zhik/tracts and census data.ipynb

## tracts and census data.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "94d6c677",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from cenpy import products, explorer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "582249dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('../lib/data-public/oca_addresses_with_ct.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0e654f5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "geoid\n",
       "36081045500    9066\n",
       "36029017400    5531\n",
       "36029004402    5329\n",
       "36081033404    5270\n",
       "36083041102    4908\n",
       "               ... \n",
       "36081024600       1\n",
       "36067012800       1\n",
       "36067012700       1\n",
       "36057072200       1\n",
       "36019100200       1\n",
       "Name: count, Length: 4014, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['geoid'] = df['geoid'].astype(str)\n",
    "df.value_counts('geoid')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ed1df2f",
   "metadata": {},
   "source": [
    "### Grab census data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "0d45a11c",
   "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>GEOID</th>\n",
       "      <th>MEDIAN GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36001000100</td>\n",
       "      <td>0.288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36001000201</td>\n",
       "      <td>0.382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36001000202</td>\n",
       "      <td>0.426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36001000301</td>\n",
       "      <td>0.377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>36001000302</td>\n",
       "      <td>0.354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5406</th>\n",
       "      <td>36123150301</td>\n",
       "      <td>0.247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5407</th>\n",
       "      <td>36123150302</td>\n",
       "      <td>0.439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5408</th>\n",
       "      <td>36123150400</td>\n",
       "      <td>0.325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5409</th>\n",
       "      <td>36123150501</td>\n",
       "      <td>0.192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5410</th>\n",
       "      <td>36123150502</td>\n",
       "      <td>0.250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5063 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            GEOID  MEDIAN GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME\n",
       "0     36001000100                                              0.288    \n",
       "1     36001000201                                              0.382    \n",
       "2     36001000202                                              0.426    \n",
       "3     36001000301                                              0.377    \n",
       "4     36001000302                                              0.354    \n",
       "...           ...                                                ...    \n",
       "5406  36123150301                                              0.247    \n",
       "5407  36123150302                                              0.439    \n",
       "5408  36123150400                                              0.325    \n",
       "5409  36123150501                                              0.192    \n",
       "5410  36123150502                                              0.250    \n",
       "\n",
       "[5063 rows x 2 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cenn = products.APIConnection(\"ACSDT5Y2021\") \n",
    "cols = {\n",
    "    \"B25071_001E\": \"MEDIAN GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME\" # IN THE PAST 12 MONTHS\n",
    "    }\n",
    "\n",
    "b2 = cenn.query(cols.keys(), \n",
    "    geo_unit='tract',\n",
    "    geo_filter={\"state\": '36'})\n",
    "\n",
    "b2['GEOID'] = b2.apply(lambda r: f\"{r['state']}{r['county']}{r['tract']}\", axis = 1)\n",
    "b2['B25071_001E'] = b2['B25071_001E'].astype(float) / 100\n",
    "\n",
    "b2 = b2[b2['B25071_001E'] > 0]\n",
    "\n",
    "b2 = b2.rename(columns = cols)[['GEOID']+ list(cols.values())]\n",
    "b2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4225bc5e",
   "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>GEOID</th>\n",
       "      <th>HOUSEHOLDS</th>\n",
       "      <th>Occupied housing units!!Renter-occupied</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36001000100</td>\n",
       "      <td>825</td>\n",
       "      <td>507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36001000201</td>\n",
       "      <td>1222</td>\n",
       "      <td>950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36001000202</td>\n",
       "      <td>1119</td>\n",
       "      <td>756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36001000301</td>\n",
       "      <td>1141</td>\n",
       "      <td>821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>36001000302</td>\n",
       "      <td>1845</td>\n",
       "      <td>1261</td>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>5406</th>\n",
       "      <td>36123150301</td>\n",
       "      <td>887</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5407</th>\n",
       "      <td>36123150302</td>\n",
       "      <td>719</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5408</th>\n",
       "      <td>36123150400</td>\n",
       "      <td>1229</td>\n",
       "      <td>370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5409</th>\n",
       "      <td>36123150501</td>\n",
       "      <td>1008</td>\n",
       "      <td>333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5410</th>\n",
       "      <td>36123150502</td>\n",
       "      <td>845</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5229 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            GEOID  HOUSEHOLDS  Occupied housing units!!Renter-occupied\n",
       "0     36001000100         825                                      507\n",
       "1     36001000201        1222                                      950\n",
       "2     36001000202        1119                                      756\n",
       "3     36001000301        1141                                      821\n",
       "4     36001000302        1845                                     1261\n",
       "...           ...         ...                                      ...\n",
       "5406  36123150301         887                                      108\n",
       "5407  36123150302         719                                       84\n",
       "5408  36123150400        1229                                      370\n",
       "5409  36123150501        1008                                      333\n",
       "5410  36123150502         845                                       80\n",
       "\n",
       "[5229 rows x 3 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cenn = products.APIConnection(\"ACSDP5Y2021\")\n",
    "\n",
    "#https://api.census.gov/data/2019/acs/acs5/profile/groups/DP04.html\n",
    "cols = {\n",
    "    \"DP02_0001E\": \"HOUSEHOLDS\",\n",
    "    \"DP04_0047E\":\"Occupied housing units!!Renter-occupied\"\n",
    "    }\n",
    "\n",
    "d2 = cenn.query(cols.keys(), \n",
    "    geo_unit='tract',\n",
    "    geo_filter={\"state\": '36'})\n",
    "\n",
    "d2['GEOID'] = d2.apply(lambda r: f\"{r['state']}{r['county']}{r['tract']}\", axis = 1)\n",
    "d2['DP02_0001E'] = d2['DP02_0001E'].astype(int)\n",
    "d2['DP04_0047E'] = d2['DP04_0047E'].astype(int)\n",
    "\n",
    "d2 = d2[d2['DP04_0047E'] > 0]\n",
    "d2 = d2.rename(columns = cols)[['GEOID']+ list(cols.values())]\n",
    "d2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "2ffa7c4e",
   "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>GEOID</th>\n",
       "      <th>MEDIAN GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME</th>\n",
       "      <th>HOUSEHOLDS</th>\n",
       "      <th>Occupied housing units!!Renter-occupied</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3577</th>\n",
       "      <td>36081054800</td>\n",
       "      <td>0.199</td>\n",
       "      <td>694</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>36007014500</td>\n",
       "      <td>0.510</td>\n",
       "      <td>1432</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4939</th>\n",
       "      <td>36119008404</td>\n",
       "      <td>0.290</td>\n",
       "      <td>2038</td>\n",
       "      <td>1297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4760</th>\n",
       "      <td>36113072001</td>\n",
       "      <td>0.312</td>\n",
       "      <td>885</td>\n",
       "      <td>287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2037</th>\n",
       "      <td>36055009301</td>\n",
       "      <td>0.316</td>\n",
       "      <td>906</td>\n",
       "      <td>748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1539</th>\n",
       "      <td>36047044000</td>\n",
       "      <td>0.336</td>\n",
       "      <td>857</td>\n",
       "      <td>551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1529</th>\n",
       "      <td>36047043000</td>\n",
       "      <td>0.405</td>\n",
       "      <td>1277</td>\n",
       "      <td>1037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3714</th>\n",
       "      <td>36081081400</td>\n",
       "      <td>0.465</td>\n",
       "      <td>1026</td>\n",
       "      <td>297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>36005037100</td>\n",
       "      <td>0.314</td>\n",
       "      <td>1683</td>\n",
       "      <td>1528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2903</th>\n",
       "      <td>36067010700</td>\n",
       "      <td>0.293</td>\n",
       "      <td>936</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            GEOID  MEDIAN GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME  \\\n",
       "3577  36081054800                                              0.199       \n",
       "494   36007014500                                              0.510       \n",
       "4939  36119008404                                              0.290       \n",
       "4760  36113072001                                              0.312       \n",
       "2037  36055009301                                              0.316       \n",
       "1539  36047044000                                              0.336       \n",
       "1529  36047043000                                              0.405       \n",
       "3714  36081081400                                              0.465       \n",
       "356   36005037100                                              0.314       \n",
       "2903  36067010700                                              0.293       \n",
       "\n",
       "      HOUSEHOLDS  Occupied housing units!!Renter-occupied  \n",
       "3577         694                                      112  \n",
       "494         1432                                      193  \n",
       "4939        2038                                     1297  \n",
       "4760         885                                      287  \n",
       "2037         906                                      748  \n",
       "1539         857                                      551  \n",
       "1529        1277                                     1037  \n",
       "3714        1026                                      297  \n",
       "356         1683                                     1528  \n",
       "2903         936                                      360  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "acs = pd.merge(b2, d2, on = 'GEOID', how = 'inner')\n",
    "acs.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b866f8d5",
   "metadata": {},
   "source": [
    "### Join and normalize "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "632da9e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "table = pd.DataFrame(df.value_counts('geoid')).reset_index().merge(\n",
    "    acs, left_on = 'geoid', right_on = 'GEOID')\n",
    "\n",
    "table['cases per 100 units'] = (table['count'] / table['Occupied housing units!!Renter-occupied']) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "52e85432",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 400.0)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = plt.subplot(111)\n",
    "\n",
    "table.plot.scatter('MEDIAN GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME','cases per 100 units', \n",
    "                   c= '#ff080805', ax = ax)\n",
    "\n",
    "\n",
    "ax.set_ylim(0,400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "b46faa24",
   "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>geoid</th>\n",
       "      <th>count</th>\n",
       "      <th>cases per 100 units</th>\n",
       "      <th>link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1231</th>\n",
       "      <td>36061011300</td>\n",
       "      <td>341</td>\n",
       "      <td>1705.000000</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>36061010900</td>\n",
       "      <td>599</td>\n",
       "      <td>880.882353</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>36083041102</td>\n",
       "      <td>4908</td>\n",
       "      <td>700.142653</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36029017400</td>\n",
       "      <td>5531</td>\n",
       "      <td>676.988984</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>36001000202</td>\n",
       "      <td>3935</td>\n",
       "      <td>520.502646</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3828</th>\n",
       "      <td>36111953400</td>\n",
       "      <td>1</td>\n",
       "      <td>0.081967</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US361...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3771</th>\n",
       "      <td>36055013902</td>\n",
       "      <td>1</td>\n",
       "      <td>0.075930</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3750</th>\n",
       "      <td>36001013602</td>\n",
       "      <td>1</td>\n",
       "      <td>0.075301</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3809</th>\n",
       "      <td>36067011102</td>\n",
       "      <td>1</td>\n",
       "      <td>0.066934</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3760</th>\n",
       "      <td>36027300000</td>\n",
       "      <td>1</td>\n",
       "      <td>0.063211</td>\n",
       "      <td>https://censusreporter.org/profiles/14000US360...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3848 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            geoid  count  cases per 100 units  \\\n",
       "1231  36061011300    341          1705.000000   \n",
       "753   36061010900    599           880.882353   \n",
       "4     36083041102   4908           700.142653   \n",
       "1     36029017400   5531           676.988984   \n",
       "9     36001000202   3935           520.502646   \n",
       "...           ...    ...                  ...   \n",
       "3828  36111953400      1             0.081967   \n",
       "3771  36055013902      1             0.075930   \n",
       "3750  36001013602      1             0.075301   \n",
       "3809  36067011102      1             0.066934   \n",
       "3760  36027300000      1             0.063211   \n",
       "\n",
       "                                                   link  \n",
       "1231  https://censusreporter.org/profiles/14000US360...  \n",
       "753   https://censusreporter.org/profiles/14000US360...  \n",
       "4     https://censusreporter.org/profiles/14000US360...  \n",
       "1     https://censusreporter.org/profiles/14000US360...  \n",
       "9     https://censusreporter.org/profiles/14000US360...  \n",
       "...                                                 ...  \n",
       "3828  https://censusreporter.org/profiles/14000US361...  \n",
       "3771  https://censusreporter.org/profiles/14000US360...  \n",
       "3750  https://censusreporter.org/profiles/14000US360...  \n",
       "3809  https://censusreporter.org/profiles/14000US360...  \n",
       "3760  https://censusreporter.org/profiles/14000US360...  \n",
       "\n",
       "[3848 rows x 4 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_with_links = table[['geoid','count','cases per 100 units']].copy().sort_values('cases per 100 units', ascending = False)\n",
    "table_with_links['link'] = 'https://censusreporter.org/profiles/14000US' + table_with_links['geoid']\n",
    "\n",
    "table_with_links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "357f4c9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "table_with_links.to_csv('../lib/data-public/table_with_links.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f37584f5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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