
       "      <td>193.0000</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>74.0000</td>\n",
       "      <td>85.0000</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>98.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1001020500</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>10766</td>\n",
       "      <td>4082</td>\n",
       "      <td>0</td>\n",
       "      <td>181.0000</td>\n",
       "      <td>1.6812</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1,126.0000</td>\n",
       "      <td>8,666.0000</td>\n",
       "      <td>1,437.0000</td>\n",
       "      <td>296.0000</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>48.0000</td>\n",
       "      <td>310.0000</td>\n",
       "      <td>355.0000</td>\n",
       "      <td>230.0000</td>\n",
       "      <td>339.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 147 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   CensusTract    State          County  Urban  Pop2010  OHU2010  \\\n",
       "0   1001020100  Alabama  Autauga County      1     1912      693   \n",
       "1   1001020200  Alabama  Autauga County      1     2170      743   \n",
       "2   1001020300  Alabama  Autauga County      1     3373     1256   \n",
       "3   1001020400  Alabama  Autauga County      1     4386     1722   \n",
       "4   1001020500  Alabama  Autauga County      1    10766     4082   \n",
       "\n",
       "   GroupQuartersFlag  NUMGQTRS  PCTGQTRS  LILATracts_1And10  ...  \\\n",
       "0                  0    0.0000    0.0000                  0  ...   \n",
       "1                  0  181.0000    8.3410                  1  ...   \n",
       "2                  0    0.0000    0.0000                  0  ...   \n",
       "3                  0    0.0000    0.0000                  0  ...   \n",
       "4                  0  181.0000    1.6812                  0  ...   \n",
       "\n",
       "   TractSeniors  TractWhite  TractBlack  TractAsian  TractNHOPI  TractAIAN  \\\n",
       "0      221.0000  1,622.0000    217.0000     14.0000      0.0000    14.0000   \n",
       "1      214.0000    888.0000  1,217.0000      5.0000      0.0000     5.0000   \n",
       "2      439.0000  2,576.0000    647.0000     17.0000      5.0000    11.0000   \n",
       "3      904.0000  4,086.0000    193.0000     18.0000      4.0000    11.0000   \n",
       "4    1,126.0000  8,666.0000  1,437.0000    296.0000      9.0000    48.0000   \n",
       "\n",
       "   TractOMultir  TractHispanic  TractHUNV  TractSNAP  \n",
       "0       45.0000        44.0000     6.0000   102.0000  \n",
       "1       55.0000        75.0000    89.0000   156.0000  \n",
       "2      117.0000        87.0000    99.0000   172.0000  \n",
       "3       74.0000        85.0000    21.0000    98.0000  \n",
       "4      310.0000       355.0000   230.0000   339.0000  \n",
       "\n",
       "[5 rows x 147 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fara.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1c0c08ba",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Denver County        108\n",
       "Jefferson County      40\n",
       "Arapahoe County       19\n",
       "Adams County          17\n",
       "Boulder County         2\n",
       "Broomfield County      1\n",
       "Douglas County         1\n",
       "Name: County, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#map census tract to DUG x,y locations\n",
    "gdf = gpd.GeoDataFrame(DUG_locs,geometry=DUG_locs['geometry']) # convert the DUG locations to a geodataframe\n",
    "gdf=gdf.to_crs(crs=census_tracts2010.crs) #fix the CRS to match the CensusTract data\n",
    "merged_file = gpd.sjoin(gdf, census_tracts_for_merge, how='left', predicate='within') #map it\n",
    "merged_file.rename({'index_right':'CensusTract'},axis=1,inplace=True) #rename the column correctly\n",
    "\n",
    "#get LILA indicator by Census Tract number, so we can then map this to the DUG x,y location data\n",
    "LILAtracts=fara[['CensusTract','LILATracts_1And10']].set_index('CensusTract')\n",
    "liladict=LILAtracts.to_dict()['LILATracts_1And10']\n",
    "merged_file['LILA1and10']=merged_file['CensusTract'].map(liladict)\n",
    "\n",
    "#get County by Census Tract number, so we can then map this to the DUG x,y location data\n",
    "COtracts=fara[['CensusTract','County']].set_index('CensusTract')\n",
    "COdict=COtracts.to_dict()['County']\n",
    "merged_file['County']=merged_file['CensusTract'].map(COdict)\n",
    "\n",
    "merged_file['County'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a9279850",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "County             LILA1and10\n",
       "Adams County       0             14\n",
       "                   1              3\n",
       "Arapahoe County    0             19\n",
       "Boulder County     0              2\n",
       "Broomfield County  0              1\n",
       "Denver County      0             97\n",
       "                   1             11\n",
       "Douglas County     0              1\n",
       "Jefferson County   0             38\n",
       "                   1              2\n",
       "Name: LILA1and10, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_file.groupby('County')['LILA1and10'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "9df3a10d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Field</th>\n",
       "      <th>LongName</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CensusTract</td>\n",
       "      <td>Census tract</td>\n",
       "      <td>Census tract number</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>State</td>\n",
       "      <td>State</td>\n",
       "      <td>State name</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>County</td>\n",
       "      <td>County</td>\n",
       "      <td>County name</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Urban</td>\n",
       "      <td>Urban tract</td>\n",
       "      <td>Flag for urban tract</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POP2010</td>\n",
       "      <td>Population, tract total</td>\n",
       "      <td>Population count from 2010 census</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>TractAIAN</td>\n",
       "      <td>Tract American Indian and Alaska Native popula...</td>\n",
       "      <td>Total count of American Indian and Alaska Nati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>TractOMultir</td>\n",
       "      <td>Tract Other/Multiple race population, number</td>\n",
       "      <td>Total count of Other/Multiple race population ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>TractHispanic</td>\n",
       "      <td>Tract Hispanic or Latino population, number</td>\n",
       "      <td>Total count of Hispanic or Latino population i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>TractHUNV</td>\n",
       "      <td>Tract housing units without a vehicle, number</td>\n",
       "      <td>Total count of housing units without a vehicle...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>TractSNAP</td>\n",
       "      <td>Tract housing units receiving SNAP benefits, n...</td>\n",
       "      <td>Total count of housing units receiving SNAP be...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>147 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Field                                           LongName  \\\n",
       "0      CensusTract                                       Census tract   \n",
       "1            State                                              State   \n",
       "2           County                                             County   \n",
       "3            Urban                                        Urban tract   \n",
       "4          POP2010                            Population, tract total   \n",
       "..             ...                                                ...   \n",
       "142      TractAIAN  Tract American Indian and Alaska Native popula...   \n",
       "143   TractOMultir       Tract Other/Multiple race population, number   \n",
       "144  TractHispanic        Tract Hispanic or Latino population, number   \n",
       "145      TractHUNV      Tract housing units without a vehicle, number   \n",
       "146      TractSNAP  Tract housing units receiving SNAP benefits, n...   \n",
       "\n",
       "                                           Description  \n",
       "0                                  Census tract number  \n",
       "1                                           State name  \n",
       "2                                          County name  \n",
       "3                                 Flag for urban tract  \n",
       "4                    Population count from 2010 census  \n",
       "..                                                 ...  \n",
       "142  Total count of American Indian and Alaska Nati...  \n",
       "143  Total count of Other/Multiple race population ...  \n",
       "144  Total count of Hispanic or Latino population i...  \n",
       "145  Total count of housing units without a vehicle...  \n",
       "146  Total count of housing units receiving SNAP be...  \n",
       "\n",
       "[147 rows x 3 columns]"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fara_variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "c816f1c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>LILA1and10</th>\n",
       "      <th>County</th>\n",
       "      <th>Pop</th>\n",
       "      <th>State</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CensusTract</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>8051963900</th>\n",
       "      <td>POLYGON ((-107.12846 38.81786, -107.12928 38.8...</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>Gunnison County</td>\n",
       "      <td>905.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8051963700</th>\n",
       "      <td>POLYGON ((-106.95269 38.55070, -106.95230 38.5...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Gunnison County</td>\n",
       "      <td>6,124.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8051963600</th>\n",
       "      <td>POLYGON ((-106.51828 38.95152, -106.51670 38.9...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Gunnison County</td>\n",
       "      <td>3,794.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8051963800</th>\n",
       "      <td>POLYGON ((-106.77386 38.72978, -106.77400 38.7...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Gunnison County</td>\n",
       "      <td>4,501.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8021974900</th>\n",
       "      <td>POLYGON ((-105.91019 37.22490, -105.91184 37.2...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Conejos County</td>\n",
       "      <td>4,369.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005081000</th>\n",
       "      <td>POLYGON ((-104.82687 39.71730, -104.82687 39.7...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Arapahoe County</td>\n",
       "      <td>5,450.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080300</th>\n",
       "      <td>POLYGON ((-104.86015 39.68204, -104.85898 39.6...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Arapahoe County</td>\n",
       "      <td>5,701.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080400</th>\n",
       "      <td>POLYGON ((-104.84359 39.65845, -104.84377 39.6...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Arapahoe County</td>\n",
       "      <td>4,500.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080800</th>\n",
       "      <td>POLYGON ((-104.82995 39.69662, -104.83047 39.6...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Arapahoe County</td>\n",
       "      <td>2,661.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8005080900</th>\n",
       "      <td>POLYGON ((-104.82884 39.70408, -104.82886 39.7...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Arapahoe County</td>\n",
       "      <td>3,977.0000</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1249 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      geometry  LILA1and10  \\\n",
       "CensusTract                                                                  \n",
       "8051963900   POLYGON ((-107.12846 38.81786, -107.12928 38.8...      1.0000   \n",
       "8051963700   POLYGON ((-106.95269 38.55070, -106.95230 38.5...      0.0000   \n",
       "8051963600   POLYGON ((-106.51828 38.95152, -106.51670 38.9...      0.0000   \n",
       "8051963800   POLYGON ((-106.77386 38.72978, -106.77400 38.7...      0.0000   \n",
       "8021974900   POLYGON ((-105.91019 37.22490, -105.91184 37.2...      0.0000   \n",
       "...                                                        ...         ...   \n",
       "8005081000   POLYGON ((-104.82687 39.71730, -104.82687 39.7...      0.0000   \n",
       "8005080300   POLYGON ((-104.86015 39.68204, -104.85898 39.6...      0.0000   \n",
       "8005080400   POLYGON ((-104.84359 39.65845, -104.84377 39.6...      0.0000   \n",
       "8005080800   POLYGON ((-104.82995 39.69662, -104.83047 39.6...      0.0000   \n",
       "8005080900   POLYGON ((-104.82884 39.70408, -104.82886 39.7...      0.0000   \n",
       "\n",
       "                      County        Pop     State  \n",
       "CensusTract                                        \n",
       "8051963900   Gunnison County   905.0000  Colorado  \n",
       "8051963700   Gunnison County 6,124.0000  Colorado  \n",
       "8051963600   Gunnison County 3,794.0000  Colorado  \n",
       "8051963800   Gunnison County 4,501.0000  Colorado  \n",
       "8021974900    Conejos County 4,369.0000  Colorado  \n",
       "...                      ...        ...       ...  \n",
       "8005081000   Arapahoe County 5,450.0000  Colorado  \n",
       "8005080300   Arapahoe County 5,701.0000  Colorado  \n",
       "8005080400   Arapahoe County 4,500.0000  Colorado  \n",
       "8005080800   Arapahoe County 2,661.0000  Colorado  \n",
       "8005080900   Arapahoe County 3,977.0000  Colorado  \n",
       "\n",
       "[1249 rows x 5 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poptracts=fara[['CensusTract','Pop2010']].set_index('CensusTract')\n",
    "popdict=poptracts.to_dict()['Pop2010']\n",
    "#popdict\n",
    "\n",
    "statetracts=fara[['CensusTract','State']].set_index('CensusTract')\n",
    "statedict=statetracts.to_dict()['State']\n",
    "#statedict\n",
    "\n",
    "\n",
    "basemap=census_tracts_for_merge.copy()\n",
    "basemap['LILA1and10']=basemap.index.map(liladict)\n",
    "basemap['County']=basemap.index.map(COdict)\n",
    "basemap['Pop']=basemap.index.map(popdict)\n",
    "basemap['State']=basemap.index.map(statedict)\n",
    "basemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "dcee2ba1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(39.625, 39.92)"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "basemap=census_tracts_for_merge.copy()\n",
    "basemap['LILA1and10']=basemap.index.map(liladict)\n",
    "basemap['County']=basemap.index.map(COdict)\n",
    "basemap['Pop']=basemap.index.map(popdict)\n",
    "basemap['State']=basemap.index.map(statedict)\n",
    "\n",
    "plt.figure(figsize=(20,20))\n",
    "base=basemap[basemap['State']=='Colorado'].boundary.plot(color='black',linewidth=0.05)\n",
    "basemap[basemap['County']=='Denver County'].plot(ax=base,color='lightblue')\n",
    "basemap[(basemap['LILA1and10']==1)&(basemap['County']=='Denver County')].boundary.plot(ax=base,color='orange',label='Low Income and Low Food-Access')\n",
    "merged_file.plot(ax=base,color='green',markersize=1)\n",
    "plt.xlim(-105.07,-104.6)\n",
    "plt.ylim(39.625,39.92)\n",
    "plt."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60e21511",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "basemap[(basemap['LILA1and10']==1)&(basemap['County']=='Denver County')].explore()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a0636306",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "6e036315",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Flag for low-income and low access when considering low accessibilty at 1 and 10 miles']"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fara_variables[fara_variables['Field']=='LILATracts_1And10']['Description'].to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "20a88340",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Description</th>\n",
       "      <th>geometry</th>\n",
       "      <th>CensusTract</th>\n",
       "      <th>LILA1and10</th>\n",
       "      <th>County</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36th &amp; Lafayette Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0k-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.97074 39.76709 0.00000)</td>\n",
       "      <td>8031003601</td>\n",
       "      <td>0</td>\n",
       "      <td>Denver County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Academia Sandoval School Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0k-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-105.01513 39.76585 0.00000)</td>\n",
       "      <td>8031000402</td>\n",
       "      <td>0</td>\n",
       "      <td>Denver County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Agape Community Gardens on Williams (Not open ...</td>\n",
       "      <td>&lt;img src=\"https://doc-10-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.96636 39.75920 0.00000)</td>\n",
       "      <td>8031002300</td>\n",
       "      <td>0</td>\n",
       "      <td>Denver County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Allison Gardens at Semper Farm</td>\n",
       "      <td>&lt;img src=\"https://doc-0c-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-105.07087 39.86479 0.00000)</td>\n",
       "      <td>8059009827</td>\n",
       "      <td>0</td>\n",
       "      <td>Jefferson County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Anythink Commerce City Library Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0g-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.91309 39.82675 0.00000)</td>\n",
       "      <td>8001008705</td>\n",
       "      <td>0</td>\n",
       "      <td>Adams County</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>Market Station Community Garden</td>\n",
       "      <td>Address&lt;br&gt;1661 Market St., Denver CO 80202&lt;br...</td>\n",
       "      <td>POINT Z (-104.99773 39.75053 0.00000)</td>\n",
       "      <td>8031001701</td>\n",
       "      <td>0</td>\n",
       "      <td>Denver County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>Nome Community Garden</td>\n",
       "      <td>&lt;img src=\"https://doc-0c-7o-mymaps.googleuserc...</td>\n",
       "      <td>POINT Z (-104.85148 39.73447 0.00000)</td>\n",
       "      <td>8005007400</td>\n",
       "      <td>0</td>\n",
       "      <td>Arapahoe County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>East Middle School Community Garden</td>\n",
       "      <td>Address&lt;br&gt;1275 Fraser Street&lt;br&gt;&lt;br&gt;Micro Net...</td>\n",
       "      <td>POINT Z (-104.81309 39.73409 0.00000)</td>\n",
       "      <td>8005081800</td>\n",
       "      <td>0</td>\n",
       "      <td>Arapahoe County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>Mountain View International Garden</td>\n",
       "      <td>Address&lt;br&gt;10700 E. Evans Ave. Aurora&lt;br&gt;&lt;br&gt;M...</td>\n",
       "      <td>POINT Z (-104.86325 39.67809 0.00000)</td>\n",
       "      <td>8005080300</td>\n",
       "      <td>0</td>\n",
       "      <td>Arapahoe County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>South Lakewood Elementary Community Garden</td>\n",
       "      <td>Address&lt;br&gt;8425 W 1st Ave, Lakewood&lt;br&gt;&lt;br&gt;Mic...</td>\n",
       "      <td>POINT Z (-105.09255 39.71899 0.00000)</td>\n",
       "      <td>8059011202</td>\n",
       "      <td>0</td>\n",
       "      <td>Jefferson County</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>188 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Name  \\\n",
       "0                    36th & Lafayette Community Garden   \n",
       "1            Academia Sandoval School Community Garden   \n",
       "2    Agape Community Gardens on Williams (Not open ...   \n",
       "3                       Allison Gardens at Semper Farm   \n",
       "4      Anythink Commerce City Library Community Garden   \n",
       "..                                                 ...   \n",
       "183                    Market Station Community Garden   \n",
       "184                              Nome Community Garden   \n",
       "185                East Middle School Community Garden   \n",
       "186                 Mountain View International Garden   \n",
       "187         South Lakewood Elementary Community Garden   \n",
       "\n",
       "                                           Description  \\\n",
       "0    <img src=\"https://doc-0k-7o-mymaps.googleuserc...   \n",
       "1    <img src=\"https://doc-0k-7o-mymaps.googleuserc...   \n",
       "2    <img src=\"https://doc-10-7o-mymaps.googleuserc...   \n",
       "3    <img src=\"https://doc-0c-7o-mymaps.googleuserc...   \n",
       "4    <img src=\"https://doc-0g-7o-mymaps.googleuserc...   \n",
       "..                                                 ...   \n",
       "183  Address<br>1661 Market St., Denver CO 80202<br...   \n",
       "184  <img src=\"https://doc-0c-7o-mymaps.googleuserc...   \n",
       "185  Address<br>1275 Fraser Street<br><br>Micro Net...   \n",
       "186  Address<br>10700 E. Evans Ave. Aurora<br><br>M...   \n",
       "187  Address<br>8425 W 1st Ave, Lakewood<br><br>Mic...   \n",
       "\n",
       "                                  geometry  CensusTract  LILA1and10  \\\n",
       "0    POINT Z (-104.97074 39.76709 0.00000)   8031003601           0   \n",
       "1    POINT Z (-105.01513 39.76585 0.00000)   8031000402           0   \n",
       "2    POINT Z (-104.96636 39.75920 0.00000)   8031002300           0   \n",
       "3    POINT Z (-105.07087 39.86479 0.00000)   8059009827           0   \n",
       "4    POINT Z (-104.91309 39.82675 0.00000)   8001008705           0   \n",
       "..                                     ...          ...         ...   \n",
       "183  POINT Z (-104.99773 39.75053 0.00000)   8031001701           0   \n",
       "184  POINT Z (-104.85148 39.73447 0.00000)   8005007400           0   \n",
       "185  POINT Z (-104.81309 39.73409 0.00000)   8005081800           0   \n",
       "186  POINT Z (-104.86325 39.67809 0.00000)   8005080300           0   \n",
       "187  POINT Z (-105.09255 39.71899 0.00000)   8059011202           0   \n",
       "\n",
       "               County  \n",
       "0       Denver County  \n",
       "1       Denver County  \n",
       "2       Denver County  \n",
       "3    Jefferson County  \n",
       "4        Adams County  \n",
       "..                ...  \n",
       "183     Denver County  \n",
       "184   Arapahoe County  \n",
       "185   Arapahoe County  \n",
       "186   Arapahoe County  \n",
       "187  Jefferson County  \n",
       "\n",
       "[188 rows x 6 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "7d7c4dd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium\n",
    "\n",
    "denvmetro=['Denver County','Adams County','Arapahoe County','Douglas County','Jefferson County','Broomfield County','Boulder County']\n",
    "\n",
    "basemap.rename(columns={'LILA1and10':'Low-income_Low-food-access','Pop':'Population'},inplace=True)\n",
    "basemap['Low-income_Low-food-access'].replace({0:\"no\",1:\"yes\"},inplace=True)\n",
    "\n",
    "m = basemap[basemap['County'].isin(denvmetro)].explore(\n",
    "    color='antiquewhite',\n",
    "    name=\"CensusTracts2010\" # name of the layer in the map\n",
    ")\n",
    "\n",
    "basemap[(basemap['Low-income_Low-food-access']=='yes')&(basemap['County'].isin(denvmetro))].explore(\n",
    "    m=m,\n",
    "    color='lightcoral',\n",
    "    name='Low Income & Low Food Access'\n",
    ")\n",
    "\n",
    "merged_file.explore(\n",
    "     m=m, # pass the map object\n",
    "     color=\"seagreen\", # use seagreen color on all points\n",
    "     tooltip=\"Name\", # show \"name\" column in the tooltip\n",
    "     tooltip_kwds=dict(labels=False), # do not show column label in the tooltip\n",
    "     name=\"DUG\" # name of the layer in the map\n",
    ")\n",
    "\n",
    "folium.TileLayer('Stamen Toner', control=True).add_to(m)  # use folium to add alternative tiles\n",
    "folium.LayerControl().add_to(m)  # use folium to add layer control\n",
    "\n",
    "#m  # show map\n",
    "m.save(\"Denver_DUG_LILATracts.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa9f4171",
   "metadata": {},
   "source": [
    "---\n",
    "---\n",
    "---\n",
    "\n",
    "**\"Defining Low-Income, Low-Access Food Areas\"**, Congressional Research Service, 06-01-2021, page 1:\n",
    "> - low-income (LI): poverty rate of 20% or greater, or median family income at or below 80% of the statewide or metropolitan area median family income; and \n",
    "> - low-access (LA): a low-income tract with at least 500 people or 33% of the tract’s population living more than 1 mile (urban areas) or more than 10 miles (rural areas) from the nearest supermarket or grocery store. (USDALA data are also available assuming different measures of distance, ranging 0.5 miles to 20 miles).\n",
    "(https://crsreports.congress.gov/product/pdf/IF/IF11841)\n",
    "----\n",
    "\n",
    "**UDSA Food Access Research Atlas (FARA)**:\n",
    "- info = https://www.ers.usda.gov/data-products/food-access-research-atlas/\n",
    "- data = https://www.ers.usda.gov/data-products/food-access-research-atlas/download-the-data/\n",
    "    - This is the \"current\", or most recent version of FARA, last updated 04-27-2021.\n",
    "    - Note that even though this FARA is \"current\", it uses 2010 Census Tracts, not 2020.\n",
    "----\n",
    "\n",
    "**Census Tract Mapping data: US Census Bureau TIGER/Line Shapefiles**\n",
    "- Main page = https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html\n",
    "- Download via web interface = https://www.census.gov/cgi-bin/geo/shapefiles/index.php \n",
    "    - Select year = 2010\n",
    "    - Select layer type = Census Tracts\n",
    "    - Submit\n",
    "    - Census Tract (2010), Select a State = Colorado\n",
    "- Note: we use 2010 Census Tract data to match the 2010 Tracts used in the FARA data from USDA.\n",
    "----\n",
    "\n",
    "**Denver Urban Gardens (DUG): Garden Directory**:\n",
    "- website = https://dug.org/find-a-garden/\n",
    "- linked Google Map = https://www.google.com/maps/d/viewer?mid=1DQq0JnovDqoXbygKTYweQsUfG4A&ll=39.74082951828451%2C-105.00433671452163&z=12\n",
    "    - From the Google Map, click the 3-dot menu and \"Download KML\"\n",
    "----\n",
    "**ProPublica Nonprofit Explorer: Denver Urban Gardens, IRS Form 990s**:\n",
    "- site = https://projects.propublica.org/nonprofits/organizations/742374848\n",
    "- Note: ProPublica also has an API that allowed me to access this Form 990 information directly from Python as well. HOWEVER, because some of the more interesting information on \"Operating Expenses\" are included in item #24 of the IRS Form 990, which has \"write-in\" names of the expense categories, and those \"write-in\" names are not entered in the same order every year, and the \"write-in\" names change over time, I also referenced the PDF files to extract that information.\n",
    "\n",
    "---\n",
    "---\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f23f1ba",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6eb8eaba",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}