02_eda_main.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Removed some extra columns.\n",
    "Some D4 and D5 columns have -99999 values which I plan on fixing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/original_data/air_walk_merged.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>name</th>\n",
       "      <th>location_type</th>\n",
       "      <th>pm_2.5</th>\n",
       "      <th>temp_f</th>\n",
       "      <th>temp_c</th>\n",
       "      <th>humidity</th>\n",
       "      <th>pressure</th>\n",
       "      <th>...</th>\n",
       "      <th>D5DRI</th>\n",
       "      <th>D5DE</th>\n",
       "      <th>D5DEI</th>\n",
       "      <th>D2A_Ranked</th>\n",
       "      <th>D2B_Ranked</th>\n",
       "      <th>D3B_Ranked</th>\n",
       "      <th>D4A_Ranked</th>\n",
       "      <th>NatWalkInd</th>\n",
       "      <th>Shape_Length</th>\n",
       "      <th>Shape_Area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22751</td>\n",
       "      <td>36.807377</td>\n",
       "      <td>-119.796109</td>\n",
       "      <td>#ValleyClimate</td>\n",
       "      <td>outside</td>\n",
       "      <td>19.54</td>\n",
       "      <td>84.0</td>\n",
       "      <td>28.888889</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1010.30</td>\n",
       "      <td>...</td>\n",
       "      <td>0.586928</td>\n",
       "      <td>0.003201</td>\n",
       "      <td>0.500064</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>15.666667</td>\n",
       "      <td>4825.986205</td>\n",
       "      <td>1.290175e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30755</td>\n",
       "      <td>36.737668</td>\n",
       "      <td>-119.778839</td>\n",
       "      <td>'S' St Between Inyo and Mono</td>\n",
       "      <td>outside</td>\n",
       "      <td>18.52</td>\n",
       "      <td>93.0</td>\n",
       "      <td>33.888889</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1009.91</td>\n",
       "      <td>...</td>\n",
       "      <td>0.643972</td>\n",
       "      <td>0.003847</td>\n",
       "      <td>0.600998</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>3072.308296</td>\n",
       "      <td>4.465223e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>122943</td>\n",
       "      <td>38.524431</td>\n",
       "      <td>-121.439374</td>\n",
       "      <td>(AMTS_SCANS_044)</td>\n",
       "      <td>inside</td>\n",
       "      <td>6.00</td>\n",
       "      <td>75.0</td>\n",
       "      <td>23.888889</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1021.05</td>\n",
       "      <td>...</td>\n",
       "      <td>0.190835</td>\n",
       "      <td>0.001870</td>\n",
       "      <td>0.356624</td>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>17.833333</td>\n",
       "      <td>2638.457599</td>\n",
       "      <td>4.120484e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>118437</td>\n",
       "      <td>38.801826</td>\n",
       "      <td>-121.265809</td>\n",
       "      <td>*Checks before every breath*</td>\n",
       "      <td>inside</td>\n",
       "      <td>2.04</td>\n",
       "      <td>76.0</td>\n",
       "      <td>24.444444</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1013.28</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019445</td>\n",
       "      <td>0.000288</td>\n",
       "      <td>0.054951</td>\n",
       "      <td>13</td>\n",
       "      <td>20</td>\n",
       "      <td>19</td>\n",
       "      <td>17</td>\n",
       "      <td>17.500000</td>\n",
       "      <td>5616.022512</td>\n",
       "      <td>1.233707e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>39625</td>\n",
       "      <td>37.509889</td>\n",
       "      <td>-122.317735</td>\n",
       "      <td>-------{---(@</td>\n",
       "      <td>outside</td>\n",
       "      <td>18.84</td>\n",
       "      <td>81.0</td>\n",
       "      <td>27.222222</td>\n",
       "      <td>24.0</td>\n",
       "      <td>997.21</td>\n",
       "      <td>...</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>7</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>8.666667</td>\n",
       "      <td>6296.012985</td>\n",
       "      <td>7.846879e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 140 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id        lat         lon                          name location_type  \\\n",
       "0   22751  36.807377 -119.796109                #ValleyClimate       outside   \n",
       "1   30755  36.737668 -119.778839  'S' St Between Inyo and Mono       outside   \n",
       "2  122943  38.524431 -121.439374              (AMTS_SCANS_044)        inside   \n",
       "3  118437  38.801826 -121.265809  *Checks before every breath*        inside   \n",
       "4   39625  37.509889 -122.317735                 -------{---(@       outside   \n",
       "\n",
       "   pm_2.5  temp_f     temp_c  humidity  pressure  ...         D5DRI  \\\n",
       "0   19.54    84.0  28.888889      22.0   1010.30  ...      0.586928   \n",
       "1   18.52    93.0  33.888889      16.0   1009.91  ...      0.643972   \n",
       "2    6.00    75.0  23.888889      42.0   1021.05  ...      0.190835   \n",
       "3    2.04    76.0  24.444444      34.0   1013.28  ...      0.019445   \n",
       "4   18.84    81.0  27.222222      24.0    997.21  ... -99999.000000   \n",
       "\n",
       "           D5DE         D5DEI  D2A_Ranked  D2B_Ranked  D3B_Ranked  D4A_Ranked  \\\n",
       "0      0.003201      0.500064          20          18          13          15   \n",
       "1      0.003847      0.600998           5           2          14          20   \n",
       "2      0.001870      0.356624          18          19          18          17   \n",
       "3      0.000288      0.054951          13          20          19          17   \n",
       "4 -99999.000000 -99999.000000           7          15          14           1   \n",
       "\n",
       "   NatWalkInd  Shape_Length    Shape_Area  \n",
       "0   15.666667   4825.986205  1.290175e+06  \n",
       "1   12.500000   3072.308296  4.465223e+05  \n",
       "2   17.833333   2638.457599  4.120484e+05  \n",
       "3   17.500000   5616.022512  1.233707e+06  \n",
       "4    8.666667   6296.012985  7.846879e+05  \n",
       "\n",
       "[5 rows x 140 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9538, 140)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filter and drop columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Outside only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.query('location_type == \"outside\"', inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_cols = [\n",
    "    'id', 'lat', 'lon', 'temp_c', 'humidity', 'pressure', \n",
    "    'last_seen', '10min_avg', '30min_avg', '1hour_avg', '6hour_avg', \n",
    "    '1day_avg', 'OBJECTID', 'GEOID20', 'location_type',\n",
    "    'AutoOwn0', 'AutoOwn1', 'AutoOwn2p']\n",
    "\n",
    "df1= df.drop(columns = drop_cols)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### D1_flag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    6560\n",
       "1       8\n",
       "Name: D1_FLAG, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['D1_FLAG'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>pm_2.5</th>\n",
       "      <th>temp_f</th>\n",
       "      <th>model</th>\n",
       "      <th>hidden</th>\n",
       "      <th>flagged</th>\n",
       "      <th>downgraded</th>\n",
       "      <th>age</th>\n",
       "      <th>is_owner</th>\n",
       "      <th>1week_avg</th>\n",
       "      <th>fips_id</th>\n",
       "      <th>STATEFP</th>\n",
       "      <th>COUNTYFP</th>\n",
       "      <th>TRACTCE</th>\n",
       "      <th>BLKGRPCE</th>\n",
       "      <th>CSA</th>\n",
       "      <th>CSA_Name</th>\n",
       "      <th>CBSA</th>\n",
       "      <th>CBSA_Name</th>\n",
       "      <th>CBSA_POP</th>\n",
       "      <th>CBSA_EMP</th>\n",
       "      <th>CBSA_WRK</th>\n",
       "      <th>Ac_Total</th>\n",
       "      <th>Ac_Water</th>\n",
       "      <th>Ac_Land</th>\n",
       "      <th>Ac_Unpr</th>\n",
       "      <th>TotPop</th>\n",
       "      <th>CountHU</th>\n",
       "      <th>HH</th>\n",
       "      <th>P_WrkAge</th>\n",
       "      <th>Pct_AO0</th>\n",
       "      <th>Pct_AO1</th>\n",
       "      <th>Pct_AO2p</th>\n",
       "      <th>Workers</th>\n",
       "      <th>R_LowWageWk</th>\n",
       "      <th>R_MedWageWk</th>\n",
       "      <th>R_HiWageWk</th>\n",
       "      <th>R_PCTLOWWAGE</th>\n",
       "      <th>TotEmp</th>\n",
       "      <th>E5_Ret</th>\n",
       "      <th>E5_Off</th>\n",
       "      <th>E5_Ind</th>\n",
       "      <th>E5_Svc</th>\n",
       "      <th>E5_Ent</th>\n",
       "      <th>E8_Ret</th>\n",
       "      <th>E8_off</th>\n",
       "      <th>E8_Ind</th>\n",
       "      <th>E8_Svc</th>\n",
       "      <th>E8_Ent</th>\n",
       "      <th>E8_Ed</th>\n",
       "      <th>E8_Hlth</th>\n",
       "      <th>E8_Pub</th>\n",
       "      <th>E_LowWageWk</th>\n",
       "      <th>E_MedWageWk</th>\n",
       "      <th>E_HiWageWk</th>\n",
       "      <th>E_PctLowWage</th>\n",
       "      <th>D1A</th>\n",
       "      <th>D1B</th>\n",
       "      <th>D1C</th>\n",
       "      <th>D1C5_RET</th>\n",
       "      <th>D1C5_OFF</th>\n",
       "      <th>D1C5_IND</th>\n",
       "      <th>D1C5_SVC</th>\n",
       "      <th>D1C5_ENT</th>\n",
       "      <th>D1C8_RET</th>\n",
       "      <th>D1C8_OFF</th>\n",
       "      <th>D1C8_IND</th>\n",
       "      <th>D1C8_SVC</th>\n",
       "      <th>D1C8_ENT</th>\n",
       "      <th>D1C8_ED</th>\n",
       "      <th>D1C8_HLTH</th>\n",
       "      <th>D1C8_PUB</th>\n",
       "      <th>D1D</th>\n",
       "      <th>D1_FLAG</th>\n",
       "      <th>D2A_JPHH</th>\n",
       "      <th>D2B_E5MIX</th>\n",
       "      <th>D2B_E5MIXA</th>\n",
       "      <th>D2B_E8MIX</th>\n",
       "      <th>D2B_E8MIXA</th>\n",
       "      <th>D2A_EPHHM</th>\n",
       "      <th>D2C_TRPMX1</th>\n",
       "      <th>D2C_TRPMX2</th>\n",
       "      <th>D2C_TRIPEQ</th>\n",
       "      <th>D2R_JOBPOP</th>\n",
       "      <th>D2R_WRKEMP</th>\n",
       "      <th>D2A_WRKEMP</th>\n",
       "      <th>D2C_WREMLX</th>\n",
       "      <th>D3A</th>\n",
       "      <th>D3AAO</th>\n",
       "      <th>D3AMM</th>\n",
       "      <th>D3APO</th>\n",
       "      <th>D3B</th>\n",
       "      <th>D3BAO</th>\n",
       "      <th>D3BMM3</th>\n",
       "      <th>D3BMM4</th>\n",
       "      <th>D3BPO3</th>\n",
       "      <th>D3BPO4</th>\n",
       "      <th>D4A</th>\n",
       "      <th>D4B025</th>\n",
       "      <th>D4B050</th>\n",
       "      <th>D4C</th>\n",
       "      <th>D4D</th>\n",
       "      <th>D4E</th>\n",
       "      <th>D5AR</th>\n",
       "      <th>D5AE</th>\n",
       "      <th>D5BR</th>\n",
       "      <th>D5BE</th>\n",
       "      <th>D5CR</th>\n",
       "      <th>D5CRI</th>\n",
       "      <th>D5CE</th>\n",
       "      <th>D5CEI</th>\n",
       "      <th>D5DR</th>\n",
       "      <th>D5DRI</th>\n",
       "      <th>D5DE</th>\n",
       "      <th>D5DEI</th>\n",
       "      <th>D2A_Ranked</th>\n",
       "      <th>D2B_Ranked</th>\n",
       "      <th>D3B_Ranked</th>\n",
       "      <th>D4A_Ranked</th>\n",
       "      <th>NatWalkInd</th>\n",
       "      <th>Shape_Length</th>\n",
       "      <th>Shape_Area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>914</th>\n",
       "      <td>3130 Pacific Ave</td>\n",
       "      <td>20.19</td>\n",
       "      <td>82.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>12.77</td>\n",
       "      <td>60750601001</td>\n",
       "      <td>6</td>\n",
       "      <td>75</td>\n",
       "      <td>60100</td>\n",
       "      <td>1</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>6529.125277</td>\n",
       "      <td>5019.63289</td>\n",
       "      <td>1509.492387</td>\n",
       "      <td>6.436060</td>\n",
       "      <td>4119</td>\n",
       "      <td>1343.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>0.715</td>\n",
       "      <td>0.027840</td>\n",
       "      <td>0.468774</td>\n",
       "      <td>0.503386</td>\n",
       "      <td>1782</td>\n",
       "      <td>226</td>\n",
       "      <td>280</td>\n",
       "      <td>1276</td>\n",
       "      <td>0.126824</td>\n",
       "      <td>5430</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>2209</td>\n",
       "      <td>454</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>1782</td>\n",
       "      <td>454</td>\n",
       "      <td>235</td>\n",
       "      <td>192</td>\n",
       "      <td>0</td>\n",
       "      <td>581</td>\n",
       "      <td>754</td>\n",
       "      <td>4095</td>\n",
       "      <td>0.106998</td>\n",
       "      <td>0.889703</td>\n",
       "      <td>2.728732</td>\n",
       "      <td>3.597236</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.463406</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.180529</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.155681</td>\n",
       "      <td>0.127195</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.486939</td>\n",
       "      <td>1</td>\n",
       "      <td>4.085779</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.807291</td>\n",
       "      <td>0.755450</td>\n",
       "      <td>0.867187</td>\n",
       "      <td>0.673537</td>\n",
       "      <td>0.721143</td>\n",
       "      <td>0.425806</td>\n",
       "      <td>0.862708</td>\n",
       "      <td>0.494176</td>\n",
       "      <td>0.328177</td>\n",
       "      <td>0.510776</td>\n",
       "      <td>33.518770</td>\n",
       "      <td>4.248306</td>\n",
       "      <td>2.088651</td>\n",
       "      <td>27.181814</td>\n",
       "      <td>236.247048</td>\n",
       "      <td>5.087803</td>\n",
       "      <td>18.655278</td>\n",
       "      <td>5.935770</td>\n",
       "      <td>245.910482</td>\n",
       "      <td>53.845916</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.33</td>\n",
       "      <td>18.371209</td>\n",
       "      <td>0.01052</td>\n",
       "      <td>87797</td>\n",
       "      <td>68894</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>2.596770e-04</td>\n",
       "      <td>0.316345</td>\n",
       "      <td>2.471990e-04</td>\n",
       "      <td>0.350401</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>25173.38839</td>\n",
       "      <td>2.642301e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>917</th>\n",
       "      <td>Cow Hollow School</td>\n",
       "      <td>24.09</td>\n",
       "      <td>85.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>15.07</td>\n",
       "      <td>60750601001</td>\n",
       "      <td>6</td>\n",
       "      <td>75</td>\n",
       "      <td>60100</td>\n",
       "      <td>1</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>6529.125277</td>\n",
       "      <td>5019.63289</td>\n",
       "      <td>1509.492387</td>\n",
       "      <td>6.436060</td>\n",
       "      <td>4119</td>\n",
       "      <td>1343.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>0.715</td>\n",
       "      <td>0.027840</td>\n",
       "      <td>0.468774</td>\n",
       "      <td>0.503386</td>\n",
       "      <td>1782</td>\n",
       "      <td>226</td>\n",
       "      <td>280</td>\n",
       "      <td>1276</td>\n",
       "      <td>0.126824</td>\n",
       "      <td>5430</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>2209</td>\n",
       "      <td>454</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>1782</td>\n",
       "      <td>454</td>\n",
       "      <td>235</td>\n",
       "      <td>192</td>\n",
       "      <td>0</td>\n",
       "      <td>581</td>\n",
       "      <td>754</td>\n",
       "      <td>4095</td>\n",
       "      <td>0.106998</td>\n",
       "      <td>0.889703</td>\n",
       "      <td>2.728732</td>\n",
       "      <td>3.597236</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.463406</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.180529</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.155681</td>\n",
       "      <td>0.127195</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.486939</td>\n",
       "      <td>1</td>\n",
       "      <td>4.085779</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.807291</td>\n",
       "      <td>0.755450</td>\n",
       "      <td>0.867187</td>\n",
       "      <td>0.673537</td>\n",
       "      <td>0.721143</td>\n",
       "      <td>0.425806</td>\n",
       "      <td>0.862708</td>\n",
       "      <td>0.494176</td>\n",
       "      <td>0.328177</td>\n",
       "      <td>0.510776</td>\n",
       "      <td>33.518770</td>\n",
       "      <td>4.248306</td>\n",
       "      <td>2.088651</td>\n",
       "      <td>27.181814</td>\n",
       "      <td>236.247048</td>\n",
       "      <td>5.087803</td>\n",
       "      <td>18.655278</td>\n",
       "      <td>5.935770</td>\n",
       "      <td>245.910482</td>\n",
       "      <td>53.845916</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.33</td>\n",
       "      <td>18.371209</td>\n",
       "      <td>0.01052</td>\n",
       "      <td>87797</td>\n",
       "      <td>68894</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>2.596770e-04</td>\n",
       "      <td>0.316345</td>\n",
       "      <td>2.471990e-04</td>\n",
       "      <td>0.350401</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>25173.38839</td>\n",
       "      <td>2.642301e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>920</th>\n",
       "      <td>Playgroup Preschool</td>\n",
       "      <td>30.33</td>\n",
       "      <td>73.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>17.04</td>\n",
       "      <td>60750601001</td>\n",
       "      <td>6</td>\n",
       "      <td>75</td>\n",
       "      <td>60100</td>\n",
       "      <td>1</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>6529.125277</td>\n",
       "      <td>5019.63289</td>\n",
       "      <td>1509.492387</td>\n",
       "      <td>6.436060</td>\n",
       "      <td>4119</td>\n",
       "      <td>1343.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>0.715</td>\n",
       "      <td>0.027840</td>\n",
       "      <td>0.468774</td>\n",
       "      <td>0.503386</td>\n",
       "      <td>1782</td>\n",
       "      <td>226</td>\n",
       "      <td>280</td>\n",
       "      <td>1276</td>\n",
       "      <td>0.126824</td>\n",
       "      <td>5430</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>2209</td>\n",
       "      <td>454</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>1782</td>\n",
       "      <td>454</td>\n",
       "      <td>235</td>\n",
       "      <td>192</td>\n",
       "      <td>0</td>\n",
       "      <td>581</td>\n",
       "      <td>754</td>\n",
       "      <td>4095</td>\n",
       "      <td>0.106998</td>\n",
       "      <td>0.889703</td>\n",
       "      <td>2.728732</td>\n",
       "      <td>3.597236</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.463406</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.180529</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.155681</td>\n",
       "      <td>0.127195</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.486939</td>\n",
       "      <td>1</td>\n",
       "      <td>4.085779</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.807291</td>\n",
       "      <td>0.755450</td>\n",
       "      <td>0.867187</td>\n",
       "      <td>0.673537</td>\n",
       "      <td>0.721143</td>\n",
       "      <td>0.425806</td>\n",
       "      <td>0.862708</td>\n",
       "      <td>0.494176</td>\n",
       "      <td>0.328177</td>\n",
       "      <td>0.510776</td>\n",
       "      <td>33.518770</td>\n",
       "      <td>4.248306</td>\n",
       "      <td>2.088651</td>\n",
       "      <td>27.181814</td>\n",
       "      <td>236.247048</td>\n",
       "      <td>5.087803</td>\n",
       "      <td>18.655278</td>\n",
       "      <td>5.935770</td>\n",
       "      <td>245.910482</td>\n",
       "      <td>53.845916</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.33</td>\n",
       "      <td>18.371209</td>\n",
       "      <td>0.01052</td>\n",
       "      <td>87797</td>\n",
       "      <td>68894</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>2.596770e-04</td>\n",
       "      <td>0.316345</td>\n",
       "      <td>2.471990e-04</td>\n",
       "      <td>0.350401</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>25173.38839</td>\n",
       "      <td>2.642301e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>922</th>\n",
       "      <td>Presidio: West Washington</td>\n",
       "      <td>22.22</td>\n",
       "      <td>73.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>14.25</td>\n",
       "      <td>60750601001</td>\n",
       "      <td>6</td>\n",
       "      <td>75</td>\n",
       "      <td>60100</td>\n",
       "      <td>1</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>6529.125277</td>\n",
       "      <td>5019.63289</td>\n",
       "      <td>1509.492387</td>\n",
       "      <td>6.436060</td>\n",
       "      <td>4119</td>\n",
       "      <td>1343.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>0.715</td>\n",
       "      <td>0.027840</td>\n",
       "      <td>0.468774</td>\n",
       "      <td>0.503386</td>\n",
       "      <td>1782</td>\n",
       "      <td>226</td>\n",
       "      <td>280</td>\n",
       "      <td>1276</td>\n",
       "      <td>0.126824</td>\n",
       "      <td>5430</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>2209</td>\n",
       "      <td>454</td>\n",
       "      <td>225</td>\n",
       "      <td>1939</td>\n",
       "      <td>603</td>\n",
       "      <td>1782</td>\n",
       "      <td>454</td>\n",
       "      <td>235</td>\n",
       "      <td>192</td>\n",
       "      <td>0</td>\n",
       "      <td>581</td>\n",
       "      <td>754</td>\n",
       "      <td>4095</td>\n",
       "      <td>0.106998</td>\n",
       "      <td>0.889703</td>\n",
       "      <td>2.728732</td>\n",
       "      <td>3.597236</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.463406</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.149057</td>\n",
       "      <td>1.284538</td>\n",
       "      <td>0.399472</td>\n",
       "      <td>1.180529</td>\n",
       "      <td>0.300763</td>\n",
       "      <td>0.155681</td>\n",
       "      <td>0.127195</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.486939</td>\n",
       "      <td>1</td>\n",
       "      <td>4.085779</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.818343</td>\n",
       "      <td>0.807291</td>\n",
       "      <td>0.755450</td>\n",
       "      <td>0.867187</td>\n",
       "      <td>0.673537</td>\n",
       "      <td>0.721143</td>\n",
       "      <td>0.425806</td>\n",
       "      <td>0.862708</td>\n",
       "      <td>0.494176</td>\n",
       "      <td>0.328177</td>\n",
       "      <td>0.510776</td>\n",
       "      <td>33.518770</td>\n",
       "      <td>4.248306</td>\n",
       "      <td>2.088651</td>\n",
       "      <td>27.181814</td>\n",
       "      <td>236.247048</td>\n",
       "      <td>5.087803</td>\n",
       "      <td>18.655278</td>\n",
       "      <td>5.935770</td>\n",
       "      <td>245.910482</td>\n",
       "      <td>53.845916</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.33</td>\n",
       "      <td>18.371209</td>\n",
       "      <td>0.01052</td>\n",
       "      <td>87797</td>\n",
       "      <td>68894</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>2.596770e-04</td>\n",
       "      <td>0.316345</td>\n",
       "      <td>2.471990e-04</td>\n",
       "      <td>0.350401</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>25173.38839</td>\n",
       "      <td>2.642301e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2847</th>\n",
       "      <td>Bear Valley Visitor Center</td>\n",
       "      <td>11.23</td>\n",
       "      <td>79.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>2.62</td>\n",
       "      <td>60411322003</td>\n",
       "      <td>6</td>\n",
       "      <td>41</td>\n",
       "      <td>132200</td>\n",
       "      <td>3</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>84174.874210</td>\n",
       "      <td>13596.53814</td>\n",
       "      <td>70578.336070</td>\n",
       "      <td>234.810310</td>\n",
       "      <td>689</td>\n",
       "      <td>330.0</td>\n",
       "      <td>285.0</td>\n",
       "      <td>0.707</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.221053</td>\n",
       "      <td>0.726316</td>\n",
       "      <td>135</td>\n",
       "      <td>28</td>\n",
       "      <td>58</td>\n",
       "      <td>49</td>\n",
       "      <td>0.207407</td>\n",
       "      <td>182</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>57</td>\n",
       "      <td>48</td>\n",
       "      <td>64</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>57</td>\n",
       "      <td>45</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "      <td>61</td>\n",
       "      <td>0.252747</td>\n",
       "      <td>0.004676</td>\n",
       "      <td>0.009762</td>\n",
       "      <td>0.002579</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>0.000808</td>\n",
       "      <td>0.000680</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>0.000808</td>\n",
       "      <td>0.000638</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.007254</td>\n",
       "      <td>1</td>\n",
       "      <td>0.638596</td>\n",
       "      <td>0.819365</td>\n",
       "      <td>0.819365</td>\n",
       "      <td>0.770402</td>\n",
       "      <td>0.663820</td>\n",
       "      <td>0.659997</td>\n",
       "      <td>0.666543</td>\n",
       "      <td>0.704310</td>\n",
       "      <td>0.739730</td>\n",
       "      <td>0.417910</td>\n",
       "      <td>0.851735</td>\n",
       "      <td>0.741758</td>\n",
       "      <td>0.772408</td>\n",
       "      <td>2.458112</td>\n",
       "      <td>0.069496</td>\n",
       "      <td>0.386722</td>\n",
       "      <td>2.001893</td>\n",
       "      <td>1.914151</td>\n",
       "      <td>0.054408</td>\n",
       "      <td>0.471533</td>\n",
       "      <td>0.063476</td>\n",
       "      <td>1.976811</td>\n",
       "      <td>0.217631</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.012060</td>\n",
       "      <td>0.00193</td>\n",
       "      <td>263</td>\n",
       "      <td>204</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>7.780000e-07</td>\n",
       "      <td>0.000948</td>\n",
       "      <td>7.320000e-07</td>\n",
       "      <td>0.001038</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5.833333</td>\n",
       "      <td>154552.23670</td>\n",
       "      <td>3.406511e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2848</th>\n",
       "      <td>Point Blue Palomarin Field Station</td>\n",
       "      <td>11.85</td>\n",
       "      <td>75.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>5.83</td>\n",
       "      <td>60411322003</td>\n",
       "      <td>6</td>\n",
       "      <td>41</td>\n",
       "      <td>132200</td>\n",
       "      <td>3</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>84174.874210</td>\n",
       "      <td>13596.53814</td>\n",
       "      <td>70578.336070</td>\n",
       "      <td>234.810310</td>\n",
       "      <td>689</td>\n",
       "      <td>330.0</td>\n",
       "      <td>285.0</td>\n",
       "      <td>0.707</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.221053</td>\n",
       "      <td>0.726316</td>\n",
       "      <td>135</td>\n",
       "      <td>28</td>\n",
       "      <td>58</td>\n",
       "      <td>49</td>\n",
       "      <td>0.207407</td>\n",
       "      <td>182</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>57</td>\n",
       "      <td>48</td>\n",
       "      <td>64</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>57</td>\n",
       "      <td>45</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "      <td>61</td>\n",
       "      <td>0.252747</td>\n",
       "      <td>0.004676</td>\n",
       "      <td>0.009762</td>\n",
       "      <td>0.002579</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>0.000808</td>\n",
       "      <td>0.000680</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>0.000808</td>\n",
       "      <td>0.000638</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.007254</td>\n",
       "      <td>1</td>\n",
       "      <td>0.638596</td>\n",
       "      <td>0.819365</td>\n",
       "      <td>0.819365</td>\n",
       "      <td>0.770402</td>\n",
       "      <td>0.663820</td>\n",
       "      <td>0.659997</td>\n",
       "      <td>0.666543</td>\n",
       "      <td>0.704310</td>\n",
       "      <td>0.739730</td>\n",
       "      <td>0.417910</td>\n",
       "      <td>0.851735</td>\n",
       "      <td>0.741758</td>\n",
       "      <td>0.772408</td>\n",
       "      <td>2.458112</td>\n",
       "      <td>0.069496</td>\n",
       "      <td>0.386722</td>\n",
       "      <td>2.001893</td>\n",
       "      <td>1.914151</td>\n",
       "      <td>0.054408</td>\n",
       "      <td>0.471533</td>\n",
       "      <td>0.063476</td>\n",
       "      <td>1.976811</td>\n",
       "      <td>0.217631</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.012060</td>\n",
       "      <td>0.00193</td>\n",
       "      <td>263</td>\n",
       "      <td>204</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>7.780000e-07</td>\n",
       "      <td>0.000948</td>\n",
       "      <td>7.320000e-07</td>\n",
       "      <td>0.001038</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5.833333</td>\n",
       "      <td>154552.23670</td>\n",
       "      <td>3.406511e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7408</th>\n",
       "      <td>Main Lodge Patrol</td>\n",
       "      <td>0.58</td>\n",
       "      <td>59.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>0.46</td>\n",
       "      <td>60510002009</td>\n",
       "      <td>6</td>\n",
       "      <td>51</td>\n",
       "      <td>200</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13632.046160</td>\n",
       "      <td>2.81101</td>\n",
       "      <td>13629.235150</td>\n",
       "      <td>6.021680</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>36</td>\n",
       "      <td>12</td>\n",
       "      <td>0.448276</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006383</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001394</td>\n",
       "      <td>0.004989</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004989</td>\n",
       "      <td>0.001394</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.006383</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.757218</td>\n",
       "      <td>0.326116</td>\n",
       "      <td>0.757218</td>\n",
       "      <td>0.252406</td>\n",
       "      <td>0.757218</td>\n",
       "      <td>0.252356</td>\n",
       "      <td>0.280944</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022989</td>\n",
       "      <td>0.376434</td>\n",
       "      <td>7.514797</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.579883</td>\n",
       "      <td>6.934914</td>\n",
       "      <td>20.184235</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.756630</td>\n",
       "      <td>0.422621</td>\n",
       "      <td>20.238847</td>\n",
       "      <td>3.756630</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.33</td>\n",
       "      <td>0.250286</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>283</td>\n",
       "      <td>89</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5.833333</td>\n",
       "      <td>40392.66479</td>\n",
       "      <td>5.516814e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7543</th>\n",
       "      <td>MDAQMD-LANDERS-BDVWA</td>\n",
       "      <td>0.00</td>\n",
       "      <td>89.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.38</td>\n",
       "      <td>60710104233</td>\n",
       "      <td>6</td>\n",
       "      <td>71</td>\n",
       "      <td>10423</td>\n",
       "      <td>3</td>\n",
       "      <td>348.0</td>\n",
       "      <td>Los Angeles-Long Beach, CA</td>\n",
       "      <td>40140.0</td>\n",
       "      <td>Riverside-San Bernardino-Ontario, CA</td>\n",
       "      <td>4518699</td>\n",
       "      <td>1439654</td>\n",
       "      <td>1749931</td>\n",
       "      <td>20521.493400</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>20521.493400</td>\n",
       "      <td>16.933852</td>\n",
       "      <td>778</td>\n",
       "      <td>574.0</td>\n",
       "      <td>417.0</td>\n",
       "      <td>0.703</td>\n",
       "      <td>0.055156</td>\n",
       "      <td>0.434053</td>\n",
       "      <td>0.510791</td>\n",
       "      <td>304</td>\n",
       "      <td>95</td>\n",
       "      <td>115</td>\n",
       "      <td>94</td>\n",
       "      <td>0.312500</td>\n",
       "      <td>57</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>0.508772</td>\n",
       "      <td>0.027971</td>\n",
       "      <td>0.037911</td>\n",
       "      <td>0.002778</td>\n",
       "      <td>0.000439</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000731</td>\n",
       "      <td>0.000780</td>\n",
       "      <td>0.000828</td>\n",
       "      <td>0.000439</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000731</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000828</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000780</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030748</td>\n",
       "      <td>1</td>\n",
       "      <td>0.136691</td>\n",
       "      <td>0.981186</td>\n",
       "      <td>0.845147</td>\n",
       "      <td>0.981186</td>\n",
       "      <td>0.654124</td>\n",
       "      <td>0.329928</td>\n",
       "      <td>0.451108</td>\n",
       "      <td>0.485175</td>\n",
       "      <td>0.116184</td>\n",
       "      <td>0.136527</td>\n",
       "      <td>0.315789</td>\n",
       "      <td>5.333333</td>\n",
       "      <td>0.013124</td>\n",
       "      <td>3.327867</td>\n",
       "      <td>0.421942</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.905926</td>\n",
       "      <td>7.070986</td>\n",
       "      <td>2.463758</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.925495</td>\n",
       "      <td>3.118681</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-99999.00</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.00000</td>\n",
       "      <td>285</td>\n",
       "      <td>927</td>\n",
       "      <td>-99999</td>\n",
       "      <td>-99999</td>\n",
       "      <td>2.210000e-06</td>\n",
       "      <td>0.001850</td>\n",
       "      <td>6.820000e-06</td>\n",
       "      <td>0.006479</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>43344.14759</td>\n",
       "      <td>8.304935e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    name  pm_2.5  temp_f  \\\n",
       "914                     3130 Pacific Ave   20.19    82.0   \n",
       "917                    Cow Hollow School   24.09    85.0   \n",
       "920                  Playgroup Preschool   30.33    73.0   \n",
       "922            Presidio: West Washington   22.22    73.0   \n",
       "2847          Bear Valley Visitor Center   11.23    79.0   \n",
       "2848  Point Blue Palomarin Field Station   11.85    75.0   \n",
       "7408                   Main Lodge Patrol    0.58    59.0   \n",
       "7543                MDAQMD-LANDERS-BDVWA    0.00    89.0   \n",
       "\n",
       "                       model  hidden  flagged  downgraded  age  is_owner  \\\n",
       "914   PMS5003+PMS5003+BME280   False    False       False    0     False   \n",
       "917   PMS5003+PMS5003+BME280   False    False       False    1     False   \n",
       "920   PMS5003+PMS5003+BME280   False    False       False    1     False   \n",
       "922   PMS5003+PMS5003+BME280   False    False       False    0     False   \n",
       "2847  PMS5003+PMS5003+BME280   False    False       False    0     False   \n",
       "2848  PMS5003+PMS5003+BME280   False    False       False    1     False   \n",
       "7408  PMS5003+PMS5003+BME280   False    False       False    1     False   \n",
       "7543  PMS5003+PMS5003+BME280   False    False       False    0     False   \n",
       "\n",
       "      1week_avg      fips_id  STATEFP  COUNTYFP  TRACTCE  BLKGRPCE    CSA  \\\n",
       "914       12.77  60750601001        6        75    60100         1  488.0   \n",
       "917       15.07  60750601001        6        75    60100         1  488.0   \n",
       "920       17.04  60750601001        6        75    60100         1  488.0   \n",
       "922       14.25  60750601001        6        75    60100         1  488.0   \n",
       "2847       2.62  60411322003        6        41   132200         3  488.0   \n",
       "2848       5.83  60411322003        6        41   132200         3  488.0   \n",
       "7408       0.46  60510002009        6        51      200         9    NaN   \n",
       "7543       0.38  60710104233        6        71    10423         3  348.0   \n",
       "\n",
       "                                CSA_Name     CBSA  \\\n",
       "914   San Jose-San Francisco-Oakland, CA  41860.0   \n",
       "917   San Jose-San Francisco-Oakland, CA  41860.0   \n",
       "920   San Jose-San Francisco-Oakland, CA  41860.0   \n",
       "922   San Jose-San Francisco-Oakland, CA  41860.0   \n",
       "2847  San Jose-San Francisco-Oakland, CA  41860.0   \n",
       "2848  San Jose-San Francisco-Oakland, CA  41860.0   \n",
       "7408                                 NaN      NaN   \n",
       "7543          Los Angeles-Long Beach, CA  40140.0   \n",
       "\n",
       "                                 CBSA_Name  CBSA_POP  CBSA_EMP  CBSA_WRK  \\\n",
       "914     San Francisco-Oakland-Berkeley, CA   4673221   2400290   2241034   \n",
       "917     San Francisco-Oakland-Berkeley, CA   4673221   2400290   2241034   \n",
       "920     San Francisco-Oakland-Berkeley, CA   4673221   2400290   2241034   \n",
       "922     San Francisco-Oakland-Berkeley, CA   4673221   2400290   2241034   \n",
       "2847    San Francisco-Oakland-Berkeley, CA   4673221   2400290   2241034   \n",
       "2848    San Francisco-Oakland-Berkeley, CA   4673221   2400290   2241034   \n",
       "7408                                   NaN         0         0         0   \n",
       "7543  Riverside-San Bernardino-Ontario, CA   4518699   1439654   1749931   \n",
       "\n",
       "          Ac_Total     Ac_Water       Ac_Land     Ac_Unpr  TotPop  CountHU  \\\n",
       "914    6529.125277   5019.63289   1509.492387    6.436060    4119   1343.0   \n",
       "917    6529.125277   5019.63289   1509.492387    6.436060    4119   1343.0   \n",
       "920    6529.125277   5019.63289   1509.492387    6.436060    4119   1343.0   \n",
       "922    6529.125277   5019.63289   1509.492387    6.436060    4119   1343.0   \n",
       "2847  84174.874210  13596.53814  70578.336070  234.810310     689    330.0   \n",
       "2848  84174.874210  13596.53814  70578.336070  234.810310     689    330.0   \n",
       "7408  13632.046160      2.81101  13629.235150    6.021680       0      0.0   \n",
       "7543  20521.493400      0.00000  20521.493400   16.933852     778    574.0   \n",
       "\n",
       "          HH  P_WrkAge   Pct_AO0   Pct_AO1  Pct_AO2p  Workers  R_LowWageWk  \\\n",
       "914   1329.0     0.715  0.027840  0.468774  0.503386     1782          226   \n",
       "917   1329.0     0.715  0.027840  0.468774  0.503386     1782          226   \n",
       "920   1329.0     0.715  0.027840  0.468774  0.503386     1782          226   \n",
       "922   1329.0     0.715  0.027840  0.468774  0.503386     1782          226   \n",
       "2847   285.0     0.707  0.052632  0.221053  0.726316      135           28   \n",
       "2848   285.0     0.707  0.052632  0.221053  0.726316      135           28   \n",
       "7408     0.0     0.000  0.000000  0.000000  0.000000        2            1   \n",
       "7543   417.0     0.703  0.055156  0.434053  0.510791      304           95   \n",
       "\n",
       "      R_MedWageWk  R_HiWageWk  R_PCTLOWWAGE  TotEmp  E5_Ret  E5_Off  E5_Ind  \\\n",
       "914           280        1276      0.126824    5430     225    1939     603   \n",
       "917           280        1276      0.126824    5430     225    1939     603   \n",
       "920           280        1276      0.126824    5430     225    1939     603   \n",
       "922           280        1276      0.126824    5430     225    1939     603   \n",
       "2847           58          49      0.207407     182       5       8      57   \n",
       "2848           58          49      0.207407     182       5       8      57   \n",
       "7408            1           0      0.500000      87       0       0       0   \n",
       "7543          115          94      0.312500      57       9       0      15   \n",
       "\n",
       "      E5_Svc  E5_Ent  E8_Ret  E8_off  E8_Ind  E8_Svc  E8_Ent  E8_Ed  E8_Hlth  \\\n",
       "914     2209     454     225    1939     603    1782     454    235      192   \n",
       "917     2209     454     225    1939     603    1782     454    235      192   \n",
       "920     2209     454     225    1939     603    1782     454    235      192   \n",
       "922     2209     454     225    1939     603    1782     454    235      192   \n",
       "2847      48      64       5       8      57      45      64      0        3   \n",
       "2848      48      64       5       8      57      45      64      0        3   \n",
       "7408      19      68       0       0       0       0      68     19        0   \n",
       "7543      16      17       9       0      15       0      17      0       16   \n",
       "\n",
       "      E8_Pub  E_LowWageWk  E_MedWageWk  E_HiWageWk  E_PctLowWage       D1A  \\\n",
       "914        0          581          754        4095      0.106998  0.889703   \n",
       "917        0          581          754        4095      0.106998  0.889703   \n",
       "920        0          581          754        4095      0.106998  0.889703   \n",
       "922        0          581          754        4095      0.106998  0.889703   \n",
       "2847       0           46           75          61      0.252747  0.004676   \n",
       "2848       0           46           75          61      0.252747  0.004676   \n",
       "7408       0           39           36          12      0.448276  0.000000   \n",
       "7543       0           29           19           9      0.508772  0.027971   \n",
       "\n",
       "           D1B       D1C  D1C5_RET  D1C5_OFF  D1C5_IND  D1C5_SVC  D1C5_ENT  \\\n",
       "914   2.728732  3.597236  0.149057  1.284538  0.399472  1.463406  0.300763   \n",
       "917   2.728732  3.597236  0.149057  1.284538  0.399472  1.463406  0.300763   \n",
       "920   2.728732  3.597236  0.149057  1.284538  0.399472  1.463406  0.300763   \n",
       "922   2.728732  3.597236  0.149057  1.284538  0.399472  1.463406  0.300763   \n",
       "2847  0.009762  0.002579  0.000071  0.000113  0.000808  0.000680  0.000907   \n",
       "2848  0.009762  0.002579  0.000071  0.000113  0.000808  0.000680  0.000907   \n",
       "7408  0.000000  0.006383  0.000000  0.000000  0.000000  0.001394  0.004989   \n",
       "7543  0.037911  0.002778  0.000439  0.000000  0.000731  0.000780  0.000828   \n",
       "\n",
       "      D1C8_RET  D1C8_OFF  D1C8_IND  D1C8_SVC  D1C8_ENT   D1C8_ED  D1C8_HLTH  \\\n",
       "914   0.149057  1.284538  0.399472  1.180529  0.300763  0.155681   0.127195   \n",
       "917   0.149057  1.284538  0.399472  1.180529  0.300763  0.155681   0.127195   \n",
       "920   0.149057  1.284538  0.399472  1.180529  0.300763  0.155681   0.127195   \n",
       "922   0.149057  1.284538  0.399472  1.180529  0.300763  0.155681   0.127195   \n",
       "2847  0.000071  0.000113  0.000808  0.000638  0.000907  0.000000   0.000043   \n",
       "2848  0.000071  0.000113  0.000808  0.000638  0.000907  0.000000   0.000043   \n",
       "7408  0.000000  0.000000  0.000000  0.000000  0.004989  0.001394   0.000000   \n",
       "7543  0.000439  0.000000  0.000731  0.000000  0.000828  0.000000   0.000780   \n",
       "\n",
       "      D1C8_PUB       D1D  D1_FLAG  D2A_JPHH  D2B_E5MIX  D2B_E5MIXA  D2B_E8MIX  \\\n",
       "914        0.0  4.486939        1  4.085779   0.818343    0.818343   0.807291   \n",
       "917        0.0  4.486939        1  4.085779   0.818343    0.818343   0.807291   \n",
       "920        0.0  4.486939        1  4.085779   0.818343    0.818343   0.807291   \n",
       "922        0.0  4.486939        1  4.085779   0.818343    0.818343   0.807291   \n",
       "2847       0.0  0.007254        1  0.638596   0.819365    0.819365   0.770402   \n",
       "2848       0.0  0.007254        1  0.638596   0.819365    0.819365   0.770402   \n",
       "7408       0.0  0.006383        1  0.000000   0.757218    0.326116   0.757218   \n",
       "7543       0.0  0.030748        1  0.136691   0.981186    0.845147   0.981186   \n",
       "\n",
       "      D2B_E8MIXA  D2A_EPHHM  D2C_TRPMX1  D2C_TRPMX2  D2C_TRIPEQ  D2R_JOBPOP  \\\n",
       "914     0.755450   0.867187    0.673537    0.721143    0.425806    0.862708   \n",
       "917     0.755450   0.867187    0.673537    0.721143    0.425806    0.862708   \n",
       "920     0.755450   0.867187    0.673537    0.721143    0.425806    0.862708   \n",
       "922     0.755450   0.867187    0.673537    0.721143    0.425806    0.862708   \n",
       "2847    0.663820   0.659997    0.666543    0.704310    0.739730    0.417910   \n",
       "2848    0.663820   0.659997    0.666543    0.704310    0.739730    0.417910   \n",
       "7408    0.252406   0.757218    0.252356    0.280944    0.367879    0.000000   \n",
       "7543    0.654124   0.329928    0.451108    0.485175    0.116184    0.136527   \n",
       "\n",
       "      D2R_WRKEMP  D2A_WRKEMP  D2C_WREMLX        D3A     D3AAO     D3AMM  \\\n",
       "914     0.494176    0.328177    0.510776  33.518770  4.248306  2.088651   \n",
       "917     0.494176    0.328177    0.510776  33.518770  4.248306  2.088651   \n",
       "920     0.494176    0.328177    0.510776  33.518770  4.248306  2.088651   \n",
       "922     0.494176    0.328177    0.510776  33.518770  4.248306  2.088651   \n",
       "2847    0.851735    0.741758    0.772408   2.458112  0.069496  0.386722   \n",
       "2848    0.851735    0.741758    0.772408   2.458112  0.069496  0.386722   \n",
       "7408    0.000000    0.022989    0.376434   7.514797  0.000000  0.579883   \n",
       "7543    0.315789    5.333333    0.013124   3.327867  0.421942  0.000000   \n",
       "\n",
       "          D3APO         D3B     D3BAO     D3BMM3    D3BMM4      D3BPO3  \\\n",
       "914   27.181814  236.247048  5.087803  18.655278  5.935770  245.910482   \n",
       "917   27.181814  236.247048  5.087803  18.655278  5.935770  245.910482   \n",
       "920   27.181814  236.247048  5.087803  18.655278  5.935770  245.910482   \n",
       "922   27.181814  236.247048  5.087803  18.655278  5.935770  245.910482   \n",
       "2847   2.001893    1.914151  0.054408   0.471533  0.063476    1.976811   \n",
       "2848   2.001893    1.914151  0.054408   0.471533  0.063476    1.976811   \n",
       "7408   6.934914   20.184235  0.000000   3.756630  0.422621   20.238847   \n",
       "7543   2.905926    7.070986  2.463758   0.000000  0.000000    5.925495   \n",
       "\n",
       "         D3BPO4      D4A  D4B025  D4B050       D4C           D4D          D4E  \\\n",
       "914   53.845916 -99999.0     0.0     0.0     43.33     18.371209      0.01052   \n",
       "917   53.845916 -99999.0     0.0     0.0     43.33     18.371209      0.01052   \n",
       "920   53.845916 -99999.0     0.0     0.0     43.33     18.371209      0.01052   \n",
       "922   53.845916 -99999.0     0.0     0.0     43.33     18.371209      0.01052   \n",
       "2847   0.217631 -99999.0     0.0     0.0      1.33      0.012060      0.00193   \n",
       "2848   0.217631 -99999.0     0.0     0.0      1.33      0.012060      0.00193   \n",
       "7408   3.756630 -99999.0     0.0     0.0      5.33      0.250286      0.00000   \n",
       "7543   3.118681 -99999.0     0.0     0.0 -99999.00 -99999.000000 -99999.00000   \n",
       "\n",
       "       D5AR   D5AE   D5BR   D5BE          D5CR     D5CRI          D5CE  \\\n",
       "914   87797  68894 -99999 -99999  2.596770e-04  0.316345  2.471990e-04   \n",
       "917   87797  68894 -99999 -99999  2.596770e-04  0.316345  2.471990e-04   \n",
       "920   87797  68894 -99999 -99999  2.596770e-04  0.316345  2.471990e-04   \n",
       "922   87797  68894 -99999 -99999  2.596770e-04  0.316345  2.471990e-04   \n",
       "2847    263    204 -99999 -99999  7.780000e-07  0.000948  7.320000e-07   \n",
       "2848    263    204 -99999 -99999  7.780000e-07  0.000948  7.320000e-07   \n",
       "7408    283     89 -99999 -99999  0.000000e+00  0.000000  0.000000e+00   \n",
       "7543    285    927 -99999 -99999  2.210000e-06  0.001850  6.820000e-06   \n",
       "\n",
       "         D5CEI     D5DR    D5DRI     D5DE    D5DEI  D2A_Ranked  D2B_Ranked  \\\n",
       "914   0.350401 -99999.0 -99999.0 -99999.0 -99999.0          20          18   \n",
       "917   0.350401 -99999.0 -99999.0 -99999.0 -99999.0          20          18   \n",
       "920   0.350401 -99999.0 -99999.0 -99999.0 -99999.0          20          18   \n",
       "922   0.350401 -99999.0 -99999.0 -99999.0 -99999.0          20          18   \n",
       "2847  0.001038 -99999.0 -99999.0 -99999.0 -99999.0          15          14   \n",
       "2848  0.001038 -99999.0 -99999.0 -99999.0 -99999.0          15          14   \n",
       "7408  0.000000 -99999.0 -99999.0 -99999.0 -99999.0          18           3   \n",
       "7543  0.006479 -99999.0 -99999.0 -99999.0 -99999.0           6          14   \n",
       "\n",
       "      D3B_Ranked  D4A_Ranked  NatWalkInd  Shape_Length    Shape_Area  \n",
       "914           20           1   13.333333   25173.38839  2.642301e+07  \n",
       "917           20           1   13.333333   25173.38839  2.642301e+07  \n",
       "920           20           1   13.333333   25173.38839  2.642301e+07  \n",
       "922           20           1   13.333333   25173.38839  2.642301e+07  \n",
       "2847           2           1    5.833333  154552.23670  3.406511e+08  \n",
       "2848           2           1    5.833333  154552.23670  3.406511e+08  \n",
       "7408           6           1    5.833333   40392.66479  5.516814e+07  \n",
       "7543           4           1    5.000000   43344.14759  8.304935e+07  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with pd.option_context('display.max_columns', 200):\n",
    "    display(df1.query('D1_FLAG == 1'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.drop(columns='D1_FLAG', inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Walkability Describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>E5_Ret</th>\n",
       "      <th>E5_Off</th>\n",
       "      <th>E5_Ind</th>\n",
       "      <th>E5_Svc</th>\n",
       "      <th>E5_Ent</th>\n",
       "      <th>E8_Ret</th>\n",
       "      <th>E8_off</th>\n",
       "      <th>E8_Ind</th>\n",
       "      <th>E8_Svc</th>\n",
       "      <th>E8_Ent</th>\n",
       "      <th>E8_Ed</th>\n",
       "      <th>E8_Hlth</th>\n",
       "      <th>E8_Pub</th>\n",
       "      <th>E_LowWageWk</th>\n",
       "      <th>E_MedWageWk</th>\n",
       "      <th>E_HiWageWk</th>\n",
       "      <th>E_PctLowWage</th>\n",
       "      <th>D1A</th>\n",
       "      <th>D1B</th>\n",
       "      <th>D1C</th>\n",
       "      <th>D1C5_RET</th>\n",
       "      <th>D1C5_OFF</th>\n",
       "      <th>D1C5_IND</th>\n",
       "      <th>D1C5_SVC</th>\n",
       "      <th>D1C5_ENT</th>\n",
       "      <th>D1C8_RET</th>\n",
       "      <th>D1C8_OFF</th>\n",
       "      <th>D1C8_IND</th>\n",
       "      <th>D1C8_SVC</th>\n",
       "      <th>D1C8_ENT</th>\n",
       "      <th>D1C8_ED</th>\n",
       "      <th>D1C8_HLTH</th>\n",
       "      <th>D1C8_PUB</th>\n",
       "      <th>D1D</th>\n",
       "      <th>D1_FLAG</th>\n",
       "      <th>D2A_JPHH</th>\n",
       "      <th>D2B_E5MIX</th>\n",
       "      <th>D2B_E5MIXA</th>\n",
       "      <th>D2B_E8MIX</th>\n",
       "      <th>D2B_E8MIXA</th>\n",
       "      <th>D2A_EPHHM</th>\n",
       "      <th>D2C_TRPMX1</th>\n",
       "      <th>D2C_TRPMX2</th>\n",
       "      <th>D2C_TRIPEQ</th>\n",
       "      <th>D2R_JOBPOP</th>\n",
       "      <th>D2R_WRKEMP</th>\n",
       "      <th>D2A_WRKEMP</th>\n",
       "      <th>D2C_WREMLX</th>\n",
       "      <th>D3A</th>\n",
       "      <th>D3AAO</th>\n",
       "      <th>D3AMM</th>\n",
       "      <th>D3APO</th>\n",
       "      <th>D3B</th>\n",
       "      <th>D3BAO</th>\n",
       "      <th>D3BMM3</th>\n",
       "      <th>D3BMM4</th>\n",
       "      <th>D3BPO3</th>\n",
       "      <th>D3BPO4</th>\n",
       "      <th>D4A</th>\n",
       "      <th>D4B025</th>\n",
       "      <th>D4B050</th>\n",
       "      <th>D4C</th>\n",
       "      <th>D4D</th>\n",
       "      <th>D4E</th>\n",
       "      <th>D5AR</th>\n",
       "      <th>D5AE</th>\n",
       "      <th>D5BR</th>\n",
       "      <th>D5BE</th>\n",
       "      <th>D5CR</th>\n",
       "      <th>D5CRI</th>\n",
       "      <th>D5CE</th>\n",
       "      <th>D5CEI</th>\n",
       "      <th>D5DR</th>\n",
       "      <th>D5DRI</th>\n",
       "      <th>D5DE</th>\n",
       "      <th>D5DEI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
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       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6.568000e+03</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>65.918240</td>\n",
       "      <td>146.455542</td>\n",
       "      <td>251.846224</td>\n",
       "      <td>427.172655</td>\n",
       "      <td>112.593788</td>\n",
       "      <td>65.918240</td>\n",
       "      <td>105.945646</td>\n",
       "      <td>251.846224</td>\n",
       "      <td>201.356121</td>\n",
       "      <td>112.593788</td>\n",
       "      <td>120.724726</td>\n",
       "      <td>105.091809</td>\n",
       "      <td>40.509896</td>\n",
       "      <td>172.826127</td>\n",
       "      <td>257.829019</td>\n",
       "      <td>573.331303</td>\n",
       "      <td>0.269691</td>\n",
       "      <td>3.398548</td>\n",
       "      <td>8.012142</td>\n",
       "      <td>3.582072</td>\n",
       "      <td>0.260527</td>\n",
       "      <td>0.719655</td>\n",
       "      <td>0.378950</td>\n",
       "      <td>1.750091</td>\n",
       "      <td>0.472849</td>\n",
       "      <td>0.260527</td>\n",
       "      <td>0.377378</td>\n",
       "      <td>0.378950</td>\n",
       "      <td>0.729900</td>\n",
       "      <td>0.472849</td>\n",
       "      <td>0.450346</td>\n",
       "      <td>0.569844</td>\n",
       "      <td>0.342278</td>\n",
       "      <td>6.980620</td>\n",
       "      <td>0.001218</td>\n",
       "      <td>2.492406</td>\n",
       "      <td>0.651673</td>\n",
       "      <td>0.586945</td>\n",
       "      <td>0.716324</td>\n",
       "      <td>0.606824</td>\n",
       "      <td>0.525778</td>\n",
       "      <td>0.509411</td>\n",
       "      <td>0.540602</td>\n",
       "      <td>0.466786</td>\n",
       "      <td>0.346393</td>\n",
       "      <td>0.473834</td>\n",
       "      <td>4.775469</td>\n",
       "      <td>0.320303</td>\n",
       "      <td>15.805488</td>\n",
       "      <td>0.962671</td>\n",
       "      <td>2.081332</td>\n",
       "      <td>12.761485</td>\n",
       "      <td>80.896852</td>\n",
       "      <td>2.236382</td>\n",
       "      <td>9.932338</td>\n",
       "      <td>5.865437</td>\n",
       "      <td>69.294921</td>\n",
       "      <td>22.186833</td>\n",
       "      <td>-47503.406956</td>\n",
       "      <td>0.032314</td>\n",
       "      <td>0.080674</td>\n",
       "      <td>-34981.573301</td>\n",
       "      <td>-34944.232667</td>\n",
       "      <td>-34987.463492</td>\n",
       "      <td>79087.569732</td>\n",
       "      <td>66814.646620</td>\n",
       "      <td>2.296478e+04</td>\n",
       "      <td>-3672.963916</td>\n",
       "      <td>0.001998</td>\n",
       "      <td>0.370175</td>\n",
       "      <td>0.001948</td>\n",
       "      <td>0.407187</td>\n",
       "      <td>-47761.396512</td>\n",
       "      <td>-47761.285836</td>\n",
       "      <td>-47761.396565</td>\n",
       "      <td>-47761.277078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>226.805167</td>\n",
       "      <td>954.386529</td>\n",
       "      <td>1485.914713</td>\n",
       "      <td>1717.705386</td>\n",
       "      <td>292.486773</td>\n",
       "      <td>226.805167</td>\n",
       "      <td>811.822138</td>\n",
       "      <td>1485.914713</td>\n",
       "      <td>1082.782120</td>\n",
       "      <td>292.486773</td>\n",
       "      <td>735.832511</td>\n",
       "      <td>498.665116</td>\n",
       "      <td>387.861605</td>\n",
       "      <td>452.605201</td>\n",
       "      <td>778.688304</td>\n",
       "      <td>2751.740828</td>\n",
       "      <td>0.124850</td>\n",
       "      <td>5.327989</td>\n",
       "      <td>11.175842</td>\n",
       "      <td>14.063405</td>\n",
       "      <td>0.833661</td>\n",
       "      <td>5.588315</td>\n",
       "      <td>2.222663</td>\n",
       "      <td>8.071074</td>\n",
       "      <td>1.740141</td>\n",
       "      <td>0.833661</td>\n",
       "      <td>3.568290</td>\n",
       "      <td>2.222663</td>\n",
       "      <td>4.589154</td>\n",
       "      <td>1.740141</td>\n",
       "      <td>2.877023</td>\n",
       "      <td>3.373873</td>\n",
       "      <td>4.077830</td>\n",
       "      <td>16.364305</td>\n",
       "      <td>0.034882</td>\n",
       "      <td>23.301847</td>\n",
       "      <td>0.217217</td>\n",
       "      <td>0.224334</td>\n",
       "      <td>0.182274</td>\n",
       "      <td>0.181047</td>\n",
       "      <td>0.194984</td>\n",
       "      <td>0.174006</td>\n",
       "      <td>0.188160</td>\n",
       "      <td>0.282745</td>\n",
       "      <td>0.271953</td>\n",
       "      <td>0.280552</td>\n",
       "      <td>8.249127</td>\n",
       "      <td>0.315073</td>\n",
       "      <td>10.892324</td>\n",
       "      <td>2.230362</td>\n",
       "      <td>2.711260</td>\n",
       "      <td>9.292966</td>\n",
       "      <td>88.241150</td>\n",
       "      <td>7.576800</td>\n",
       "      <td>16.558875</td>\n",
       "      <td>13.073227</td>\n",
       "      <td>82.108396</td>\n",
       "      <td>37.976761</td>\n",
       "      <td>50200.373108</td>\n",
       "      <td>0.142689</td>\n",
       "      <td>0.235226</td>\n",
       "      <td>47700.609816</td>\n",
       "      <td>47728.252319</td>\n",
       "      <td>47696.286678</td>\n",
       "      <td>87917.731987</td>\n",
       "      <td>72466.561323</td>\n",
       "      <td>1.726296e+05</td>\n",
       "      <td>117793.744412</td>\n",
       "      <td>0.005823</td>\n",
       "      <td>0.251057</td>\n",
       "      <td>0.005366</td>\n",
       "      <td>0.258548</td>\n",
       "      <td>49953.187857</td>\n",
       "      <td>49953.293693</td>\n",
       "      <td>49953.187806</td>\n",
       "      <td>49953.302068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000699</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.201734</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.033017</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>-9.999900e+04</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>0.182713</td>\n",
       "      <td>0.324743</td>\n",
       "      <td>0.704303</td>\n",
       "      <td>0.128184</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001143</td>\n",
       "      <td>0.010918</td>\n",
       "      <td>0.043457</td>\n",
       "      <td>0.000622</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000678</td>\n",
       "      <td>0.010918</td>\n",
       "      <td>0.012313</td>\n",
       "      <td>0.000622</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005791</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.611305</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.208042</td>\n",
       "      <td>0.517664</td>\n",
       "      <td>0.433108</td>\n",
       "      <td>0.635228</td>\n",
       "      <td>0.498076</td>\n",
       "      <td>0.380408</td>\n",
       "      <td>0.386540</td>\n",
       "      <td>0.408399</td>\n",
       "      <td>0.258097</td>\n",
       "      <td>0.127204</td>\n",
       "      <td>0.239042</td>\n",
       "      <td>0.903226</td>\n",
       "      <td>0.009342</td>\n",
       "      <td>5.226973</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.296585</td>\n",
       "      <td>3.804942</td>\n",
       "      <td>11.309733</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.348963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.540670</td>\n",
       "      <td>0.783275</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>12225.000000</td>\n",
       "      <td>12555.000000</td>\n",
       "      <td>-9.999900e+04</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.163719</td>\n",
       "      <td>0.000164</td>\n",
       "      <td>0.196729</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "      <td>-99999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>0.253113</td>\n",
       "      <td>1.964285</td>\n",
       "      <td>4.699322</td>\n",
       "      <td>0.625745</td>\n",
       "      <td>0.008530</td>\n",
       "      <td>0.017539</td>\n",
       "      <td>0.052960</td>\n",
       "      <td>0.294056</td>\n",
       "      <td>0.032065</td>\n",
       "      <td>0.008530</td>\n",
       "      <td>0.015112</td>\n",
       "      <td>0.052960</td>\n",
       "      <td>0.084606</td>\n",
       "      <td>0.032065</td>\n",
       "      <td>0.004866</td>\n",
       "      <td>0.058395</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.180697</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.464286</td>\n",
       "      <td>0.699363</td>\n",
       "      <td>0.618558</td>\n",
       "      <td>0.764205</td>\n",
       "      <td>0.639104</td>\n",
       "      <td>0.525528</td>\n",
       "      <td>0.519455</td>\n",
       "      <td>0.549969</td>\n",
       "      <td>0.473379</td>\n",
       "      <td>0.268247</td>\n",
       "      <td>0.448578</td>\n",
       "      <td>2.451378</td>\n",
       "      <td>0.233400</td>\n",
       "      <td>15.719917</td>\n",
       "      <td>0.043947</td>\n",
       "      <td>1.094100</td>\n",
       "      <td>12.340091</td>\n",
       "      <td>58.376932</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.223524</td>\n",
       "      <td>0.414470</td>\n",
       "      <td>46.573230</td>\n",
       "      <td>7.015535</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.670000</td>\n",
       "      <td>0.894316</td>\n",
       "      <td>0.000987</td>\n",
       "      <td>54860.500000</td>\n",
       "      <td>50407.000000</td>\n",
       "      <td>3.235000e+02</td>\n",
       "      <td>579.000000</td>\n",
       "      <td>0.000423</td>\n",
       "      <td>0.363731</td>\n",
       "      <td>0.000420</td>\n",
       "      <td>0.404276</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.000618</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.002154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>44.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>265.000000</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>163.000000</td>\n",
       "      <td>236.250000</td>\n",
       "      <td>262.000000</td>\n",
       "      <td>0.336634</td>\n",
       "      <td>4.191310</td>\n",
       "      <td>10.613825</td>\n",
       "      <td>2.423106</td>\n",
       "      <td>0.127174</td>\n",
       "      <td>0.116717</td>\n",
       "      <td>0.186599</td>\n",
       "      <td>1.162999</td>\n",
       "      <td>0.288309</td>\n",
       "      <td>0.127174</td>\n",
       "      <td>0.103835</td>\n",
       "      <td>0.186599</td>\n",
       "      <td>0.334262</td>\n",
       "      <td>0.288309</td>\n",
       "      <td>0.171301</td>\n",
       "      <td>0.293131</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.454130</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.173868</td>\n",
       "      <td>0.817922</td>\n",
       "      <td>0.768221</td>\n",
       "      <td>0.849422</td>\n",
       "      <td>0.743128</td>\n",
       "      <td>0.673978</td>\n",
       "      <td>0.650392</td>\n",
       "      <td>0.690721</td>\n",
       "      <td>0.677727</td>\n",
       "      <td>0.517771</td>\n",
       "      <td>0.706830</td>\n",
       "      <td>5.667984</td>\n",
       "      <td>0.570652</td>\n",
       "      <td>24.202735</td>\n",
       "      <td>0.833698</td>\n",
       "      <td>2.761875</td>\n",
       "      <td>19.866642</td>\n",
       "      <td>125.080112</td>\n",
       "      <td>1.142245</td>\n",
       "      <td>11.825651</td>\n",
       "      <td>6.070980</td>\n",
       "      <td>102.283434</td>\n",
       "      <td>26.026233</td>\n",
       "      <td>472.070000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>17.549629</td>\n",
       "      <td>0.004099</td>\n",
       "      <td>117911.000000</td>\n",
       "      <td>96744.000000</td>\n",
       "      <td>6.524050e+04</td>\n",
       "      <td>48283.500000</td>\n",
       "      <td>0.001359</td>\n",
       "      <td>0.543041</td>\n",
       "      <td>0.001296</td>\n",
       "      <td>0.597752</td>\n",
       "      <td>0.000504</td>\n",
       "      <td>0.162911</td>\n",
       "      <td>0.000512</td>\n",
       "      <td>0.178562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6380.000000</td>\n",
       "      <td>30980.000000</td>\n",
       "      <td>43401.000000</td>\n",
       "      <td>46805.000000</td>\n",
       "      <td>7331.000000</td>\n",
       "      <td>6380.000000</td>\n",
       "      <td>30802.000000</td>\n",
       "      <td>43401.000000</td>\n",
       "      <td>42065.000000</td>\n",
       "      <td>7331.000000</td>\n",
       "      <td>16562.000000</td>\n",
       "      <td>10153.000000</td>\n",
       "      <td>15386.000000</td>\n",
       "      <td>16269.000000</td>\n",
       "      <td>26614.000000</td>\n",
       "      <td>80040.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>73.861091</td>\n",
       "      <td>149.156894</td>\n",
       "      <td>696.244666</td>\n",
       "      <td>23.153369</td>\n",
       "      <td>166.039668</td>\n",
       "      <td>120.190281</td>\n",
       "      <td>334.473279</td>\n",
       "      <td>52.388070</td>\n",
       "      <td>23.153369</td>\n",
       "      <td>159.343771</td>\n",
       "      <td>120.190281</td>\n",
       "      <td>300.600758</td>\n",
       "      <td>52.388070</td>\n",
       "      <td>60.082598</td>\n",
       "      <td>89.817441</td>\n",
       "      <td>100.685461</td>\n",
       "      <td>706.649390</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1294.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.998274</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.972284</td>\n",
       "      <td>0.993134</td>\n",
       "      <td>0.969981</td>\n",
       "      <td>0.989403</td>\n",
       "      <td>0.999739</td>\n",
       "      <td>0.999854</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>242.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>66.257393</td>\n",
       "      <td>35.319543</td>\n",
       "      <td>28.413881</td>\n",
       "      <td>59.853592</td>\n",
       "      <td>930.130573</td>\n",
       "      <td>146.448102</td>\n",
       "      <td>162.064156</td>\n",
       "      <td>251.931476</td>\n",
       "      <td>911.625358</td>\n",
       "      <td>438.674602</td>\n",
       "      <td>1205.670000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>402.330000</td>\n",
       "      <td>3593.895311</td>\n",
       "      <td>5.734000</td>\n",
       "      <td>616492.000000</td>\n",
       "      <td>484231.000000</td>\n",
       "      <td>1.127939e+06</td>\n",
       "      <td>617792.000000</td>\n",
       "      <td>0.091781</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.080836</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            E5_Ret        E5_Off        E5_Ind        E5_Svc       E5_Ent  \\\n",
       "count  6568.000000   6568.000000   6568.000000   6568.000000  6568.000000   \n",
       "mean     65.918240    146.455542    251.846224    427.172655   112.593788   \n",
       "std     226.805167    954.386529   1485.914713   1717.705386   292.486773   \n",
       "min       0.000000      0.000000      0.000000      0.000000     0.000000   \n",
       "25%       0.000000      2.000000      9.000000     44.000000     2.000000   \n",
       "50%       8.000000     10.000000     27.000000    111.000000    27.000000   \n",
       "75%      44.000000     38.000000     79.000000    265.000000   105.000000   \n",
       "max    6380.000000  30980.000000  43401.000000  46805.000000  7331.000000   \n",
       "\n",
       "            E8_Ret        E8_off        E8_Ind        E8_Svc       E8_Ent  \\\n",
       "count  6568.000000   6568.000000   6568.000000   6568.000000  6568.000000   \n",
       "mean     65.918240    105.945646    251.846224    201.356121   112.593788   \n",
       "std     226.805167    811.822138   1485.914713   1082.782120   292.486773   \n",
       "min       0.000000      0.000000      0.000000      0.000000     0.000000   \n",
       "25%       0.000000      2.000000      9.000000     14.000000     2.000000   \n",
       "50%       8.000000      9.000000     27.000000     35.000000    27.000000   \n",
       "75%      44.000000     31.000000     79.000000     94.000000   105.000000   \n",
       "max    6380.000000  30802.000000  43401.000000  42065.000000  7331.000000   \n",
       "\n",
       "              E8_Ed       E8_Hlth        E8_Pub   E_LowWageWk   E_MedWageWk  \\\n",
       "count   6568.000000   6568.000000   6568.000000   6568.000000   6568.000000   \n",
       "mean     120.724726    105.091809     40.509896    172.826127    257.829019   \n",
       "std      735.832511    498.665116    387.861605    452.605201    778.688304   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        0.000000      8.000000      0.000000     31.000000     37.000000   \n",
       "50%        7.000000     23.000000      0.000000     69.000000     88.000000   \n",
       "75%       62.000000     65.000000      0.000000    163.000000    236.250000   \n",
       "max    16562.000000  10153.000000  15386.000000  16269.000000  26614.000000   \n",
       "\n",
       "         E_HiWageWk  E_PctLowWage          D1A          D1B          D1C  \\\n",
       "count   6568.000000   6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean     573.331303      0.269691     3.398548     8.012142     3.582072   \n",
       "std     2751.740828      0.124850     5.327989    11.175842    14.063405   \n",
       "min        0.000000      0.000000     0.000000     0.000000     0.000000   \n",
       "25%       39.000000      0.182713     0.324743     0.704303     0.128184   \n",
       "50%       98.000000      0.253113     1.964285     4.699322     0.625745   \n",
       "75%      262.000000      0.336634     4.191310    10.613825     2.423106   \n",
       "max    80040.000000      1.000000    73.861091   149.156894   696.244666   \n",
       "\n",
       "          D1C5_RET     D1C5_OFF     D1C5_IND     D1C5_SVC     D1C5_ENT  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.260527     0.719655     0.378950     1.750091     0.472849   \n",
       "std       0.833661     5.588315     2.222663     8.071074     1.740141   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000000     0.001143     0.010918     0.043457     0.000622   \n",
       "50%       0.008530     0.017539     0.052960     0.294056     0.032065   \n",
       "75%       0.127174     0.116717     0.186599     1.162999     0.288309   \n",
       "max      23.153369   166.039668   120.190281   334.473279    52.388070   \n",
       "\n",
       "          D1C8_RET     D1C8_OFF     D1C8_IND     D1C8_SVC     D1C8_ENT  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.260527     0.377378     0.378950     0.729900     0.472849   \n",
       "std       0.833661     3.568290     2.222663     4.589154     1.740141   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000000     0.000678     0.010918     0.012313     0.000622   \n",
       "50%       0.008530     0.015112     0.052960     0.084606     0.032065   \n",
       "75%       0.127174     0.103835     0.186599     0.334262     0.288309   \n",
       "max      23.153369   159.343771   120.190281   300.600758    52.388070   \n",
       "\n",
       "           D1C8_ED    D1C8_HLTH     D1C8_PUB          D1D      D1_FLAG  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.450346     0.569844     0.342278     6.980620     0.001218   \n",
       "std       2.877023     3.373873     4.077830    16.364305     0.034882   \n",
       "min       0.000000     0.000000     0.000000     0.000699     0.000000   \n",
       "25%       0.000000     0.005791     0.000000     0.611305     0.000000   \n",
       "50%       0.004866     0.058395     0.000000     3.180697     0.000000   \n",
       "75%       0.171301     0.293131     0.000000     7.454130     0.000000   \n",
       "max      60.082598    89.817441   100.685461   706.649390     1.000000   \n",
       "\n",
       "          D2A_JPHH    D2B_E5MIX   D2B_E5MIXA    D2B_E8MIX   D2B_E8MIXA  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      2.492406     0.651673     0.586945     0.716324     0.606824   \n",
       "std      23.301847     0.217217     0.224334     0.182274     0.181047   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.208042     0.517664     0.433108     0.635228     0.498076   \n",
       "50%       0.464286     0.699363     0.618558     0.764205     0.639104   \n",
       "75%       1.173868     0.817922     0.768221     0.849422     0.743128   \n",
       "max    1294.000000     1.000000     0.998274     1.000000     0.972284   \n",
       "\n",
       "         D2A_EPHHM   D2C_TRPMX1   D2C_TRPMX2   D2C_TRIPEQ   D2R_JOBPOP  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.525778     0.509411     0.540602     0.466786     0.346393   \n",
       "std       0.194984     0.174006     0.188160     0.282745     0.271953   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.380408     0.386540     0.408399     0.258097     0.127204   \n",
       "50%       0.525528     0.519455     0.549969     0.473379     0.268247   \n",
       "75%       0.673978     0.650392     0.690721     0.677727     0.517771   \n",
       "max       0.993134     0.969981     0.989403     0.999739     0.999854   \n",
       "\n",
       "        D2R_WRKEMP   D2A_WRKEMP   D2C_WREMLX          D3A        D3AAO  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.473834     4.775469     0.320303    15.805488     0.962671   \n",
       "std       0.280552     8.249127     0.315073    10.892324     2.230362   \n",
       "min       0.000000     0.000000     0.000000     0.201734     0.000000   \n",
       "25%       0.239042     0.903226     0.009342     5.226973     0.000000   \n",
       "50%       0.448578     2.451378     0.233400    15.719917     0.043947   \n",
       "75%       0.706830     5.667984     0.570652    24.202735     0.833698   \n",
       "max       1.000000   242.000000     1.000000    66.257393    35.319543   \n",
       "\n",
       "             D3AMM        D3APO          D3B        D3BAO       D3BMM3  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      2.081332    12.761485    80.896852     2.236382     9.932338   \n",
       "std       2.711260     9.292966    88.241150     7.576800    16.558875   \n",
       "min       0.000000     0.000000     0.033017     0.000000     0.000000   \n",
       "25%       0.296585     3.804942    11.309733     0.000000     0.348963   \n",
       "50%       1.094100    12.340091    58.376932     0.000000     3.223524   \n",
       "75%       2.761875    19.866642   125.080112     1.142245    11.825651   \n",
       "max      28.413881    59.853592   930.130573   146.448102   162.064156   \n",
       "\n",
       "            D3BMM4       D3BPO3       D3BPO4           D4A       D4B025  \\\n",
       "count  6568.000000  6568.000000  6568.000000   6568.000000  6568.000000   \n",
       "mean      5.865437    69.294921    22.186833 -47503.406956     0.032314   \n",
       "std      13.073227    82.108396    37.976761  50200.373108     0.142689   \n",
       "min       0.000000     0.000000     0.000000 -99999.000000     0.000000   \n",
       "25%       0.000000     9.540670     0.783275 -99999.000000     0.000000   \n",
       "50%       0.414470    46.573230     7.015535     57.000000     0.000000   \n",
       "75%       6.070980   102.283434    26.026233    472.070000     0.000000   \n",
       "max     251.931476   911.625358   438.674602   1205.670000     1.000000   \n",
       "\n",
       "            D4B050           D4C           D4D           D4E           D5AR  \\\n",
       "count  6568.000000   6568.000000   6568.000000   6568.000000    6568.000000   \n",
       "mean      0.080674 -34981.573301 -34944.232667 -34987.463492   79087.569732   \n",
       "std       0.235226  47700.609816  47728.252319  47696.286678   87917.731987   \n",
       "min       0.000000 -99999.000000 -99999.000000 -99999.000000      33.000000   \n",
       "25%       0.000000 -99999.000000 -99999.000000 -99999.000000   12225.000000   \n",
       "50%       0.000000      1.670000      0.894316      0.000987   54860.500000   \n",
       "75%       0.000000      6.000000     17.549629      0.004099  117911.000000   \n",
       "max       1.000000    402.330000   3593.895311      5.734000  616492.000000   \n",
       "\n",
       "                D5AE          D5BR           D5BE         D5CR        D5CRI  \\\n",
       "count    6568.000000  6.568000e+03    6568.000000  6568.000000  6568.000000   \n",
       "mean    66814.646620  2.296478e+04   -3672.963916     0.001998     0.370175   \n",
       "std     72466.561323  1.726296e+05  117793.744412     0.005823     0.251057   \n",
       "min        89.000000 -9.999900e+04  -99999.000000     0.000000     0.000000   \n",
       "25%     12555.000000 -9.999900e+04  -99999.000000     0.000159     0.163719   \n",
       "50%     50407.000000  3.235000e+02     579.000000     0.000423     0.363731   \n",
       "75%     96744.000000  6.524050e+04   48283.500000     0.001359     0.543041   \n",
       "max    484231.000000  1.127939e+06  617792.000000     0.091781     1.000000   \n",
       "\n",
       "              D5CE        D5CEI          D5DR         D5DRI          D5DE  \\\n",
       "count  6568.000000  6568.000000   6568.000000   6568.000000   6568.000000   \n",
       "mean      0.001948     0.407187 -47761.396512 -47761.285836 -47761.396565   \n",
       "std       0.005366     0.258548  49953.187857  49953.293693  49953.187806   \n",
       "min       0.000000     0.000000 -99999.000000 -99999.000000 -99999.000000   \n",
       "25%       0.000164     0.196729 -99999.000000 -99999.000000 -99999.000000   \n",
       "50%       0.000420     0.404276      0.000002      0.000618      0.000004   \n",
       "75%       0.001296     0.597752      0.000504      0.162911      0.000512   \n",
       "max       0.080836     1.000000      1.000000      1.000000      1.000000   \n",
       "\n",
       "              D5DEI  \n",
       "count   6568.000000  \n",
       "mean  -47761.277078  \n",
       "std    49953.302068  \n",
       "min   -99999.000000  \n",
       "25%   -99999.000000  \n",
       "50%        0.002154  \n",
       "75%        0.178562  \n",
       "max        1.000000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with pd.option_context('display.max_columns', 200):\n",
    "    display(df.loc[:,'E5_Ret':'D5DEI'].describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Clean -99999.0 values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "columns with -99999: D4A, D4C, D4D, D4E, D5BR, D5BE, D5DR, D5RI, D5DE, D5DEI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    3431\n",
       "True     3137\n",
       "Name: D4A, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df1['D4A'] == -99999).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.query('D4A >= 0')['D4A'].plot(kind = 'hist');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing values indicate missing transit data or > 3/4 mile from the \n",
    "population center to the nearest transportation stop.\n",
    "See page 23 / footnote 65 of the [technical documentation](https://www.epa.gov/sites/default/files/2021-06/documents/epa_sld_3.0_technicaldocumentationuserguide_may2021.pdf).\n",
    "A reasonable value to impute is 2000, indicating a very large distance to\n",
    "transit as well as setting a low transit flag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['Low_transit_flag_dist'] = (df1['D4A'] == -99999.)\n",
    "df1['D4A'].replace({-99999.: 2000}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    4270\n",
       "True     2298\n",
       "Name: D4C, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df1['D4C'] == -99999).value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "D4C, D4D, and D4E are frequency measures so we can impute missing values with 0.\n",
    "See page 24, from technical documentation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df1['D4C'] >= 0) == (df1['D4D'] >= 0)).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((df1['D4C'] >= 0) == (df1['D4E'] >= 0)).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['Low_transit_flag_freq'] = df1['D4C'] == -99999.\n",
    "# df1['Low_transit_flag_freq'].value_counts()\n",
    "df1.loc[df1['Low_transit_flag_freq'], ['D4C', 'D4D', 'D4E']] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1['D4C'].plot(kind = 'hist');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>D5BR</th>\n",
       "      <th>D5BE</th>\n",
       "      <th>D5DR</th>\n",
       "      <th>D5DRI</th>\n",
       "      <th>D5DE</th>\n",
       "      <th>D5DEI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</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>9530</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9532</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9533</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9534</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9536</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6568 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       D5BR   D5BE   D5DR  D5DRI   D5DE  D5DEI\n",
       "0     False  False  False  False  False  False\n",
       "1     False  False  False  False  False  False\n",
       "4      True   True   True   True   True   True\n",
       "8      True   True   True   True   True   True\n",
       "12    False  False  False  False  False  False\n",
       "...     ...    ...    ...    ...    ...    ...\n",
       "9530   True   True   True   True   True   True\n",
       "9532  False  False  False  False  False  False\n",
       "9533  False  False  False  False  False  False\n",
       "9534  False  False  False  False  False  False\n",
       "9536  False  False  False  False  False  False\n",
       "\n",
       "[6568 rows x 6 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d5cols = ['D5BR', 'D5BE', 'D5DR', 'D5DRI', 'D5DE', 'D5DEI'] \n",
    "df1[d5cols] == -99999"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The -99999 values for destination accessibility are the same as the earlier\n",
    "`Low_transit_flag_dist` flag. Since these indicate the number of jobs\n",
    "or working age population within transit distance of the area, a reasonable \n",
    "value to impute is 0, when very little transportation is available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "for col in d5cols:\n",
    "    print(((df1[col] == -99999) == (df1['Low_transit_flag_dist'])).all())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.loc[~df1['Low_transit_flag_dist'], ['D5BR', 'D5BE'] ].plot(\n",
    "    subplots = True, kind = 'hist', figsize = (10, 10), \n",
    "    sharex = False, logy = True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ekqpqO8OEJVkMLAb+CFjb4dPNAR7v8Dk0cfbL9GOfTE/2y/Rjn0xPU9Evv1lVr93Zga4syKZSktVVNdR2Dr2S/TL92CfTk/0y/dgn01Pb/eL9viRJklpmQSZJktQyC7LxLW87gHbKfpl+7JPpyX6ZfuyT6anVfnENmSRJUsscIZMkSWqZBdmoJIuS/DjJuiSX7+R4klw7evy+JKe2kbOfNOiTi0b74r4k30lychs5+814/TLmdacn2ZrkXVOZrx816ZMkb0pyb5IHk3x7qjP2owb/hh2UZGWSfx/tl3EfH6i9k+SGJBuTPLCL46191luQAUkGgOuBs4EFwAVJFuzwsrOBY0a/lgB/O6Uh+0zDPnkYOLOqTgI+iesyOq5hv2x/3V8zcgNodVCTPknyGuCzwDlVdQLw7qnO2W8a/q58EPhhVZ0MvAn41OgTbNQ5NwKLdnO8tc96C7IRZwDrqmp9Vb0A3AKcu8NrzgVuqhF3Aa9JcthUB+0j4/ZJVX2nqv5jdPMuRp6Lqs5q8rsC8CHgH4GNUxmuTzXpkwuBr1bVIwBVZb90XpN+KeCAJAH2B54AXpramP2lqlYx8nPeldY+6y3IRhwOPDpme3h030Rfo8kz0Z/3xcDXOppI0KBfkhwOnA8sm8Jc/azJ78qxwMFJ7khyT5L3T1m6/tWkX64DjgceA+4H/ryqtk1NPO1Ca5/1M6biJF0gO9m34+WnTV6jydP4553kLEYKsjd2NJGgWb98BvhIVW0d+cNfHdakT2YApwG/B8wCvpvkrqp6qNPh+liTfvkD4F7gzcBRwDeS3FlVT3Y4m3attc96C7IRw8ARY7bnMvIXy0Rfo8nT6Oed5CTgC8DZVbV5irL1syb9MgTcMlqMzQHeluSlqloxJQn7T9N/vx6vqmeAZ5KsAk4GLMg6p0m/fAC4ukbuP7UuycPA64DvT01E7URrn/VOWY64GzgmyfzRBZXvBW7b4TW3Ae8fvQLjt4AtVfXzqQ7aR8btkyTzgK8C7/Mv/Skzbr9U1fyqGqyqQeArwKUWYx3V5N+vfwJ+N8mMJPsBbwDWTHHOftOkXx5hZNSSJL8OHAesn9KU2lFrn/WOkAFV9VKSyxi5ImwAuKGqHkyydPT4MuB24G3AOuAXjPxlow5p2CdXArOBz46OxrzkA3s7q2G/aAo16ZOqWpPkn4H7gG3AF6pqp5f9a3I0/F35JHBjkvsZmSr7SFU93lroPpDkZkauaJ2TZBj4OLAPtP9Z7536JUmSWuaUpSRJUsssyCRJklpmQSZJktQyCzJJkqSWWZBJkiS1zIJMkiSpZRZkkiRJLbMgkyRJallX36l/zpw5NTg42HYMSZKkcd1zzz2PV9Vrd3asqwuywcFBVq9e3XYMSZKkcSX56a6OOWUpSZLUMgsySZKkllmQSZIktayr15BNiasOajvB5LlqS9sJJEk96sUXX2R4eJjnnnuu7SitmzlzJnPnzmWfffZp3MaCTJIk7bXh4WEOOOAABgcHSdJ2nNZUFZs3b2Z4eJj58+c3bueUpSRJ2mvPPfccs2fP7utiDCAJs2fPnvBIoQWZJEmaFP1ejG23Jz8HCzJJktQTBgYGWLhwISeccAInn3wy11xzDdu2bQNgw4YNzJo1i4ULF7Jw4UKWLl36crvBwUFOPPFETjzxRBYsWMAVV1zB888//yvtFixYwPvf/35efPFFAO644w7+8A//cFKyT5s1ZEmOB/4cmAP8a1X9bcuRJEnSnprsi+IaXJg2a9Ys7r33XgA2btzIhRdeyJYtW/jEJz4BwFFHHfXy8R1961vfYs6cOTz99NMsWbKEJUuW8MUvfvEV7bZu3cpb3/pWbr31Vi666KJJ+c/arqMjZEluSLIxyQM77F+U5MdJ1iW5HKCq1lTVUuA9wFAnc0mSpN526KGHsnz5cq677jqqqnG7/fffn2XLlrFixQqeeOKJVxwbGBjgjDPO4Gc/+9lkx+34lOWNwKKxO5IMANcDZwMLgAuSLBg9dg7wv4F/7XAuSZLU44488ki2bdvGxo0bAXj44Yc55ZRTOPPMM7nzzjt32e7AAw9k/vz5rF279hX7n3vuOb73ve+xaNGiXbTccx0tyKpqFfDEDrvPANZV1fqqegG4BTh39PW3VdVvA5M7DihJkvrS9tGxww47jEceeYQf/OAHXHPNNVx44YU8+eST47YD+MlPfsLChQuZPXs28+bN46STTpr0nG0s6j8ceHTM9jBweJI3Jbk2yeeA21vIJUmSesj69esZGBjg0EMP5dWvfjWzZ88G4LTTTuOoo47ioYce2mm7p556ig0bNnDssccCv1xDtm7dOu666y5uu+22Sc/aRkG2s2tBq6ruqKo/q6o/rarrd9k4WZJkdZLVmzZt6mBMSZLUrTZt2sTSpUu57LLLSMKmTZvYunUrMFKorV27liOPPPJX2j399NNceumlnHfeeRx88MGvOHbYYYdx9dVX81d/9VeTnreNqyyHgSPGbM8FHmvauKqWA8sBhoaGmq/SkyRJPe3ZZ59l4cKFvPjii8yYMYP3ve99fPjDHwZg1apVXHnllcyYMYOBgQGWLVvGIYcc8nLbs846i6pi27ZtnH/++XzsYx/b6TnOO+88rrrqqt2uQdsTmciVB3t0gmQQ+P+q6vWj2zOAh4DfA34G3A1cWFUPTuA9FwOLjz766Et2XHA36XyWpSRJ41qzZg3HH3982zGmjZ39PJLcU1U7vZNEp297cTPwXeC4JMNJLq6ql4DLgK8Da4BbJ1KMAVTVyqpactBBPVQsSZKkvtXRKcuqumAX+2/HhfuSJElAlz46KcniJMu3bHEKTpIkdb+uLMicspQkafrp9Lr0brEnP4euLMgkSdL0MnPmTDZv3tz3RVlVsXnzZmbOnDmhdtPm4eITMeYqy7ajSJIkYO7cuQwPD+M9QkeK07lz506oTVcWZFW1Elg5NDR0SdtZJEkS7LPPPsyfP7/tGF3LKUtJkqSWWZBJkiS1rCsLMm97IUmSeklXFmTe9kKSJPWSrlzUrz3kczklSZqWunKETJIkqZdYkEmSJLWsKwsyF/VLkqRe0pUFmYv6JUlSL+nKgkySJKmXNCrIkry+00EkSZL6VdPbXixLsi9wI/D3VfV/OpZIasJbeEiSekijEbKqeiNwEXAEsDrJ3yd5a0eT7YaL+iVJUi9pvIasqtYCVwAfAc4Erk3yoyTv6FS43WRxUb8kSeoZTdeQnZTk08Aa4M3A4qo6fvT7T3cwnyRJUs9ruobsOuDzwEer6tntO6vqsSRXdCSZJElSn2hakL0NeLaqtgIkeRUws6p+UVVf6lg6SZKkPtB0Ddk3gVljtvcb3SdJkqS91HSEbGZVPb19o6qeTrJfhzJJ/aVXbuHh7TskaY81HSF7Jsmp2zeSnAY8u5vXd5S3vZAkSb2kaUH2F8CXk9yZ5E7gH4DLOpZqHN72QpIk9ZJGU5ZVdXeS1wHHAQF+VFUvdjSZJElSn2i6hgzgdGBwtM0pSaiqmzqSSpIkqY80KsiSfAk4CrgX2Dq6uwALMkkjeuXiBPACBUlTrukI2RCwoKqqk2EkSZL6UdNF/Q8Av9HJIJIkSf2q6QjZHOCHSb4PPL99Z1Wd05FUkiRJfaRpQXZVJ0NIkiT1s6a3vfh2kt8Ejqmqb47epX+gs9EkSZL6Q6M1ZEkuAb4CfG501+HAig5lapLHO/VLkqSe0XRR/weB3wGeBKiqtcChnQo1Hu/UL0mSeknTNWTPV9ULSQBIMoOR+5BJkqazXrk/nPeGU49rOkL27SQfBWYleSvwZWBl52JJkiT1j6YF2eXAJuB+4E+B24ErOhVKkiSpnzS9ynIb8PnRL0mSJE2ips+yfJidrBmrqiMnPZEkSVKfmcizLLebCbwbOGTy40iSJPWfRmvIqmrzmK+fVdVngDd3NpokSVJ/aDpleeqYzVcxMmJ2QEcSSZIk9ZmmU5afGvP9S8AG4D2TnkaSJKkPNb3K8qxOB5EkSepXTacsP7y741V1zeTEkaRpoFfubi+pa0zkKsvTgdtGtxcDq4BHOxFKkiSpnzQtyOYAp1bVUwBJrgK+XFV/MplhkpwHvJ2RB5dfX1X/MpnvL0mSNB01fXTSPOCFMdsvAINNGia5IcnGJA/ssH9Rkh8nWZfkcoCqWlFVlwD/GfijhtkkSZK6WtOC7EvA95NcleTjwPeAmxq2vRFYNHZHkgHgeuBsYAFwQZIFY15yxehxSZKkntf0Ksv/luRrwO+O7vpAVf2gYdtVSQZ32H0GsK6q1gMkuQU4N8ka4Grga1X1b03eX5Ikqds1HSED2A94sqr+BhhOMn8vzns4r7wgYHh034eAtwDvSrJ0Zw2TLEmyOsnqTZs27UUESZKk6aHpbS8+zsiVlscB/y+wD/B3wO/s4Xmzk31VVdcC1+6uYVUtB5YDDA0N/coDzyVJkrpN0xGy84FzgGcAquox9u7RScPAEWO25wKPNW2cZHGS5Vu2bNmLCJIkSdND04LshaoqoACS/Npenvdu4Jgk85PsC7yXX97jbFxVtbKqlhx0kDdvlCRJ3a9pQXZrks8Br0lyCfBN4PNNGia5GfgucFyS4SQXV9VLwGXA14E1wK1V9eDE40uSJHW/cdeQJQnwD8DrgCcZWUd2ZVV9o8kJquqCXey/Hbi9edRXZFoMLD766KP3pLkkSdK0Mm5BVlWVZEVVnQY0KsI6rapWAiuHhoYuaTuLJEnS3mo6ZXlXktM7mkSSJKlPNX2W5VnA0iQbGLnSMowMnp3UqWC745SlJEnqJbstyJLMq6pHGHnE0bThlKUkSeol442QrQBOraqfJvnHqnrnFGSSJOmVruqh2xxd5T009avGW0M29o76R3YyiCRJUr8aryCrXXzfKu/UL0mSesl4BdnJSZ5M8hRw0uj3TyZ5KsmTUxFwZ7xTvyRJ6iW7XUNWVQNTFUSSJKlfNb0PmSRJkjrEgkySJKllXVmQuahfkiT1kq4syFzUL0mSeklXFmSSJEm9xIJMkiSpZRZkkiRJLevKgsxF/ZIkqZd0ZUHmon5JktRLurIgkyRJ6iUWZJIkSS2zIJMkSWqZBZkkSVLLLMgkSZJa1pUFmbe9kCRJvaQrCzJveyFJknpJVxZkkiRJvcSCTJIkqWUWZJIkSS2zIJMkSWqZBZkkSVLLLMgkSZJaZkEmSZLUMgsySZKkllmQSZIktawrCzIfnSRJknrJjLYD7ImqWgmsHBoauqTtLJIkTchVPvZvWrqq3UGerhwhkyRJ6iUWZJIkSS2zIJMkSWqZBZkkSVLLUlVtZ9hjSTYBP+3waeYAj3f4HJo4+2X6sU+mJ/tl+rFPpqep6JffrKrX7uxAVxdkUyHJ6qoaajuHXsl+mX7sk+nJfpl+7JPpqe1+ccpSkiSpZRZkkiRJLbMgG9/ytgNop+yX6cc+mZ7sl+nHPpmeWu0X15BJkiS1zBEySZKkllmQjUqyKMmPk6xLcvlOjifJtaPH70tyahs5+0mDPrlotC/uS/KdJCe3kbPfjNcvY153epKtSd41lfn6UZM+SfKmJPcmeTDJt6c6Yz9q8G/YQUlWJvn30X75QBs5+0mSG5JsTPLALo639llvQQYkGQCuB84GFgAXJFmww8vOBo4Z/VoC/O2UhuwzDfvkYeDMqjoJ+CSuy+i4hv2y/XV/DXx9ahP2nyZ9kuQ1wGeBc6rqBODdU52z3zT8Xfkg8MOqOhl4E/CpJPtOadD+cyOwaDfHW/ustyAbcQawrqrWV9ULwC3AuTu85lzgphpxF/CaJIdNddA+Mm6fVNV3quo/RjfvAuZOccZ+1OR3BeBDwD8CG6cyXJ9q0icXAl+tqkcAqsp+6bwm/VLAAUkC7A88Abw0tTH7S1WtYuTnvCutfdZbkI04HHh0zPbw6L6JvkaTZ6I/74uBr3U0kaBBvyQ5HDgfWDaFufpZk9+VY4GDk9yR5J4k75+ydP2rSb9cBxwPPAbcD/x5VW2bmnjahdY+62dMxUm6QHayb8fLT5u8RpOn8c87yVmMFGRv7GgiQbN++QzwkaraOvKHvzqsSZ/MAE4Dfg+YBXw3yV1V9VCnw/WxJv3yB8C9wJuBo4BvJLmzqp7scDbtWmuf9RZkI4aBI8Zsz2XkL5aJvkaTp9HPO8lJwBeAs6tq8xRl62dN+mUIuGW0GJsDvC3JS1W1YkoS9p+m/349XlXPAM8kWQWcDFiQdU6TfvkAcHWN3H9qXZKHgdcB35+aiNqJ1j7rnbIccTdwTJL5owsq3wvctsNrbgPeP3oFxm8BW6rq51MdtI+M2ydJ5gFfBd7nX/pTZtx+qar5VTVYVYPAV4BLLcY6qsm/X/8E/G6SGUn2A94ArJninP2mSb88wsioJUl+HTgOWD+lKbWj1j7rHSEDquqlJJcxckXYAHBDVT2YZOno8WXA7cDbgHXALxj5y0Yd0rBPrgRmA58dHY15yQf2dlbDftEUatInVbUmyT8D9wHbgC9U1U4v+9fkaPi78kngxiT3MzJV9pGqery10H0gyc2MXNE6J8kw8HFgH2j/s9479UuSJLXMKUtJkqSWWZBJkiS1zIJMkiSpZRZkkiRJLbMgkyRJapkFmSRJUsssyCRJklpmQSZJktSyrrxTf5LFwOIDDjjgkmOPPbbtOJIkSeO65557Hq+q1+7sWFffqX9oaKhWr17ddgxJkqRxJblnV4/4c8pSkiSpZV1ZkCVZnGT5li1b2o4iSZK017qyIKuqlVW15KCDDmo7iiRJ0l7rykX9U+nEL57YdoRJc/9/ur/tCJKkPvHiiy8yPDzMc88913aUKTdz5kzmzp3LPvvs07iNBZkkSZp0w8PDHHDAAQwODpKk7ThTpqrYvHkzw8PDzJ8/v3G7rpyydA2ZJEnT23PPPcfs2bP7qhgDSMLs2bMnPDLYlQWZa8gkSZr++q0Y225P/ru7siCTJEkaz8DAAAsXLuSEE07g5JNP5pprrmHbtm0AbNiwgVmzZrFw4UIWLlzI0qVLX243ODjIiSeeyIknnsiCBQu44ooreP7553fabuHChdx00017ndU1ZJIkqeMm+yK5JheqzZo1i3vvvReAjRs3cuGFF7JlyxY+8YlPAHDUUUe9fHxH3/rWt5gzZw5PP/00S5YsYcmSJXzxi18ct92ecoRMkiT1vEMPPZTly5dz3XXXMZGnFO2///4sW7aMFStW8MQTT3QsX1cWZC7qlyRJE3XkkUeybds2Nm7cCMDDDz/MKaecwplnnsmdd965y3YHHngg8+fPZ+3atQD85Cc/ecWU5e7aNtWVU5ZVtRJYOTQ0dEnbWSRJUvfYPjp22GGH8cgjjzB79mzuuecezjvvPB588EEOPPDA3bYDpywlSZL22Pr16xkYGODQQw/l1a9+NbNnzwbgtNNO46ijjuKhhx7aabunnnqKDRs2cOyxx3YsmwWZJEnqeZs2bWLp0qVcdtllJGHTpk1s3boVGCnU1q5dy5FHHvkr7Z5++mkuvfRSzjvvPA4++OCO5evKKUtJkqTxPPvssyxcuJAXX3yRGTNm8L73vY8Pf/jDAKxatYorr7ySGTNmMDAwwLJlyzjkkENebnvWWWdRVWzbto3zzz+fj33sYy8f276GbLs//uM/5s/+7M/2Kuu0KciSHA/8OTAH+Neq+tuWI0mSpEnSxvOUt4+A7cw73/lO3vnOd+702IYNG3bZbnBwkGeffXZvo/2Kjk5ZJrkhycYkD+ywf1GSHydZl+RygKpaU1VLgfcAQ53MJUmSNJ10eg3ZjcCisTuSDADXA2cDC4ALkiwYPXYO8L+Bf+1wLkmSpGmjowVZVa0CdryL2hnAuqpaX1UvALcA546+/raq+m3gok7mkiRJmk7aWEN2OPDomO1h4A1J3gS8A3g1cPuuGidZAiwBmDdvXsdCSpKkvVNVffmA8Yk8CWC7NgqynfVMVdUdwB3jNa6q5cBygKGhoYn/F0uSpI6bOXMmmzdvZvbs2X1VlFUVmzdvZubMmRNq10ZBNgwcMWZ7LvDYRN4gyWJg8dFHHz2ZuSRJ0iSZO3cuw8PDbNq0qe0oU27mzJnMnTt3Qm3aKMjuBo5JMh/4GfBe4MIWckiSpA7ZZ599mD9/ftsxukanb3txM/Bd4Lgkw0kurqqXgMuArwNrgFur6sGJvG9VrayqJQcddNDkh5YkSZpiHR0hq6oLdrH/dnazcH88TllKkqRe0pXPsnSETJIk9ZKuLMiSLE6yfMuWLW1HkSRJ2mtdWZA5QiZJknpJVxZkkiRJvaQrCzKnLCVJUi/pyoLMKUtJktRLurIgkyRJ6iVdWZA5ZSlJknpJo4Isyes7HWQinLKUJEm9pOkI2bIk309yaZLXdDKQJElSv2lUkFXVG4GLgCOA1Un+PslbO5psN5yylCRJvaTxGrKqWgtcAXwEOBO4NsmPkryjU+F2k8UpS0mS1DOariE7KcmngTXAm4HFVXX86Pef7mA+SZKknjej4euuAz4PfLSqnt2+s6oeS3JFR5JJkiT1iaYF2duAZ6tqK0CSVwEzq+oXVfWljqWTJEnqA03XkH0TmDVme7/RfZIkSdpLTQuymVX19PaN0e/360yk8XmVpSRJ6iVNC7Jnkpy6fSPJacCzu3l9R3mVpSRJ6iVN15D9BfDlJI+Nbh8G/FFHEkmSJPWZRgVZVd2d5HXAcUCAH1XVix1NJkmS1CeajpABnA4MjrY5JQlVdVNHUkmSJPWRRgVZki8BRwH3AltHdxcwqQVZkvOAtwOHAtdX1b9M5vtLkiRNR01HyIaABVVVEz1BkhuAPwQ2VtXrx+xfBPwNMAB8oaqurqoVwIokBwP/HbAgkyRJPa/pVZYPAL+xh+e4EVg0dkeSAeB64GxgAXBBkgVjXnLF6HFJkqSe13SEbA7wwyTfB57fvrOqzhmvYVWtSjK4w+4zgHVVtR4gyS3AuUnWAFcDX6uqf2uYTZIkqas1LciumuTzHg48OmZ7GHgD8CHgLcBBSY6uqmU7NkyyBFgCMG/evEmOJUmSNPWa3vbi20l+Ezimqr6ZZD9G1n7tqez8NHUtcO04WZYn+TmweN999z1tLzJIkiRNC43WkCW5BPgK8LnRXYcDK/bivMPAEWO25wKP7eK1v8I79UuSpF7SdFH/B4HfAZ4EqKq1jNyaYk/dDRyTZH6SfYH3Arc1beyzLCVJUi9pWpA9X1UvbN9IMoOR+5CNK8nNwHeB45IMJ7m4ql4CLgO+DqwBbq2qB5uGdoRMkiT1kqaL+r+d5KPArCRvBS4FVjZpWFUX7GL/7cDtDc//CkkWA4uPPvroPWkuSZI0rTQdIbsc2ATcD/wpI4XUFZ0KNR5HyCRJUi9pepXlNuDzo1+tc4RMkiT1kqZXWT6cZP2OX50OtyuOkEmSpF4ykWdZbjcTeDdwyOTHacYRMkmS1EsajZBV1eYxXz+rqs8Ab+5stN3mcYRMkiT1jEYjZElOHbP5KkZGzA7oSCJJkqQ+03TK8lNjvn8J2AC8Z9LTNOSUpSRJ6iVNr7I8q9NBJqKqVgIrh4aGLmk7iyRJ0t5qOmX54d0dr6prJieOJElS/5nIVZan88vnTS4GVgGPdiKUJElSP2lakM0BTq2qpwCSXAV8uar+pFPBdsc1ZJIkqZc0fXTSPOCFMdsvAIOTnqYhb3shSZJ6SdMRsi8B30/yP4ECzgdu6lgqSZKkPtL0Ksv/luRrwO+O7vpAVf2gc7EkSZL6R9MpS4D9gCer6m+A4STzO5RJkiSprzR9uPjHgY8Afzm6ax/g7zoVqkGexUmWb9mypa0IkiRJk6bpCNn5wDnAMwBV9RgtPjrJRf2SJKmXNC3IXqiqYmRBP0l+rXORJEmS+kvTguzWJJ8DXpPkEuCbwOc7F0uSJKl/jHuVZZIA/wC8DngSOA64sqq+0eFskiRJfWHcgqyqKsmKqjoN6FgRluRI4L8CB1XVuzp1HkmSpOmm6ZTlXUlOn+ibJ7khycYkD+ywf1GSHydZl+RygKpaX1UXT/QckiRJ3a5pQXYWI0XZT5Lcl+T+JPc1aHcjsGjsjiQDwPXA2cAC4IIkCyaQWZIkqafsdsoyybyqeoSR4mnCqmpVksEddp8BrKuq9aPnuAU4F/jhnpxDkiSp2403QrYCoKp+ClxTVT8d+7WH5zwceHTM9jBweJLZSZYBpyT5y503hSRLkqxOsnrTpk17GEGSJGn6GG9Rf8Z8f+QknTM72VdVtRlYOl7jqloOLAcYGhqqScokSZLUmvEKstrF93tjGDhizPZc4LGJvEGSxcDio48+epIi9YcTv3hi2xEmzf3/6f62I0iSNGnGK8hOTvIkI6Nas0a/Z3S7qurAPTjn3cAxow8n/xnwXuDCPXgfSZKknrDbNWRVNVBVB1bVAVU1Y/T77dvjFmNJbga+CxyXZDjJxVX1EnAZ8HVgDXBrVT04kdA+y1KSJPWScW8Muzeq6oJd7L8duH1P39cpS0mS1Eua3odsWnGETJIk9ZKuLMiSLE6yfMuWLW1HkSRJ2mtdWZA5QiZJknpJVxZkjpBJkqRe0pUFmSNkkiSpl3RlQSZJktRLurIgc8pSkiT1kq4syJyylCRJvaQrCzJJkqReYkEmSZLUsq4syFxDJkmSeklXFmSuIZMkSb2kKwsySZKkXmJBJkmS1DILMkmSpJZ1ZUHmon5JktRLurIgc1G/JEnqJV1ZkEmSJPUSCzJJkqSWWZBJkiS1zIJMkiSpZTPaDrBdkl8DPgu8ANxRVf+j5UiSJElToqMjZEluSLIxyQM77F+U5MdJ1iW5fHT3O4CvVNUlwDmdzCVJkjSddHrK8kZg0dgdSQaA64GzgQXABUkWAHOBR0dftrXDuSRJkqaNjhZkVbUKeGKH3WcA66pqfVW9ANwCnAsMM1KUdTyXJEnSdNLGGrLD+eVIGIwUYm8ArgWuS/J2YOWuGidZAiwBmDdvXgdjajo78Ysnth1BPez+/3R/2xEmTa/8rvRSn/SSXvn/C9r/f6yNgiw72VdV9QzwgfEaV9XyJD8HFu+7776nTXo6SZKkKdbG1OAwcMSY7bnAYxN5Ax+dJEmSekkbBdndwDFJ5ifZF3gvcNtE3sCHi0uSpF7S6dte3Ax8FzguyXCSi6vqJeAy4OvAGuDWqnqwkzkkSZKms1RV2xn2WJJNwE87fJo5wOMdPocmzn6ZfuyT6cl+mX7sk+lpKvrlN6vqtTs70NUF2VRIsrqqhtrOoVeyX6Yf+2R6sl+mH/tkemq7X7zflyRJUsssyCRJklpmQTa+5W0H0E7ZL9OPfTI92S/Tj30yPbXaL64hkyRJapkjZJIkSS2zIBuVZFGSHydZl+TynRxPkmtHj9+X5NQ2cvaTBn1y0Whf3JfkO0lObiNnvxmvX8a87vQkW5O8ayrz9aMmfZLkTUnuTfJgkm9PdcZ+1ODfsIOSrEzy76P9Mu7jA7V3ktyQZGOSB3ZxvLXPegsyIMkAcD1wNrAAuCDJgh1edjZwzOjXEuBvpzRkn2nYJw8DZ1bVScAncV1GxzXsl+2v+2tGbgCtDmrSJ0leA3wWOKeqTgDePdU5+03D35UPAj+sqpOBNwGfGn2CjTrnRmDRbo639llvQTbiDGBdVa2vqheAW4Bzd3jNucBNNeIu4DVJDpvqoH1k3D6pqu9U1X+Mbt7FyHNR1VlNflcAPgT8I7BxKsP1qSZ9ciHw1ap6BKCq7JfOa9IvBRyQJMD+wBPAS1Mbs79U1SpGfs670tpnvQXZiMOBR8dsD4/um+hrNHkm+vO+GPhaRxMJGvRLksOB84FlU5irnzX5XTkWODjJHUnuSfL+KUvXv5r0y3XA8cBjwP3An1fVtqmJp11o7bN+xlScpAtkJ/t2vPy0yWs0eRr/vJOcxUhB9saOJhI065fPAB+pqq0jf/irw5r0yQzgNOD3gFnAd5PcVVUPdTpcH2vSL38A3Au8GTgK+EaSO6vqyQ5n06619llvQTZiGDhizPZcRv5imehrNHka/byTnAR8ATi7qjZPUbZ+1qRfhoBbRouxOcDbkrxUVSumJGH/afrv1+NV9QzwTJJVwMmABVnnNOmXDwBX18j9p9YleRh4HfD9qYmonWjts94pyxF3A8ckmT+6oPK9wG07vOY24P2jV2D8FrClqn4+1UH7yLh9kmQe8FXgff6lP2XG7Zeqml9Vg1U1CHwFuNRirKOa/Pv1T8DvJpmRZD/gDcCaKc7Zb5r0yyOMjFqS5NeB44D1U5pSO2rts94RMqCqXkpyGSNXhA0AN1TVg0mWjh5fBtwOvA1YB/yCkb9s1CEN++RKYDbw2dHRmJd8YG9nNewXTaEmfVJVa5L8M3AfsA34QlXt9LJ/TY6GvyufBG5Mcj8jU2UfqarHWwvdB5LczMgVrXOSDAMfB/aB9j/rvVO/JElSy5yylCRJapkFmSRJUsssyCRJklpmQSZJktQyCzJJkqSWWZBJkiS1zIJMkiSpZRZkkiRJLevqO/XPmTOnBgcH244hSZI0rnvuuefxqnrtzo51dUE2ODjI6tWr244hSZI0riQ/3dUxpywlSZJaZkEmSZLUMgsySZKklnX1GrKpsOZ1x7cdYdIc/6M1bUeQJPWwF198keHhYZ577rm2o7Rq5syZzJ07l3322adxGwsySZI0KYaHhznggAMYHBwkSdtxWlFVbN68meHhYebPn9+4nVOWkiRpUjz33HPMnj27b4sxgCTMnj17wqOE06YgS3J8kmVJvpLkv7SdR5IkTVw/F2Pb7cnPoKMFWZIbkmxM8sAO+xcl+XGSdUkuB6iqNVW1FHgPMNTJXJIkqTcNDAywcOFCTjjhBE4++WSuueYatm3bBsCGDRuYNWsWCxcuZOHChSxduvTldoODg5x44omceOKJLFiwgCuuuILnn39+p+0WLlzITTfd9HK7xx9/fK9zd3oN2Y3AdcBN23ckGQCuB94KDAN3J7mtqn6Y5Bzg8tE2kiSpi032hXFNLk6bNWsW9957LwAbN27kwgsvZMuWLXziE58A4Kijjnr5+I6+9a1vMWfOHJ5++mmWLFnCkiVL+OIXvzhuu8nQ0RGyqloFPLHD7jOAdVW1vqpeAG4Bzh19/W1V9dvARZ3MJUmSet+hhx7K8uXLue6666iqxu32339/li1bxooVK3jiiR3LmM5oYw3Z4cCjY7aHgcOTvCnJtUk+B9y+q8ZJliRZnWT1pk2bOp1VkiR1sSOPPJJt27axceNGAB5++GFOOeUUzjzzTO68885dtjvwwAOZP38+a9euBeAnP/nJK6Ysd9d2T7Rx24udrXSrqroDuGO8xlW1HFgOMDQ01LzclSRJfWn76Nhhhx3GI488wuzZs7nnnns477zzePDBBznwwAN32w66fMpyF4aBI8ZszwUeayGHJEnqcevXr2dgYIBDDz2UV7/61cyePRuA0047jaOOOoqHHnpop+2eeuopNmzYwLHHHjslOdsoyO4GjkkyP8m+wHuB2ybyBkkWJ1m+ZcuWjgSUJEndb9OmTSxdupTLLruMJGzatImtW7cCI4Xa2rVrOfLII3+l3dNPP82ll17Keeedx8EHHzwlWTs6ZZnkZuBNwJwkw8DHq+r/SXIZ8HVgALihqh6cyPtW1Upg5dDQ0CWTnVmSJHWvZ599loULF/Liiy8yY8YM3ve+9/HhD38YgFWrVnHllVcyY8YMBgYGWLZsGYcccsjLbc866yyqim3btnH++efzsY997OVj29eQbffHf/zH/Nmf/dmk5c5ErjqYboaGhmr16tUdPYfPspQkqZk1a9Zw/PG987m5N3b2s0hyT1Xt9F6r0+ZO/RPhlKUkSeolXVmQVdXKqlpy0EEHtR1FkiRpr3VlQSZJktRLLMgkSdKk6ea16ZNlT34GXVmQuYZMkqTpZ+bMmWzevLmvi7KqYvPmzcycOXNC7dq4U/9e87YXkiRNP3PnzmV4eJh+f7ThzJkzmTt37oTadGVBJkmSpp999tmH+fPntx2jK3XllKUkSVIv6cqCzDVkkiSpl3TllKVryPaMTx2QJGl66soRMkmSpF5iQSZJktQyCzJJkqSWdWVB5qJ+SZLUS7qyIPPh4pIkqZd0ZUEmSZLUS7rytheSt/CQJPWSRiNkSV7f6SCSJEn9qumU5bIk309yaZLXdDJQEy7qlyRJvaRRQVZVbwQuAo4AVif5+yRv7Wiy3edxUb8kSeoZjRf1V9Va4ArgI8CZwLVJfpTkHZ0KJ0mS1A+ariE7KcmngTXAm4HFVXX86Pef7mA+SZKkntf0KsvrgM8DH62qZ7fvrKrHklzRkWSSJEl9omlB9jbg2araCpDkVcDMqvpFVX2pY+kkSZL6QNOC7JvAW4CnR7f3A/4F+O1OhJL6Sa/cU837qUnSnmu6qH9mVW0vxhj9fr/ORJIkSeovTQuyZ5Kcun0jyWnAs7t5fUd5HzJJktRLmhZkfwF8OcmdSe4E/gG4rGOpxuF9yCRJUi9ptIasqu5O8jrgOCDAj6rqxY4mk9RVemUtHLgeTtLUm8jDxU8HBkfbnJKEqrqpI6kkSZL6SKOCLMmXgKOAe4Gto7sLsCCTJEnaS01HyIaABVVVnQwjSZLUj5ou6n8A+I1OBpEkSepXTUfI5gA/TPJ94PntO6vqnI6kkiRJ6iNNC7KrOhlCkiSpnzW97cW3k/wmcExVfTPJfsBAZ6NJkiT1h0ZryJJcAnwF+NzorsOBFR3KJEmS1FeaLur/IPA7wJMAVbUWOLRTocbjo5MkSVIvabqG7PmqeiEJAElmMHIfslZU1Upg5dDQ0CVtZZDUu3zqgKSp1rQg+3aSjwKzkrwVuBRY2blYkqTJ0CvFpYWlel3TKcvLgU3A/cCfArcDV3QqlCRJUj9pepXlNuDzo1+SJEmaRE2fZfkwO1kzVlVHTnoiSZKkPjORZ1luNxN4N3DI5MeRJEnqP43WkFXV5jFfP6uqzwBv7mw0SZKk/tB0yvLUMZuvYmTE7ICOJJIkSeozTacsPzXm+5eADcB7Jj2NJElSH2p6leVZnQ4iSZLUr5pOWX54d8er6prJiSNJktR/JnKV5enAbaPbi4FVwKOdCCVJktRPmhZkc4BTq+opgCRXAV+uqj/pVDBJkqR+0fTRSfOAF8ZsvwAMTnaYJOcl+XySf0ry+5P9/pIkSdNR04LsS8D3k1yV5OPA94CbmjRMckOSjUke2GH/oiQ/TrIuyeUAVbWiqi4B/jPwR43/KyRJkrpY0xvD/jfgA8B/AP8H+EBV/V8Nz3EjsGjsjiQDwPXA2cAC4IIkC8a85IrR45IkST2v6QgZwH7Ak1X1N8BwkvlNGlXVKuCJHXafAayrqvVV9QJwC3BuRvw18LWq+rcJZJMkSepajQqy0WnKjwB/ObprH+Dv9uK8h/PKKzSHR/d9CHgL8K4kS3eRZUmS1UlWb9q0aS8iSJIkTQ9Nr7I8HzgF+DeAqnosyd48Oik72VdVdS1w7e4aVtVyYDnA0NBQ7UUGSZKkaaHplOULVVVAAST5tb087zBwxJjtucBje/mekiRJXalpQXZrks8Br0lyCfBN4PN7cd67gWOSzE+yL/BefnnT2XElWZxk+ZYtW/YigiRJ0vQwbkGWJMA/AF8B/hE4Driyqv7vJidIcjPwXeC4JMNJLq6ql4DLgK8Da4Bbq+rBpqGramVVLTnooIOaNpEkSZq2xl1DVlWVZEVVnQZ8Y6InqKoLdrH/duD2ib6fJElSr2k6ZXlXktM7mmQCnLKUJEm9pGlBdhYjRdlPktyX5P4k93Uy2O44ZSlJknrJbqcsk8yrqkcYuaO+JEmSOmC8EbIVAFX1U+Caqvrp2K+Op9sFpywlSVIvGa8gG3sD1yM7GWQinLKUJEm9ZLyrLGsX30uSNGXWvO74tiNMmuN/tKbtCJqGxivITk7yJCMjZbNGv2d0u6rqwI6mkyRJ6gO7LciqamCqgkxEksXA4qOPPrrtKJIkSXut6W0vphXXkEmSpF7SlQWZJElSL7EgkyRJapkFmSRJUsu6siDzxrCSJKmXdGVB5qJ+SZLUS7qyIJMkSeolFmSSJEktsyCTJElqmQWZJElSy7qyIPMqS0mS1Eu6siDzKktJktRLurIgkyRJ6iUWZJIkSS2zIJMkSWqZBZkkSVLLLMgkSZJa1pUFmbe9kCRJvaQrCzJveyFJknpJVxZkkiRJvcSCTJIkqWUz2g4gSVI/WfO649uOMGmO/9GatiP0DEfIJEmSWmZBJkmS1DILMkmSpJa5hkySJO0R18NNHkfIJEmSWmZBJkmS1LKuLMh8dJIkSeolXVmQ+egkSZLUS7qyIJMkSeolqaq2M+yxJJuAn3b4NHOAxzt8Dk2c/TL92CfTk/0y/dgn09NU9MtvVtVrd3agqwuyqZBkdVUNtZ1Dr2S/TD/2yfRkv0w/9sn01Ha/OGUpSZLUMgsySZKkllmQjW952wG0U/bL9GOfTE/2y/Rjn0xPrfaLa8gkSZJa5giZJElSyyzIRiVZlOTHSdYluXwnx5Pk2tHj9yU5tY2c/aRBn1w02hf3JflOkpPbyNlvxuuXMa87PcnWJO+aynz9qEmfJHlTknuTPJjk21OdsR81+DfsoCQrk/z7aL98oI2c/STJDUk2JnlgF8db+6y3IAOSDADXA2cDC4ALkizY4WVnA8eMfi0B/nZKQ/aZhn3yMHBmVZ0EfBLXZXRcw37Z/rq/Br4+tQn7T5M+SfIa4LPAOVV1AvDuqc7Zbxr+rnwQ+GFVnQy8CfhUkn2nNGj/uRFYtJvjrX3WW5CNOANYV1Xrq+oF4Bbg3B1ecy5wU424C3hNksOmOmgfGbdPquo7VfUfo5t3AXOnOGM/avK7AvAh4B+BjVMZrk816ZMLga9W1SMAVWW/dF6TfinggCQB9geeAF6a2pj9papWMfJz3pXWPustyEYcDjw6Znt4dN9EX6PJM9Gf98XA1zqaSNCgX5IcDpwPLJvCXP2sye/KscDBSe5Ick+S909Zuv7VpF+uA44HHgPuB/68qrZNTTztQmuf9TOm4iRdIDvZt+Plp01eo8nT+Oed5CxGCrI3djSRoFm/fAb4SFVtHfnDXx3WpE9mAKcBvwfMAr6b5K6qeqjT4fpYk375A+Be4M3AUcA3ktxZVU92OJt2rbXPeguyEcPAEWO25zLyF8tEX6PJ0+jnneQk4AvA2VW1eYqy9bMm/TIE3DJajM0B3pbkpapaMSUJ+0/Tf78er6pngGeSrAJOBizIOqdJv3wAuLpG7j+1LsnDwOuA709NRO1Ea5/1TlmOuBs4Jsn80QWV7wVu2+E1twHvH70C47eALVX186kO2kfG7ZMk84CvAu/zL/0pM26/VNX8qhqsqkHgK8ClFmMd1eTfr38CfjfJjCT7AW8A1kxxzn7TpF8eYWTUkiS/DhwHrJ/SlNpRa5/1jpABVfVSkssYuSJsALihqh5MsnT0+DLgduBtwDrgF4z8ZaMOadgnVwKzgc+Ojsa85AN7O6thv2gKNemTqlqT5J+B+4BtwBeqaqeX/WtyNPxd+SRwY5L7GZkq+0hVPd5a6D6Q5GZGrmidk2QY+DiwD7T/We+d+iVJklrmlKUkSVLLLMgkSZJaZkEmSZLUMgsySZKkllmQSZIktcyCTJIkqWUWZJIkSS2zIJMkSWrZ/w9u7rQWuousSwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.loc[~df1['Low_transit_flag_dist'], ['D5DR', 'D5DRI', 'D5DE', 'D5DEI']].plot(\n",
    "    subplots = True, kind = 'hist', figsize = (10, 10), \n",
    "    sharex = False, logy = True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.loc[df1['Low_transit_flag_dist'], d5cols] = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Scale variables to percentages / more normal distributions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Area (Water, Land, Unprotected relative to total)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1[['Pct_Water', 'Pct_Land', 'Pct_Unpr']] = df1[['Ac_Water', 'Ac_Land', 'Ac_Unpr']].div(df1['Ac_Total'], axis = 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Log Acreage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1['Log_Acres'] = np.log1p(df1['Ac_Total'])\n",
    "df1['Log_Acres'].hist();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Log Population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ZQ9/2xzqUH5lm++3A9g71Q8D1s+pdRERcUPlGbkRERRL6EREVSehHRFQkoR8RUZGEfkRERRL6EREVmctv70TEgCyf9HMIW1ZPDOwnEmJhyZF+RERFEvoRERVJ6EdEVCShHxFRkYR+RERFEvoRERVJ6EdEVCShHxFRkYR+RERFurly1leBO4DTtq8vtauB/w0sp3XlrP9s+42ybhtwH3AO+H3bf1HqN/LPV856AnjA9pQXR4+IOG/yN5Dbzfe3kU/suH3ennsQujnSfxRYN6m2FThgeyVwoDxG0ipgI3BdafOwpEWlzU5glNZ1c1d2eM6IiJhnM4a+7aeBn04qrwd2l+XdwIa2+h7bZ22/AhwH1pQLqV9p+5lydP9YW5uIiOiTXn9wbcj2KQDbpyRdW+pLgWfbthsrtTfL8uR6R5JGab0rYGhoiGaz2VMnx8fHe267kNU6bqhn7FtWT7zt8dDid9ZqMd9jf7f+PfX6t36hf2VTHWqept6R7V3ALoCRkRE3Go2eOtNsNum17UJW67ihnrFPnsPesnqCB4/U+aO58z32E3c15u2556LXv/Vez955vUzZUO5Pl/oYsKxtu2HgZKkPd6hHREQf9Rr6+4FNZXkTsK+tvlHSZZJW0PrA9mCZCjojaa0kAfe0tYmIiD7p5pTNbwAN4BpJY8BngB3AXkn3Aa8CdwLYPippL/AiMAFstn2uPNX9/PMpm0+WW0RE9NGMoW/7Y1OsumWK7bcD2zvUDwHXz6p3ERFxQeUbuRERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREXmFPqSTkg6Iul5SYdK7WpJT0l6udxf1bb9NknHJb0k6ba5dj4iImbnQhzp32z7Btsj5fFW4IDtlcCB8hhJq4CNwHXAOuBhSYsuwP4jIqJL8zG9sx7YXZZ3Axva6ntsn7X9CnAcWDMP+4+IiCnMNfQN/KWkw5JGS23I9imAcn9tqS8FftzWdqzUIiKiT2a8MPoMbrJ9UtK1wFOSfjTNtupQc8cNW/+AjAIMDQ3RbDZ76tz4+HjPbReyWscN9Yx9y+qJtz0eWvzOWi3me+zv1r+nXv/W5xT6tk+W+9OSvkNruuZ1SUtsn5K0BDhdNh8DlrU1HwZOTvG8u4BdACMjI240Gj31r9ls0mvbhazWcUM9Y7936+Nve7xl9QQPHpnrMdzCNN9jP3FXY96eey56/VvveXpH0uWSfvX8MvAfgReA/cCmstkmYF9Z3g9slHSZpBXASuBgr/uPiIjZm8s/j0PAdySdf57/ZfvPJf0NsFfSfcCrwJ0Ato9K2gu8CEwAm22fm1PvIyJiVnoOfdt/D3ywQ/0nwC1TtNkObO91nxERMTf5Rm5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFUnoR0RUJKEfEVGROi+qGRHRpeWTrkfcLyd23D4vz9v30Je0DvgTYBHwFds7+t2HiAthUGEQMRd9nd6RtAj4EvA7wCrgY5JW9bMPERE16/eR/hrgeLm+LpL2AOtpXSw9oiftR9xbVk9wb47AI6Yk2/3bmfSfgHW2/2t5fDfwb21/ctJ2o8BoefibwEs97vIa4B97bLuQ1TpuqHfstY4b6h37TOP+l7bfP7nY7yN9dai9418d27uAXXPemXTI9shcn2ehqXXcUO/Yax031Dv2Xsfd71M2x4BlbY+HgZN97kNERLX6Hfp/A6yUtELSvwA2Avv73IeIiGr1dXrH9oSkTwJ/QeuUza/aPjqPu5zzFNECVeu4od6x1zpuqHfsPY27rx/kRkTEYOVnGCIiKpLQj4ioyEUZ+pLWSXpJ0nFJWwfdn36RtEzS9yQdk3RU0gOD7lM/SVok6YeSvjvovvSTpPdJ+qakH5XX/t8Nuk/9IOm/l7/zFyR9Q9J7B92n+SLpq5JOS3qhrXa1pKckvVzur+rmuS660K/8px4mgC22fwtYC2yuaOwADwDHBt2JAfgT4M9t/2vgg1Tw30DSUuD3gRHb19M6MWTjYHs1rx4F1k2qbQUO2F4JHCiPZ3TRhT5tP/Vg+5+A8z/1cNGzfcr2c2X5DK3/+ZcOtlf9IWkYuB34yqD70k+SrgT+A/AIgO1/sv2zgXaqfy4BFku6BPgVLuLv/Nh+GvjppPJ6YHdZ3g1s6Oa5LsbQXwr8uO3xGJUEXztJy4EPAT8YcFf65Y+BPwDeGnA/+u1fAf8A/M8ytfUVSZcPulPzzfZrwOeBV4FTwM9t/+Vge9V3Q7ZPQeuAD7i2m0YXY+h39VMPFzNJVwDfAj5l+xeD7s98k3QHcNr24UH3ZQAuAf4NsNP2h4Bf0uXb/IWszF+vB1YAHwAul/R7g+3VwnAxhn7VP/Ug6VJagf91298edH/65CbgdyWdoDWd92FJXxtsl/pmDBizff4d3Tdp/SNwsbsVeMX2P9h+E/g28O8H3Kd+e13SEoByf7qbRhdj6Ff7Uw+SRGtu95jtLwy6P/1ie5vtYdvLab3ef227iqM+2/8X+LGk3yylW6jjp8pfBdZK+pXyd38LFXyAPcl+YFNZ3gTs66bRRXe5xAH81MO7yU3A3cARSc+X2qdtPzG4LkUf/Dfg6+Ug5++B/zLg/sw72z+Q9E3gOVpnrf2Qi/jnGCR9A2gA10gaAz4D7AD2SrqP1j+Cd3b1XPkZhoiIelyM0zsRETGFhH5EREUS+hERFUnoR0RUJKEfEVGRhH5EREUS+hERFfl/iNeqY5p68G8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df['TotPop'].hist()\n",
    "df1['log_TotPop'] = np.log1p(df1['TotPop'])\n",
    "df1['log_TotPop'].hist();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Housing Occupancy Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>pm_2.5</th>\n",
       "      <th>temp_f</th>\n",
       "      <th>model</th>\n",
       "      <th>hidden</th>\n",
       "      <th>flagged</th>\n",
       "      <th>downgraded</th>\n",
       "      <th>age</th>\n",
       "      <th>is_owner</th>\n",
       "      <th>1week_avg</th>\n",
       "      <th>fips_id</th>\n",
       "      <th>STATEFP</th>\n",
       "      <th>COUNTYFP</th>\n",
       "      <th>TRACTCE</th>\n",
       "      <th>BLKGRPCE</th>\n",
       "      <th>CSA</th>\n",
       "      <th>CSA_Name</th>\n",
       "      <th>CBSA</th>\n",
       "      <th>CBSA_Name</th>\n",
       "      <th>CBSA_POP</th>\n",
       "      <th>CBSA_EMP</th>\n",
       "      <th>CBSA_WRK</th>\n",
       "      <th>Ac_Total</th>\n",
       "      <th>Ac_Water</th>\n",
       "      <th>Ac_Land</th>\n",
       "      <th>Ac_Unpr</th>\n",
       "      <th>TotPop</th>\n",
       "      <th>CountHU</th>\n",
       "      <th>HH</th>\n",
       "      <th>P_WrkAge</th>\n",
       "      <th>Pct_AO0</th>\n",
       "      <th>Pct_AO1</th>\n",
       "      <th>Pct_AO2p</th>\n",
       "      <th>Workers</th>\n",
       "      <th>R_LowWageWk</th>\n",
       "      <th>R_MedWageWk</th>\n",
       "      <th>R_HiWageWk</th>\n",
       "      <th>R_PCTLOWWAGE</th>\n",
       "      <th>TotEmp</th>\n",
       "      <th>E5_Ret</th>\n",
       "      <th>E5_Off</th>\n",
       "      <th>E5_Ind</th>\n",
       "      <th>E5_Svc</th>\n",
       "      <th>E5_Ent</th>\n",
       "      <th>E8_Ret</th>\n",
       "      <th>E8_off</th>\n",
       "      <th>E8_Ind</th>\n",
       "      <th>E8_Svc</th>\n",
       "      <th>E8_Ent</th>\n",
       "      <th>E8_Ed</th>\n",
       "      <th>E8_Hlth</th>\n",
       "      <th>E8_Pub</th>\n",
       "      <th>E_LowWageWk</th>\n",
       "      <th>E_MedWageWk</th>\n",
       "      <th>E_HiWageWk</th>\n",
       "      <th>E_PctLowWage</th>\n",
       "      <th>D1A</th>\n",
       "      <th>D1B</th>\n",
       "      <th>D1C</th>\n",
       "      <th>D1C5_RET</th>\n",
       "      <th>D1C5_OFF</th>\n",
       "      <th>D1C5_IND</th>\n",
       "      <th>D1C5_SVC</th>\n",
       "      <th>D1C5_ENT</th>\n",
       "      <th>D1C8_RET</th>\n",
       "      <th>D1C8_OFF</th>\n",
       "      <th>D1C8_IND</th>\n",
       "      <th>D1C8_SVC</th>\n",
       "      <th>D1C8_ENT</th>\n",
       "      <th>D1C8_ED</th>\n",
       "      <th>D1C8_HLTH</th>\n",
       "      <th>D1C8_PUB</th>\n",
       "      <th>D1D</th>\n",
       "      <th>D2A_JPHH</th>\n",
       "      <th>D2B_E5MIX</th>\n",
       "      <th>D2B_E5MIXA</th>\n",
       "      <th>D2B_E8MIX</th>\n",
       "      <th>D2B_E8MIXA</th>\n",
       "      <th>D2A_EPHHM</th>\n",
       "      <th>D2C_TRPMX1</th>\n",
       "      <th>D2C_TRPMX2</th>\n",
       "      <th>D2C_TRIPEQ</th>\n",
       "      <th>D2R_JOBPOP</th>\n",
       "      <th>D2R_WRKEMP</th>\n",
       "      <th>D2A_WRKEMP</th>\n",
       "      <th>D2C_WREMLX</th>\n",
       "      <th>D3A</th>\n",
       "      <th>D3AAO</th>\n",
       "      <th>D3AMM</th>\n",
       "      <th>D3APO</th>\n",
       "      <th>D3B</th>\n",
       "      <th>D3BAO</th>\n",
       "      <th>D3BMM3</th>\n",
       "      <th>D3BMM4</th>\n",
       "      <th>D3BPO3</th>\n",
       "      <th>D3BPO4</th>\n",
       "      <th>D4A</th>\n",
       "      <th>D4B025</th>\n",
       "      <th>D4B050</th>\n",
       "      <th>D4C</th>\n",
       "      <th>D4D</th>\n",
       "      <th>D4E</th>\n",
       "      <th>D5AR</th>\n",
       "      <th>D5AE</th>\n",
       "      <th>D5BR</th>\n",
       "      <th>D5BE</th>\n",
       "      <th>D5CR</th>\n",
       "      <th>D5CRI</th>\n",
       "      <th>D5CE</th>\n",
       "      <th>D5CEI</th>\n",
       "      <th>D5DR</th>\n",
       "      <th>D5DRI</th>\n",
       "      <th>D5DE</th>\n",
       "      <th>D5DEI</th>\n",
       "      <th>D2A_Ranked</th>\n",
       "      <th>D2B_Ranked</th>\n",
       "      <th>D3B_Ranked</th>\n",
       "      <th>D4A_Ranked</th>\n",
       "      <th>NatWalkInd</th>\n",
       "      <th>Shape_Length</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>Low_transit_flag_dist</th>\n",
       "      <th>Low_transit_flag_freq</th>\n",
       "      <th>Pct_Water</th>\n",
       "      <th>Pct_Land</th>\n",
       "      <th>Pct_Unpr</th>\n",
       "      <th>Log_Acres</th>\n",
       "      <th>log_TotPop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3107</th>\n",
       "      <td>CSUStan Naraghi Roof</td>\n",
       "      <td>2.92</td>\n",
       "      <td>96.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>6.16</td>\n",
       "      <td>60990036053</td>\n",
       "      <td>6</td>\n",
       "      <td>99</td>\n",
       "      <td>3605</td>\n",
       "      <td>3</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>33700.0</td>\n",
       "      <td>Modesto, CA</td>\n",
       "      <td>539301</td>\n",
       "      <td>186753</td>\n",
       "      <td>213072</td>\n",
       "      <td>181.596014</td>\n",
       "      <td>6.354671</td>\n",
       "      <td>175.241343</td>\n",
       "      <td>175.241343</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237</td>\n",
       "      <td>56</td>\n",
       "      <td>78</td>\n",
       "      <td>103</td>\n",
       "      <td>0.236287</td>\n",
       "      <td>1750</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1708</td>\n",
       "      <td>19</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>19</td>\n",
       "      <td>1679</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>398</td>\n",
       "      <td>379</td>\n",
       "      <td>973</td>\n",
       "      <td>0.227429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022826</td>\n",
       "      <td>9.986228</td>\n",
       "      <td>0.131248</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.746558</td>\n",
       "      <td>0.108422</td>\n",
       "      <td>0.131248</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.159780</td>\n",
       "      <td>0.108422</td>\n",
       "      <td>9.581072</td>\n",
       "      <td>0.005706</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.986228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.118103</td>\n",
       "      <td>0.080618</td>\n",
       "      <td>0.134336</td>\n",
       "      <td>0.103973</td>\n",
       "      <td>0.118103</td>\n",
       "      <td>0.073021</td>\n",
       "      <td>0.081293</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.004561</td>\n",
       "      <td>0.238551</td>\n",
       "      <td>0.135429</td>\n",
       "      <td>0.421232</td>\n",
       "      <td>38.154980</td>\n",
       "      <td>2.736643</td>\n",
       "      <td>2.255862</td>\n",
       "      <td>33.162475</td>\n",
       "      <td>297.142667</td>\n",
       "      <td>10.956319</td>\n",
       "      <td>7.304212</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>306.776923</td>\n",
       "      <td>87.650549</td>\n",
       "      <td>506.94</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>25.564744</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>27707</td>\n",
       "      <td>32589</td>\n",
       "      <td>31738</td>\n",
       "      <td>24825</td>\n",
       "      <td>0.002667</td>\n",
       "      <td>0.472356</td>\n",
       "      <td>0.002813</td>\n",
       "      <td>0.528176</td>\n",
       "      <td>0.006157</td>\n",
       "      <td>0.605826</td>\n",
       "      <td>0.006000</td>\n",
       "      <td>0.518657</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>12.333333</td>\n",
       "      <td>3852.606004</td>\n",
       "      <td>7.349083e+05</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.034993</td>\n",
       "      <td>0.965007</td>\n",
       "      <td>0.965007</td>\n",
       "      <td>5.207276</td>\n",
       "      <td>1.609438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3108</th>\n",
       "      <td>CSUSTAN-CDC</td>\n",
       "      <td>37.38</td>\n",
       "      <td>83.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>37.29</td>\n",
       "      <td>60990036053</td>\n",
       "      <td>6</td>\n",
       "      <td>99</td>\n",
       "      <td>3605</td>\n",
       "      <td>3</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>33700.0</td>\n",
       "      <td>Modesto, CA</td>\n",
       "      <td>539301</td>\n",
       "      <td>186753</td>\n",
       "      <td>213072</td>\n",
       "      <td>181.596014</td>\n",
       "      <td>6.354671</td>\n",
       "      <td>175.241343</td>\n",
       "      <td>175.241343</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237</td>\n",
       "      <td>56</td>\n",
       "      <td>78</td>\n",
       "      <td>103</td>\n",
       "      <td>0.236287</td>\n",
       "      <td>1750</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1708</td>\n",
       "      <td>19</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>19</td>\n",
       "      <td>1679</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>398</td>\n",
       "      <td>379</td>\n",
       "      <td>973</td>\n",
       "      <td>0.227429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.022826</td>\n",
       "      <td>9.986228</td>\n",
       "      <td>0.131248</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.746558</td>\n",
       "      <td>0.108422</td>\n",
       "      <td>0.131248</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.159780</td>\n",
       "      <td>0.108422</td>\n",
       "      <td>9.581072</td>\n",
       "      <td>0.005706</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.986228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.118103</td>\n",
       "      <td>0.080618</td>\n",
       "      <td>0.134336</td>\n",
       "      <td>0.103973</td>\n",
       "      <td>0.118103</td>\n",
       "      <td>0.073021</td>\n",
       "      <td>0.081293</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.004561</td>\n",
       "      <td>0.238551</td>\n",
       "      <td>0.135429</td>\n",
       "      <td>0.421232</td>\n",
       "      <td>38.154980</td>\n",
       "      <td>2.736643</td>\n",
       "      <td>2.255862</td>\n",
       "      <td>33.162475</td>\n",
       "      <td>297.142667</td>\n",
       "      <td>10.956319</td>\n",
       "      <td>7.304212</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>306.776923</td>\n",
       "      <td>87.650549</td>\n",
       "      <td>506.94</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>25.564744</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>27707</td>\n",
       "      <td>32589</td>\n",
       "      <td>31738</td>\n",
       "      <td>24825</td>\n",
       "      <td>0.002667</td>\n",
       "      <td>0.472356</td>\n",
       "      <td>0.002813</td>\n",
       "      <td>0.528176</td>\n",
       "      <td>0.006157</td>\n",
       "      <td>0.605826</td>\n",
       "      <td>0.006000</td>\n",
       "      <td>0.518657</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>12.333333</td>\n",
       "      <td>3852.606004</td>\n",
       "      <td>7.349083e+05</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.034993</td>\n",
       "      <td>0.965007</td>\n",
       "      <td>0.965007</td>\n",
       "      <td>5.207276</td>\n",
       "      <td>1.609438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6058</th>\n",
       "      <td>GEA-SCLA</td>\n",
       "      <td>0.00</td>\n",
       "      <td>89.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>4.03</td>\n",
       "      <td>60719802001</td>\n",
       "      <td>6</td>\n",
       "      <td>71</td>\n",
       "      <td>980200</td>\n",
       "      <td>1</td>\n",
       "      <td>348.0</td>\n",
       "      <td>Los Angeles-Long Beach, CA</td>\n",
       "      <td>40140.0</td>\n",
       "      <td>Riverside-San Bernardino-Ontario, CA</td>\n",
       "      <td>4518699</td>\n",
       "      <td>1439654</td>\n",
       "      <td>1749931</td>\n",
       "      <td>4806.163694</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4806.163694</td>\n",
       "      <td>4788.248289</td>\n",
       "      <td>3900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.973</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>997</td>\n",
       "      <td>256</td>\n",
       "      <td>395</td>\n",
       "      <td>346</td>\n",
       "      <td>0.256770</td>\n",
       "      <td>1684</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1478</td>\n",
       "      <td>194</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1478</td>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>106</td>\n",
       "      <td>513</td>\n",
       "      <td>1065</td>\n",
       "      <td>0.062945</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.814494</td>\n",
       "      <td>0.351694</td>\n",
       "      <td>0.002506</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.308672</td>\n",
       "      <td>0.040516</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002506</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.308672</td>\n",
       "      <td>0.038427</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002088</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.351694</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.362922</td>\n",
       "      <td>0.247733</td>\n",
       "      <td>0.304482</td>\n",
       "      <td>0.202988</td>\n",
       "      <td>0.362922</td>\n",
       "      <td>0.416093</td>\n",
       "      <td>0.108367</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.603152</td>\n",
       "      <td>0.743752</td>\n",
       "      <td>0.592043</td>\n",
       "      <td>0.665007</td>\n",
       "      <td>4.845223</td>\n",
       "      <td>0.231898</td>\n",
       "      <td>0.553534</td>\n",
       "      <td>4.059791</td>\n",
       "      <td>12.298740</td>\n",
       "      <td>0.798974</td>\n",
       "      <td>2.396922</td>\n",
       "      <td>1.065299</td>\n",
       "      <td>7.856578</td>\n",
       "      <td>4.394357</td>\n",
       "      <td>2000.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.133162</td>\n",
       "      <td>0.000256</td>\n",
       "      <td>8500</td>\n",
       "      <td>12698</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>0.055174</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>0.088749</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3.333333</td>\n",
       "      <td>24599.890300</td>\n",
       "      <td>1.945027e+07</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.996272</td>\n",
       "      <td>8.477863</td>\n",
       "      <td>8.268988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7242</th>\n",
       "      <td>Little Holmby</td>\n",
       "      <td>0.69</td>\n",
       "      <td>87.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>6.17</td>\n",
       "      <td>60372653011</td>\n",
       "      <td>6</td>\n",
       "      <td>37</td>\n",
       "      <td>265301</td>\n",
       "      <td>1</td>\n",
       "      <td>348.0</td>\n",
       "      <td>Los Angeles-Long Beach, CA</td>\n",
       "      <td>31080.0</td>\n",
       "      <td>Los Angeles-Long Beach-Anaheim, CA</td>\n",
       "      <td>13262234</td>\n",
       "      <td>6249699</td>\n",
       "      <td>5825012</td>\n",
       "      <td>394.324898</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>394.324898</td>\n",
       "      <td>361.705600</td>\n",
       "      <td>11235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.463</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1120</td>\n",
       "      <td>235</td>\n",
       "      <td>280</td>\n",
       "      <td>605</td>\n",
       "      <td>0.209821</td>\n",
       "      <td>9673</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>9504</td>\n",
       "      <td>111</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>443</td>\n",
       "      <td>111</td>\n",
       "      <td>0</td>\n",
       "      <td>9061</td>\n",
       "      <td>0</td>\n",
       "      <td>818</td>\n",
       "      <td>996</td>\n",
       "      <td>7859</td>\n",
       "      <td>0.084565</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.061172</td>\n",
       "      <td>26.742743</td>\n",
       "      <td>0.033176</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.127175</td>\n",
       "      <td>26.275512</td>\n",
       "      <td>0.306879</td>\n",
       "      <td>0.033176</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.127175</td>\n",
       "      <td>1.224753</td>\n",
       "      <td>0.306879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.050760</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>26.742743</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.073809</td>\n",
       "      <td>0.063576</td>\n",
       "      <td>0.178600</td>\n",
       "      <td>0.138232</td>\n",
       "      <td>0.073809</td>\n",
       "      <td>0.051102</td>\n",
       "      <td>0.055175</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.925292</td>\n",
       "      <td>0.207542</td>\n",
       "      <td>0.115786</td>\n",
       "      <td>0.413039</td>\n",
       "      <td>43.030542</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.158233</td>\n",
       "      <td>40.872308</td>\n",
       "      <td>716.008148</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>19.476325</td>\n",
       "      <td>14.607244</td>\n",
       "      <td>740.100362</td>\n",
       "      <td>194.763253</td>\n",
       "      <td>658.49</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>106.67</td>\n",
       "      <td>173.128302</td>\n",
       "      <td>0.009494</td>\n",
       "      <td>295560</td>\n",
       "      <td>224932</td>\n",
       "      <td>238786</td>\n",
       "      <td>132664</td>\n",
       "      <td>0.000119</td>\n",
       "      <td>0.431814</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.437447</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.200037</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>0.132401</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>14</td>\n",
       "      <td>11.833333</td>\n",
       "      <td>6253.057077</td>\n",
       "      <td>1.595809e+06</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.917278</td>\n",
       "      <td>5.979708</td>\n",
       "      <td>9.326878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7408</th>\n",
       "      <td>Main Lodge Patrol</td>\n",
       "      <td>0.58</td>\n",
       "      <td>59.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>0.46</td>\n",
       "      <td>60510002009</td>\n",
       "      <td>6</td>\n",
       "      <td>51</td>\n",
       "      <td>200</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13632.046160</td>\n",
       "      <td>2.811010</td>\n",
       "      <td>13629.235150</td>\n",
       "      <td>6.021680</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>36</td>\n",
       "      <td>12</td>\n",
       "      <td>0.448276</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006383</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001394</td>\n",
       "      <td>0.004989</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004989</td>\n",
       "      <td>0.001394</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006383</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.757218</td>\n",
       "      <td>0.326116</td>\n",
       "      <td>0.757218</td>\n",
       "      <td>0.252406</td>\n",
       "      <td>0.757218</td>\n",
       "      <td>0.252356</td>\n",
       "      <td>0.280944</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022989</td>\n",
       "      <td>0.376434</td>\n",
       "      <td>7.514797</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.579883</td>\n",
       "      <td>6.934914</td>\n",
       "      <td>20.184235</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.756630</td>\n",
       "      <td>0.422621</td>\n",
       "      <td>20.238847</td>\n",
       "      <td>3.756630</td>\n",
       "      <td>2000.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.33</td>\n",
       "      <td>0.250286</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>283</td>\n",
       "      <td>89</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5.833333</td>\n",
       "      <td>40392.664790</td>\n",
       "      <td>5.516814e+07</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000206</td>\n",
       "      <td>0.999794</td>\n",
       "      <td>0.000442</td>\n",
       "      <td>9.520252</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7608</th>\n",
       "      <td>Metropolitan Golf Links</td>\n",
       "      <td>35.30</td>\n",
       "      <td>77.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>21.24</td>\n",
       "      <td>60014090004</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>409000</td>\n",
       "      <td>4</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>3284.545615</td>\n",
       "      <td>652.595301</td>\n",
       "      <td>2631.950315</td>\n",
       "      <td>2630.342600</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4141</td>\n",
       "      <td>0</td>\n",
       "      <td>296</td>\n",
       "      <td>3597</td>\n",
       "      <td>191</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>296</td>\n",
       "      <td>3597</td>\n",
       "      <td>155</td>\n",
       "      <td>57</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>653</td>\n",
       "      <td>1459</td>\n",
       "      <td>2029</td>\n",
       "      <td>0.157691</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.574320</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.112533</td>\n",
       "      <td>1.367502</td>\n",
       "      <td>0.072614</td>\n",
       "      <td>0.021670</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.112533</td>\n",
       "      <td>1.367502</td>\n",
       "      <td>0.058928</td>\n",
       "      <td>0.021670</td>\n",
       "      <td>0.013306</td>\n",
       "      <td>0.000380</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.574320</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.369195</td>\n",
       "      <td>0.318007</td>\n",
       "      <td>0.298723</td>\n",
       "      <td>0.257396</td>\n",
       "      <td>0.369195</td>\n",
       "      <td>0.653379</td>\n",
       "      <td>0.535962</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.234823</td>\n",
       "      <td>2.039153</td>\n",
       "      <td>0.388665</td>\n",
       "      <td>3.807005</td>\n",
       "      <td>11.676573</td>\n",
       "      <td>5.592811</td>\n",
       "      <td>2.431657</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>11.428787</td>\n",
       "      <td>2.431657</td>\n",
       "      <td>2000.00</td>\n",
       "      <td>0.046790</td>\n",
       "      <td>0.162232</td>\n",
       "      <td>31.33</td>\n",
       "      <td>7.618381</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>133669</td>\n",
       "      <td>110644</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000395</td>\n",
       "      <td>0.481628</td>\n",
       "      <td>0.000397</td>\n",
       "      <td>0.562744</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3.666667</td>\n",
       "      <td>19809.830200</td>\n",
       "      <td>1.329237e+07</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>0.198687</td>\n",
       "      <td>0.801313</td>\n",
       "      <td>0.800824</td>\n",
       "      <td>8.097288</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7981</th>\n",
       "      <td>Oakland Coliseum</td>\n",
       "      <td>39.39</td>\n",
       "      <td>76.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>22.42</td>\n",
       "      <td>60014090002</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>409000</td>\n",
       "      <td>2</td>\n",
       "      <td>488.0</td>\n",
       "      <td>San Jose-San Francisco-Oakland, CA</td>\n",
       "      <td>41860.0</td>\n",
       "      <td>San Francisco-Oakland-Berkeley, CA</td>\n",
       "      <td>4673221</td>\n",
       "      <td>2400290</td>\n",
       "      <td>2241034</td>\n",
       "      <td>1397.244988</td>\n",
       "      <td>432.035818</td>\n",
       "      <td>965.209171</td>\n",
       "      <td>613.289550</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14440</td>\n",
       "      <td>507</td>\n",
       "      <td>613</td>\n",
       "      <td>5494</td>\n",
       "      <td>5821</td>\n",
       "      <td>2005</td>\n",
       "      <td>507</td>\n",
       "      <td>475</td>\n",
       "      <td>5494</td>\n",
       "      <td>4249</td>\n",
       "      <td>2005</td>\n",
       "      <td>496</td>\n",
       "      <td>1076</td>\n",
       "      <td>138</td>\n",
       "      <td>3244</td>\n",
       "      <td>3701</td>\n",
       "      <td>7495</td>\n",
       "      <td>0.224654</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23.545159</td>\n",
       "      <td>0.826689</td>\n",
       "      <td>0.999528</td>\n",
       "      <td>8.958248</td>\n",
       "      <td>9.491438</td>\n",
       "      <td>3.269255</td>\n",
       "      <td>0.826689</td>\n",
       "      <td>0.774512</td>\n",
       "      <td>8.958248</td>\n",
       "      <td>6.928212</td>\n",
       "      <td>3.269255</td>\n",
       "      <td>0.808753</td>\n",
       "      <td>1.754473</td>\n",
       "      <td>0.225016</td>\n",
       "      <td>23.545159</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.782737</td>\n",
       "      <td>0.782737</td>\n",
       "      <td>0.762426</td>\n",
       "      <td>0.762426</td>\n",
       "      <td>0.782737</td>\n",
       "      <td>0.523171</td>\n",
       "      <td>0.501417</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000692</td>\n",
       "      <td>0.000346</td>\n",
       "      <td>0.368007</td>\n",
       "      <td>20.842700</td>\n",
       "      <td>3.414073</td>\n",
       "      <td>4.061706</td>\n",
       "      <td>13.366922</td>\n",
       "      <td>72.303664</td>\n",
       "      <td>7.956825</td>\n",
       "      <td>10.609099</td>\n",
       "      <td>5.304550</td>\n",
       "      <td>76.915970</td>\n",
       "      <td>8.619893</td>\n",
       "      <td>545.84</td>\n",
       "      <td>0.070807</td>\n",
       "      <td>0.267484</td>\n",
       "      <td>51.33</td>\n",
       "      <td>34.035317</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>180040</td>\n",
       "      <td>153098</td>\n",
       "      <td>173647</td>\n",
       "      <td>86974</td>\n",
       "      <td>0.000533</td>\n",
       "      <td>0.648709</td>\n",
       "      <td>0.000549</td>\n",
       "      <td>0.778669</td>\n",
       "      <td>0.000320</td>\n",
       "      <td>0.148899</td>\n",
       "      <td>0.000270</td>\n",
       "      <td>0.147160</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>10813.489700</td>\n",
       "      <td>5.654571e+06</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.309205</td>\n",
       "      <td>0.690795</td>\n",
       "      <td>0.438928</td>\n",
       "      <td>7.242973</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8504</th>\n",
       "      <td>Rivian El Segundo</td>\n",
       "      <td>6.71</td>\n",
       "      <td>88.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>16.43</td>\n",
       "      <td>60379800131</td>\n",
       "      <td>6</td>\n",
       "      <td>37</td>\n",
       "      <td>980013</td>\n",
       "      <td>1</td>\n",
       "      <td>348.0</td>\n",
       "      <td>Los Angeles-Long Beach, CA</td>\n",
       "      <td>31080.0</td>\n",
       "      <td>Los Angeles-Long Beach-Anaheim, CA</td>\n",
       "      <td>13262234</td>\n",
       "      <td>6249699</td>\n",
       "      <td>5825012</td>\n",
       "      <td>1311.738010</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1311.738010</td>\n",
       "      <td>1279.749100</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>321</td>\n",
       "      <td>54</td>\n",
       "      <td>70</td>\n",
       "      <td>197</td>\n",
       "      <td>0.168224</td>\n",
       "      <td>51851</td>\n",
       "      <td>2427</td>\n",
       "      <td>8540</td>\n",
       "      <td>22162</td>\n",
       "      <td>15711</td>\n",
       "      <td>3011</td>\n",
       "      <td>2427</td>\n",
       "      <td>8485</td>\n",
       "      <td>22162</td>\n",
       "      <td>14000</td>\n",
       "      <td>3011</td>\n",
       "      <td>238</td>\n",
       "      <td>1473</td>\n",
       "      <td>55</td>\n",
       "      <td>4057</td>\n",
       "      <td>7685</td>\n",
       "      <td>40109</td>\n",
       "      <td>0.078243</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>40.516536</td>\n",
       "      <td>1.896465</td>\n",
       "      <td>6.673183</td>\n",
       "      <td>17.317457</td>\n",
       "      <td>12.276625</td>\n",
       "      <td>2.352805</td>\n",
       "      <td>1.896465</td>\n",
       "      <td>6.630206</td>\n",
       "      <td>17.317457</td>\n",
       "      <td>10.939644</td>\n",
       "      <td>2.352805</td>\n",
       "      <td>0.185974</td>\n",
       "      <td>1.151007</td>\n",
       "      <td>0.042977</td>\n",
       "      <td>40.516536</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.826833</td>\n",
       "      <td>0.826833</td>\n",
       "      <td>0.699588</td>\n",
       "      <td>0.699588</td>\n",
       "      <td>0.826833</td>\n",
       "      <td>0.588843</td>\n",
       "      <td>0.547480</td>\n",
       "      <td>0.367879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012305</td>\n",
       "      <td>0.006191</td>\n",
       "      <td>0.370164</td>\n",
       "      <td>15.308178</td>\n",
       "      <td>1.692695</td>\n",
       "      <td>6.852019</td>\n",
       "      <td>6.763464</td>\n",
       "      <td>58.081354</td>\n",
       "      <td>7.806437</td>\n",
       "      <td>17.564483</td>\n",
       "      <td>9.270144</td>\n",
       "      <td>45.374914</td>\n",
       "      <td>6.830632</td>\n",
       "      <td>464.03</td>\n",
       "      <td>0.314533</td>\n",
       "      <td>0.880367</td>\n",
       "      <td>59.33</td>\n",
       "      <td>28.947244</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>275632</td>\n",
       "      <td>235227</td>\n",
       "      <td>185223</td>\n",
       "      <td>164876</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>0.402699</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.457468</td>\n",
       "      <td>0.000101</td>\n",
       "      <td>0.155166</td>\n",
       "      <td>0.000122</td>\n",
       "      <td>0.164549</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>14.333333</td>\n",
       "      <td>10465.185090</td>\n",
       "      <td>5.308528e+06</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.975613</td>\n",
       "      <td>7.179870</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name  pm_2.5  temp_f                   model  hidden  \\\n",
       "3107     CSUStan Naraghi Roof    2.92    96.0  PMS5003+PMS5003+BME280   False   \n",
       "3108              CSUSTAN-CDC   37.38    83.0  PMS5003+PMS5003+BME280   False   \n",
       "6058                 GEA-SCLA    0.00    89.0  PMS5003+PMS5003+BME280   False   \n",
       "7242            Little Holmby    0.69    87.0  PMS5003+PMS5003+BME280   False   \n",
       "7408        Main Lodge Patrol    0.58    59.0  PMS5003+PMS5003+BME280   False   \n",
       "7608  Metropolitan Golf Links   35.30    77.0  PMS5003+PMS5003+BME280   False   \n",
       "7981         Oakland Coliseum   39.39    76.0  PMS5003+PMS5003+BME280   False   \n",
       "8504        Rivian El Segundo    6.71    88.0  PMS5003+PMS5003+BME280   False   \n",
       "\n",
       "      flagged  downgraded  age  is_owner  1week_avg      fips_id  STATEFP  \\\n",
       "3107    False       False    1     False       6.16  60990036053        6   \n",
       "3108    False       False    1     False      37.29  60990036053        6   \n",
       "6058    False       False    1     False       4.03  60719802001        6   \n",
       "7242    False       False    0     False       6.17  60372653011        6   \n",
       "7408    False       False    1     False       0.46  60510002009        6   \n",
       "7608    False       False    1     False      21.24  60014090004        6   \n",
       "7981    False       False    1     False      22.42  60014090002        6   \n",
       "8504    False       False    0     False      16.43  60379800131        6   \n",
       "\n",
       "      COUNTYFP  TRACTCE  BLKGRPCE    CSA                            CSA_Name  \\\n",
       "3107        99     3605         3  488.0  San Jose-San Francisco-Oakland, CA   \n",
       "3108        99     3605         3  488.0  San Jose-San Francisco-Oakland, CA   \n",
       "6058        71   980200         1  348.0          Los Angeles-Long Beach, CA   \n",
       "7242        37   265301         1  348.0          Los Angeles-Long Beach, CA   \n",
       "7408        51      200         9    NaN                                 NaN   \n",
       "7608         1   409000         4  488.0  San Jose-San Francisco-Oakland, CA   \n",
       "7981         1   409000         2  488.0  San Jose-San Francisco-Oakland, CA   \n",
       "8504        37   980013         1  348.0          Los Angeles-Long Beach, CA   \n",
       "\n",
       "         CBSA                             CBSA_Name  CBSA_POP  CBSA_EMP  \\\n",
       "3107  33700.0                           Modesto, CA    539301    186753   \n",
       "3108  33700.0                           Modesto, CA    539301    186753   \n",
       "6058  40140.0  Riverside-San Bernardino-Ontario, CA   4518699   1439654   \n",
       "7242  31080.0    Los Angeles-Long Beach-Anaheim, CA  13262234   6249699   \n",
       "7408      NaN                                   NaN         0         0   \n",
       "7608  41860.0    San Francisco-Oakland-Berkeley, CA   4673221   2400290   \n",
       "7981  41860.0    San Francisco-Oakland-Berkeley, CA   4673221   2400290   \n",
       "8504  31080.0    Los Angeles-Long Beach-Anaheim, CA  13262234   6249699   \n",
       "\n",
       "      CBSA_WRK      Ac_Total    Ac_Water       Ac_Land      Ac_Unpr  TotPop  \\\n",
       "3107    213072    181.596014    6.354671    175.241343   175.241343       4   \n",
       "3108    213072    181.596014    6.354671    175.241343   175.241343       4   \n",
       "6058   1749931   4806.163694    0.000000   4806.163694  4788.248289    3900   \n",
       "7242   5825012    394.324898    0.000000    394.324898   361.705600   11235   \n",
       "7408         0  13632.046160    2.811010  13629.235150     6.021680       0   \n",
       "7608   2241034   3284.545615  652.595301   2631.950315  2630.342600       0   \n",
       "7981   2241034   1397.244988  432.035818    965.209171   613.289550       0   \n",
       "8504   5825012   1311.738010    0.000000   1311.738010  1279.749100       0   \n",
       "\n",
       "      CountHU   HH  P_WrkAge  Pct_AO0  Pct_AO1  Pct_AO2p  Workers  \\\n",
       "3107      0.0  0.0     0.750      0.0      0.0       0.0      237   \n",
       "3108      0.0  0.0     0.750      0.0      0.0       0.0      237   \n",
       "6058      0.0  0.0     0.973      0.0      0.0       0.0      997   \n",
       "7242      0.0  0.0     0.463      0.0      0.0       0.0     1120   \n",
       "7408      0.0  0.0     0.000      0.0      0.0       0.0        2   \n",
       "7608      0.0  0.0     0.000      0.0      0.0       0.0        0   \n",
       "7981      0.0  0.0     0.000      0.0      0.0       0.0        5   \n",
       "8504      0.0  0.0     0.000      0.0      0.0       0.0      321   \n",
       "\n",
       "      R_LowWageWk  R_MedWageWk  R_HiWageWk  R_PCTLOWWAGE  TotEmp  E5_Ret  \\\n",
       "3107           56           78         103      0.236287    1750      23   \n",
       "3108           56           78         103      0.236287    1750      23   \n",
       "6058          256          395         346      0.256770    1684      12   \n",
       "7242          235          280         605      0.209821    9673      12   \n",
       "7408            1            1           0      0.500000      87       0   \n",
       "7608            0            0           0      0.000000    4141       0   \n",
       "7981            0            3           2      0.000000   14440     507   \n",
       "8504           54           70         197      0.168224   51851    2427   \n",
       "\n",
       "      E5_Off  E5_Ind  E5_Svc  E5_Ent  E8_Ret  E8_off  E8_Ind  E8_Svc  E8_Ent  \\\n",
       "3107       0       0    1708      19      23       0       0      28      19   \n",
       "3108       0       0    1708      19      23       0       0      28      19   \n",
       "6058       0    1478     194       0      12       0    1478     184       0   \n",
       "7242       0      46    9504     111      12       0      46     443     111   \n",
       "7408       0       0      19      68       0       0       0       0      68   \n",
       "7608     296    3597     191      57       0     296    3597     155      57   \n",
       "7981     613    5494    5821    2005     507     475    5494    4249    2005   \n",
       "8504    8540   22162   15711    3011    2427    8485   22162   14000    3011   \n",
       "\n",
       "      E8_Ed  E8_Hlth  E8_Pub  E_LowWageWk  E_MedWageWk  E_HiWageWk  \\\n",
       "3107   1679        1       0          398          379         973   \n",
       "3108   1679        1       0          398          379         973   \n",
       "6058      0       10       0          106          513        1065   \n",
       "7242      0     9061       0          818          996        7859   \n",
       "7408     19        0       0           39           36          12   \n",
       "7608     35        1       0          653         1459        2029   \n",
       "7981    496     1076     138         3244         3701        7495   \n",
       "8504    238     1473      55         4057         7685       40109   \n",
       "\n",
       "      E_PctLowWage  D1A        D1B        D1C  D1C5_RET  D1C5_OFF   D1C5_IND  \\\n",
       "3107      0.227429  0.0   0.022826   9.986228  0.131248  0.000000   0.000000   \n",
       "3108      0.227429  0.0   0.022826   9.986228  0.131248  0.000000   0.000000   \n",
       "6058      0.062945  0.0   0.814494   0.351694  0.002506  0.000000   0.308672   \n",
       "7242      0.084565  0.0  31.061172  26.742743  0.033176  0.000000   0.127175   \n",
       "7408      0.448276  0.0   0.000000   0.006383  0.000000  0.000000   0.000000   \n",
       "7608      0.157691  0.0   0.000000   1.574320  0.000000  0.112533   1.367502   \n",
       "7981      0.224654  0.0   0.000000  23.545159  0.826689  0.999528   8.958248   \n",
       "8504      0.078243  0.0   0.000000  40.516536  1.896465  6.673183  17.317457   \n",
       "\n",
       "       D1C5_SVC  D1C5_ENT  D1C8_RET  D1C8_OFF   D1C8_IND   D1C8_SVC  D1C8_ENT  \\\n",
       "3107   9.746558  0.108422  0.131248  0.000000   0.000000   0.159780  0.108422   \n",
       "3108   9.746558  0.108422  0.131248  0.000000   0.000000   0.159780  0.108422   \n",
       "6058   0.040516  0.000000  0.002506  0.000000   0.308672   0.038427  0.000000   \n",
       "7242  26.275512  0.306879  0.033176  0.000000   0.127175   1.224753  0.306879   \n",
       "7408   0.001394  0.004989  0.000000  0.000000   0.000000   0.000000  0.004989   \n",
       "7608   0.072614  0.021670  0.000000  0.112533   1.367502   0.058928  0.021670   \n",
       "7981   9.491438  3.269255  0.826689  0.774512   8.958248   6.928212  3.269255   \n",
       "8504  12.276625  2.352805  1.896465  6.630206  17.317457  10.939644  2.352805   \n",
       "\n",
       "       D1C8_ED  D1C8_HLTH  D1C8_PUB        D1D  D2A_JPHH  D2B_E5MIX  \\\n",
       "3107  9.581072   0.005706  0.000000   9.986228       0.0   0.118103   \n",
       "3108  9.581072   0.005706  0.000000   9.986228       0.0   0.118103   \n",
       "6058  0.000000   0.002088  0.000000   0.351694       0.0   0.362922   \n",
       "7242  0.000000  25.050760  0.000000  26.742743       0.0   0.073809   \n",
       "7408  0.001394   0.000000  0.000000   0.006383       0.0   0.757218   \n",
       "7608  0.013306   0.000380  0.000000   1.574320       0.0   0.369195   \n",
       "7981  0.808753   1.754473  0.225016  23.545159       0.0   0.782737   \n",
       "8504  0.185974   1.151007  0.042977  40.516536       0.0   0.826833   \n",
       "\n",
       "      D2B_E5MIXA  D2B_E8MIX  D2B_E8MIXA  D2A_EPHHM  D2C_TRPMX1  D2C_TRPMX2  \\\n",
       "3107    0.080618   0.134336    0.103973   0.118103    0.073021    0.081293   \n",
       "3108    0.080618   0.134336    0.103973   0.118103    0.073021    0.081293   \n",
       "6058    0.247733   0.304482    0.202988   0.362922    0.416093    0.108367   \n",
       "7242    0.063576   0.178600    0.138232   0.073809    0.051102    0.055175   \n",
       "7408    0.326116   0.757218    0.252406   0.757218    0.252356    0.280944   \n",
       "7608    0.318007   0.298723    0.257396   0.369195    0.653379    0.535962   \n",
       "7981    0.782737   0.762426    0.762426   0.782737    0.523171    0.501417   \n",
       "8504    0.826833   0.699588    0.699588   0.826833    0.588843    0.547480   \n",
       "\n",
       "      D2C_TRIPEQ  D2R_JOBPOP  D2R_WRKEMP  D2A_WRKEMP  D2C_WREMLX        D3A  \\\n",
       "3107    0.367879    0.004561    0.238551    0.135429    0.421232  38.154980   \n",
       "3108    0.367879    0.004561    0.238551    0.135429    0.421232  38.154980   \n",
       "6058    0.367879    0.603152    0.743752    0.592043    0.665007   4.845223   \n",
       "7242    0.367879    0.925292    0.207542    0.115786    0.413039  43.030542   \n",
       "7408    0.367879    0.000000    0.000000    0.022989    0.376434   7.514797   \n",
       "7608    0.367879    0.000000    1.000000    0.000000    0.000000   6.234823   \n",
       "7981    0.367879    0.000000    0.000692    0.000346    0.368007  20.842700   \n",
       "8504    0.367879    0.000000    0.012305    0.006191    0.370164  15.308178   \n",
       "\n",
       "         D3AAO     D3AMM      D3APO         D3B      D3BAO     D3BMM3  \\\n",
       "3107  2.736643  2.255862  33.162475  297.142667  10.956319   7.304212   \n",
       "3108  2.736643  2.255862  33.162475  297.142667  10.956319   7.304212   \n",
       "6058  0.231898  0.553534   4.059791   12.298740   0.798974   2.396922   \n",
       "7242  0.000000  2.158233  40.872308  716.008148   0.000000  19.476325   \n",
       "7408  0.000000  0.579883   6.934914   20.184235   0.000000   3.756630   \n",
       "7608  2.039153  0.388665   3.807005   11.676573   5.592811   2.431657   \n",
       "7981  3.414073  4.061706  13.366922   72.303664   7.956825  10.609099   \n",
       "8504  1.692695  6.852019   6.763464   58.081354   7.806437  17.564483   \n",
       "\n",
       "         D3BMM4      D3BPO3      D3BPO4      D4A    D4B025    D4B050     D4C  \\\n",
       "3107   0.000000  306.776923   87.650549   506.94  0.000000  0.000000    7.00   \n",
       "3108   0.000000  306.776923   87.650549   506.94  0.000000  0.000000    7.00   \n",
       "6058   1.065299    7.856578    4.394357  2000.00  0.000000  0.000000    1.00   \n",
       "7242  14.607244  740.100362  194.763253   658.49  0.000000  0.000000  106.67   \n",
       "7408   0.422621   20.238847    3.756630  2000.00  0.000000  0.000000    5.33   \n",
       "7608   0.000000   11.428787    2.431657  2000.00  0.046790  0.162232   31.33   \n",
       "7981   5.304550   76.915970    8.619893   545.84  0.070807  0.267484   51.33   \n",
       "8504   9.270144   45.374914    6.830632   464.03  0.314533  0.880367   59.33   \n",
       "\n",
       "             D4D       D4E    D5AR    D5AE    D5BR    D5BE      D5CR  \\\n",
       "3107   25.564744  1.750000   27707   32589   31738   24825  0.002667   \n",
       "3108   25.564744  1.750000   27707   32589   31738   24825  0.002667   \n",
       "6058    0.133162  0.000256    8500   12698       0       0  0.000066   \n",
       "7242  173.128302  0.009494  295560  224932  238786  132664  0.000119   \n",
       "7408    0.250286  0.000000     283      89       0       0  0.000000   \n",
       "7608    7.618381  0.000000  133669  110644       0       0  0.000395   \n",
       "7981   34.035317  0.000000  180040  153098  173647   86974  0.000533   \n",
       "8504   28.947244  0.000000  275632  235227  185223  164876  0.000111   \n",
       "\n",
       "         D5CRI      D5CE     D5CEI      D5DR     D5DRI      D5DE     D5DEI  \\\n",
       "3107  0.472356  0.002813  0.528176  0.006157  0.605826  0.006000  0.518657   \n",
       "3108  0.472356  0.002813  0.528176  0.006157  0.605826  0.006000  0.518657   \n",
       "6058  0.055174  0.000093  0.088749  0.000000  0.000000  0.000000  0.000000   \n",
       "7242  0.431814  0.000103  0.437447  0.000130  0.200037  0.000098  0.132401   \n",
       "7408  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "7608  0.481628  0.000397  0.562744  0.000000  0.000000  0.000000  0.000000   \n",
       "7981  0.648709  0.000549  0.778669  0.000320  0.148899  0.000270  0.147160   \n",
       "8504  0.402699  0.000108  0.457468  0.000101  0.155166  0.000122  0.164549   \n",
       "\n",
       "      D2A_Ranked  D2B_Ranked  D3B_Ranked  D4A_Ranked  NatWalkInd  \\\n",
       "3107           2           2          20          15   12.333333   \n",
       "3108           2           2          20          15   12.333333   \n",
       "6058           6           2           5           1    3.333333   \n",
       "7242           1           2          20          14   11.833333   \n",
       "7408          18           3           6           1    5.833333   \n",
       "7608           7           3           5           1    3.666667   \n",
       "7981          18          18          12          15   15.000000   \n",
       "8504          19          15          10          16   14.333333   \n",
       "\n",
       "      Shape_Length    Shape_Area  Low_transit_flag_dist  \\\n",
       "3107   3852.606004  7.349083e+05                  False   \n",
       "3108   3852.606004  7.349083e+05                  False   \n",
       "6058  24599.890300  1.945027e+07                   True   \n",
       "7242   6253.057077  1.595809e+06                  False   \n",
       "7408  40392.664790  5.516814e+07                   True   \n",
       "7608  19809.830200  1.329237e+07                   True   \n",
       "7981  10813.489700  5.654571e+06                  False   \n",
       "8504  10465.185090  5.308528e+06                  False   \n",
       "\n",
       "      Low_transit_flag_freq  Pct_Water  Pct_Land  Pct_Unpr  Log_Acres  \\\n",
       "3107                  False   0.034993  0.965007  0.965007   5.207276   \n",
       "3108                  False   0.034993  0.965007  0.965007   5.207276   \n",
       "6058                  False   0.000000  1.000000  0.996272   8.477863   \n",
       "7242                  False   0.000000  1.000000  0.917278   5.979708   \n",
       "7408                  False   0.000206  0.999794  0.000442   9.520252   \n",
       "7608                  False   0.198687  0.801313  0.800824   8.097288   \n",
       "7981                  False   0.309205  0.690795  0.438928   7.242973   \n",
       "8504                  False   0.000000  1.000000  0.975613   7.179870   \n",
       "\n",
       "      log_TotPop  \n",
       "3107    1.609438  \n",
       "3108    1.609438  \n",
       "6058    8.268988  \n",
       "7242    9.326878  \n",
       "7408    0.000000  \n",
       "7608    0.000000  \n",
       "7981    0.000000  \n",
       "8504    0.000000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 8 rows with 0 house hold units\n",
    "with pd.option_context('display.max_columns', 200):\n",
    "    display(df1.query('CountHU == 0'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['Pct_HH_occupied'] = df1['HH'].div(df1['CountHU'], axis = 0).fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Diversity (D2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>D2A_JPHH</th>\n",
       "      <th>D2B_E5MIX</th>\n",
       "      <th>D2B_E5MIXA</th>\n",
       "      <th>D2B_E8MIX</th>\n",
       "      <th>D2B_E8MIXA</th>\n",
       "      <th>D2A_EPHHM</th>\n",
       "      <th>D2C_TRPMX1</th>\n",
       "      <th>D2C_TRPMX2</th>\n",
       "      <th>D2C_TRIPEQ</th>\n",
       "      <th>D2R_JOBPOP</th>\n",
       "      <th>D2R_WRKEMP</th>\n",
       "      <th>D2A_WRKEMP</th>\n",
       "      <th>D2C_WREMLX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.466063</td>\n",
       "      <td>0.917728</td>\n",
       "      <td>0.917728</td>\n",
       "      <td>0.891662</td>\n",
       "      <td>0.768304</td>\n",
       "      <td>0.866894</td>\n",
       "      <td>0.772433</td>\n",
       "      <td>0.830073</td>\n",
       "      <td>0.496555</td>\n",
       "      <td>0.740571</td>\n",
       "      <td>0.760994</td>\n",
       "      <td>0.614198</td>\n",
       "      <td>0.679905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22.464567</td>\n",
       "      <td>0.223268</td>\n",
       "      <td>0.192313</td>\n",
       "      <td>0.226667</td>\n",
       "      <td>0.195308</td>\n",
       "      <td>0.293581</td>\n",
       "      <td>0.223464</td>\n",
       "      <td>0.246951</td>\n",
       "      <td>0.373636</td>\n",
       "      <td>0.200378</td>\n",
       "      <td>0.059624</td>\n",
       "      <td>0.030728</td>\n",
       "      <td>0.379359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.246088</td>\n",
       "      <td>0.601312</td>\n",
       "      <td>0.601312</td>\n",
       "      <td>0.721792</td>\n",
       "      <td>0.675442</td>\n",
       "      <td>0.383994</td>\n",
       "      <td>0.444501</td>\n",
       "      <td>0.489292</td>\n",
       "      <td>0.345147</td>\n",
       "      <td>0.193783</td>\n",
       "      <td>0.395429</td>\n",
       "      <td>4.057803</td>\n",
       "      <td>0.046991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.246088</td>\n",
       "      <td>0.601312</td>\n",
       "      <td>0.601312</td>\n",
       "      <td>0.721792</td>\n",
       "      <td>0.675442</td>\n",
       "      <td>0.383994</td>\n",
       "      <td>0.444501</td>\n",
       "      <td>0.489292</td>\n",
       "      <td>0.345147</td>\n",
       "      <td>0.193783</td>\n",
       "      <td>0.395429</td>\n",
       "      <td>4.057803</td>\n",
       "      <td>0.046991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.629526</td>\n",
       "      <td>0.559777</td>\n",
       "      <td>0.559777</td>\n",
       "      <td>0.737556</td>\n",
       "      <td>0.737556</td>\n",
       "      <td>0.682299</td>\n",
       "      <td>0.605275</td>\n",
       "      <td>0.668630</td>\n",
       "      <td>0.457875</td>\n",
       "      <td>0.602782</td>\n",
       "      <td>0.867377</td>\n",
       "      <td>0.765812</td>\n",
       "      <td>0.791213</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9530</th>\n",
       "      <td>0.518968</td>\n",
       "      <td>0.552391</td>\n",
       "      <td>0.552391</td>\n",
       "      <td>0.527209</td>\n",
       "      <td>0.454271</td>\n",
       "      <td>0.527904</td>\n",
       "      <td>0.529933</td>\n",
       "      <td>0.581115</td>\n",
       "      <td>0.655780</td>\n",
       "      <td>0.482710</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.888889</td>\n",
       "      <td>0.894839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9532</th>\n",
       "      <td>0.450172</td>\n",
       "      <td>0.305470</td>\n",
       "      <td>0.305470</td>\n",
       "      <td>0.462165</td>\n",
       "      <td>0.432487</td>\n",
       "      <td>0.430894</td>\n",
       "      <td>0.447652</td>\n",
       "      <td>0.489364</td>\n",
       "      <td>0.865687</td>\n",
       "      <td>0.329353</td>\n",
       "      <td>0.745377</td>\n",
       "      <td>1.683206</td>\n",
       "      <td>0.504995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9533</th>\n",
       "      <td>0.535755</td>\n",
       "      <td>0.826411</td>\n",
       "      <td>0.826411</td>\n",
       "      <td>0.889763</td>\n",
       "      <td>0.832626</td>\n",
       "      <td>0.619911</td>\n",
       "      <td>0.615384</td>\n",
       "      <td>0.660931</td>\n",
       "      <td>0.931952</td>\n",
       "      <td>0.290194</td>\n",
       "      <td>0.519252</td>\n",
       "      <td>2.851695</td>\n",
       "      <td>0.156971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9534</th>\n",
       "      <td>1.726368</td>\n",
       "      <td>0.790146</td>\n",
       "      <td>0.790146</td>\n",
       "      <td>0.680833</td>\n",
       "      <td>0.680833</td>\n",
       "      <td>0.816222</td>\n",
       "      <td>0.602239</td>\n",
       "      <td>0.659063</td>\n",
       "      <td>0.449960</td>\n",
       "      <td>0.834135</td>\n",
       "      <td>0.772406</td>\n",
       "      <td>0.629203</td>\n",
       "      <td>0.690184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9536</th>\n",
       "      <td>0.686747</td>\n",
       "      <td>0.651526</td>\n",
       "      <td>0.651526</td>\n",
       "      <td>0.859461</td>\n",
       "      <td>0.804271</td>\n",
       "      <td>0.615444</td>\n",
       "      <td>0.632685</td>\n",
       "      <td>0.685767</td>\n",
       "      <td>0.632446</td>\n",
       "      <td>0.324324</td>\n",
       "      <td>0.564356</td>\n",
       "      <td>2.543860</td>\n",
       "      <td>0.213555</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6568 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       D2A_JPHH  D2B_E5MIX  D2B_E5MIXA  D2B_E8MIX  D2B_E8MIXA  D2A_EPHHM  \\\n",
       "0      1.466063   0.917728    0.917728   0.891662    0.768304   0.866894   \n",
       "1     22.464567   0.223268    0.192313   0.226667    0.195308   0.293581   \n",
       "4      0.246088   0.601312    0.601312   0.721792    0.675442   0.383994   \n",
       "8      0.246088   0.601312    0.601312   0.721792    0.675442   0.383994   \n",
       "12     1.629526   0.559777    0.559777   0.737556    0.737556   0.682299   \n",
       "...         ...        ...         ...        ...         ...        ...   \n",
       "9530   0.518968   0.552391    0.552391   0.527209    0.454271   0.527904   \n",
       "9532   0.450172   0.305470    0.305470   0.462165    0.432487   0.430894   \n",
       "9533   0.535755   0.826411    0.826411   0.889763    0.832626   0.619911   \n",
       "9534   1.726368   0.790146    0.790146   0.680833    0.680833   0.816222   \n",
       "9536   0.686747   0.651526    0.651526   0.859461    0.804271   0.615444   \n",
       "\n",
       "      D2C_TRPMX1  D2C_TRPMX2  D2C_TRIPEQ  D2R_JOBPOP  D2R_WRKEMP  D2A_WRKEMP  \\\n",
       "0       0.772433    0.830073    0.496555    0.740571    0.760994    0.614198   \n",
       "1       0.223464    0.246951    0.373636    0.200378    0.059624    0.030728   \n",
       "4       0.444501    0.489292    0.345147    0.193783    0.395429    4.057803   \n",
       "8       0.444501    0.489292    0.345147    0.193783    0.395429    4.057803   \n",
       "12      0.605275    0.668630    0.457875    0.602782    0.867377    0.765812   \n",
       "...          ...         ...         ...         ...         ...         ...   \n",
       "9530    0.529933    0.581115    0.655780    0.482710    0.941176    0.888889   \n",
       "9532    0.447652    0.489364    0.865687    0.329353    0.745377    1.683206   \n",
       "9533    0.615384    0.660931    0.931952    0.290194    0.519252    2.851695   \n",
       "9534    0.602239    0.659063    0.449960    0.834135    0.772406    0.629203   \n",
       "9536    0.632685    0.685767    0.632446    0.324324    0.564356    2.543860   \n",
       "\n",
       "      D2C_WREMLX  \n",
       "0       0.679905  \n",
       "1       0.379359  \n",
       "4       0.046991  \n",
       "8       0.046991  \n",
       "12      0.791213  \n",
       "...          ...  \n",
       "9530    0.894839  \n",
       "9532    0.504995  \n",
       "9533    0.156971  \n",
       "9534    0.690184  \n",
       "9536    0.213555  \n",
       "\n",
       "[6568 rows x 13 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.loc[:, 'D2A_JPHH':'D2C_WREMLX'] # This is mostly already appropriately scaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>D2A_JPHH</th>\n",
       "      <th>D2B_E5MIX</th>\n",
       "      <th>D2B_E5MIXA</th>\n",
       "      <th>D2B_E8MIX</th>\n",
       "      <th>D2B_E8MIXA</th>\n",
       "      <th>D2A_EPHHM</th>\n",
       "      <th>D2C_TRPMX1</th>\n",
       "      <th>D2C_TRPMX2</th>\n",
       "      <th>D2C_TRIPEQ</th>\n",
       "      <th>D2R_JOBPOP</th>\n",
       "      <th>D2R_WRKEMP</th>\n",
       "      <th>D2A_WRKEMP</th>\n",
       "      <th>D2C_WREMLX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.492406</td>\n",
       "      <td>0.651673</td>\n",
       "      <td>0.586945</td>\n",
       "      <td>0.716324</td>\n",
       "      <td>0.606824</td>\n",
       "      <td>0.525778</td>\n",
       "      <td>0.509411</td>\n",
       "      <td>0.540602</td>\n",
       "      <td>0.466786</td>\n",
       "      <td>0.346393</td>\n",
       "      <td>0.473834</td>\n",
       "      <td>4.775469</td>\n",
       "      <td>0.320303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>23.301847</td>\n",
       "      <td>0.217217</td>\n",
       "      <td>0.224334</td>\n",
       "      <td>0.182274</td>\n",
       "      <td>0.181047</td>\n",
       "      <td>0.194984</td>\n",
       "      <td>0.174006</td>\n",
       "      <td>0.188160</td>\n",
       "      <td>0.282745</td>\n",
       "      <td>0.271953</td>\n",
       "      <td>0.280552</td>\n",
       "      <td>8.249127</td>\n",
       "      <td>0.315073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.208042</td>\n",
       "      <td>0.517664</td>\n",
       "      <td>0.433108</td>\n",
       "      <td>0.635228</td>\n",
       "      <td>0.498076</td>\n",
       "      <td>0.380408</td>\n",
       "      <td>0.386540</td>\n",
       "      <td>0.408399</td>\n",
       "      <td>0.258097</td>\n",
       "      <td>0.127204</td>\n",
       "      <td>0.239042</td>\n",
       "      <td>0.903226</td>\n",
       "      <td>0.009342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.464286</td>\n",
       "      <td>0.699363</td>\n",
       "      <td>0.618558</td>\n",
       "      <td>0.764205</td>\n",
       "      <td>0.639104</td>\n",
       "      <td>0.525528</td>\n",
       "      <td>0.519455</td>\n",
       "      <td>0.549969</td>\n",
       "      <td>0.473379</td>\n",
       "      <td>0.268247</td>\n",
       "      <td>0.448578</td>\n",
       "      <td>2.451378</td>\n",
       "      <td>0.233400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.173868</td>\n",
       "      <td>0.817922</td>\n",
       "      <td>0.768221</td>\n",
       "      <td>0.849422</td>\n",
       "      <td>0.743128</td>\n",
       "      <td>0.673978</td>\n",
       "      <td>0.650392</td>\n",
       "      <td>0.690721</td>\n",
       "      <td>0.677727</td>\n",
       "      <td>0.517771</td>\n",
       "      <td>0.706830</td>\n",
       "      <td>5.667984</td>\n",
       "      <td>0.570652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1294.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.998274</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.972284</td>\n",
       "      <td>0.993134</td>\n",
       "      <td>0.969981</td>\n",
       "      <td>0.989403</td>\n",
       "      <td>0.999739</td>\n",
       "      <td>0.999854</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>242.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          D2A_JPHH    D2B_E5MIX   D2B_E5MIXA    D2B_E8MIX   D2B_E8MIXA  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      2.492406     0.651673     0.586945     0.716324     0.606824   \n",
       "std      23.301847     0.217217     0.224334     0.182274     0.181047   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.208042     0.517664     0.433108     0.635228     0.498076   \n",
       "50%       0.464286     0.699363     0.618558     0.764205     0.639104   \n",
       "75%       1.173868     0.817922     0.768221     0.849422     0.743128   \n",
       "max    1294.000000     1.000000     0.998274     1.000000     0.972284   \n",
       "\n",
       "         D2A_EPHHM   D2C_TRPMX1   D2C_TRPMX2   D2C_TRIPEQ   D2R_JOBPOP  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.525778     0.509411     0.540602     0.466786     0.346393   \n",
       "std       0.194984     0.174006     0.188160     0.282745     0.271953   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.380408     0.386540     0.408399     0.258097     0.127204   \n",
       "50%       0.525528     0.519455     0.549969     0.473379     0.268247   \n",
       "75%       0.673978     0.650392     0.690721     0.677727     0.517771   \n",
       "max       0.993134     0.969981     0.989403     0.999739     0.999854   \n",
       "\n",
       "        D2R_WRKEMP   D2A_WRKEMP   D2C_WREMLX  \n",
       "count  6568.000000  6568.000000  6568.000000  \n",
       "mean      0.473834     4.775469     0.320303  \n",
       "std       0.280552     8.249127     0.315073  \n",
       "min       0.000000     0.000000     0.000000  \n",
       "25%       0.239042     0.903226     0.009342  \n",
       "50%       0.448578     2.451378     0.233400  \n",
       "75%       0.706830     5.667984     0.570652  \n",
       "max       1.000000   242.000000     1.000000  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# D2A_JPHH and D2A_WRKEMP have outliers\n",
    "df1.loc[:, 'D2A_JPHH':'D2C_WREMLX'].describe() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Log Jobs per house hold."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1['log_D2A_JPHH'] = np.log1p(df1['D2A_JPHH'])\n",
    "np.log1p(df1['D2A_JPHH']).hist(); # slightly better"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Log workers per job compared to regional average."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1['log_D2A_WRKEMP'] = np.log1p(df1['D2A_WRKEMP'])\n",
    "np.log1p(df1['D2A_WRKEMP']).hist();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Employment Rate (E, D1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['Pct_Workers'] = df1['Workers'].div(df1['TotPop'], axis = 0).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7981          inf\n",
       "8504          inf\n",
       "7408          inf\n",
       "3108    59.250000\n",
       "3107    59.250000\n",
       "6271    34.400000\n",
       "8371    19.300000\n",
       "8306     6.285714\n",
       "8307     6.285714\n",
       "5804     4.800000\n",
       "3063     2.649573\n",
       "3061     2.649573\n",
       "3060     2.649573\n",
       "3059     2.649573\n",
       "6888     2.554348\n",
       "6889     2.554348\n",
       "2738     2.185185\n",
       "2740     2.185185\n",
       "8870     2.066667\n",
       "3921     1.549815\n",
       "Name: Pct_Workers, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['Pct_Workers'].sort_values(ascending = False).head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Limit outlier worker numbers to double the population\n",
    "df1['Pct_Workers'].clip(upper = 2, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(39, 52)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.columns.slice_locs('E5_Ret', 'E8_Pub')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Employment sector jobs relative to total employment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "employment_cols = df1.columns[39:52]\n",
    "pct_employment_cols = ['pct_' + col for col in employment_cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1[pct_employment_cols] = \\\n",
    "    df1[employment_cols].div(df['TotEmp'], axis = 0).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>pct_E5_Ret</th>\n",
       "      <th>pct_E5_Off</th>\n",
       "      <th>pct_E5_Ind</th>\n",
       "      <th>pct_E5_Svc</th>\n",
       "      <th>pct_E5_Ent</th>\n",
       "      <th>pct_E8_Ret</th>\n",
       "      <th>pct_E8_off</th>\n",
       "      <th>pct_E8_Ind</th>\n",
       "      <th>pct_E8_Svc</th>\n",
       "      <th>pct_E8_Ent</th>\n",
       "      <th>pct_E8_Ed</th>\n",
       "      <th>pct_E8_Hlth</th>\n",
       "      <th>pct_E8_Pub</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.156379</td>\n",
       "      <td>0.060700</td>\n",
       "      <td>0.190329</td>\n",
       "      <td>0.372428</td>\n",
       "      <td>0.220165</td>\n",
       "      <td>0.156379</td>\n",
       "      <td>0.060700</td>\n",
       "      <td>0.190329</td>\n",
       "      <td>0.335391</td>\n",
       "      <td>0.220165</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.006776</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005491</td>\n",
       "      <td>0.924524</td>\n",
       "      <td>0.063208</td>\n",
       "      <td>0.006776</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005491</td>\n",
       "      <td>0.018343</td>\n",
       "      <td>0.063208</td>\n",
       "      <td>0.000818</td>\n",
       "      <td>0.905363</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.014451</td>\n",
       "      <td>0.297688</td>\n",
       "      <td>0.043353</td>\n",
       "      <td>0.612717</td>\n",
       "      <td>0.031792</td>\n",
       "      <td>0.014451</td>\n",
       "      <td>0.297688</td>\n",
       "      <td>0.043353</td>\n",
       "      <td>0.057803</td>\n",
       "      <td>0.031792</td>\n",
       "      <td>0.465318</td>\n",
       "      <td>0.089595</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.014451</td>\n",
       "      <td>0.297688</td>\n",
       "      <td>0.043353</td>\n",
       "      <td>0.612717</td>\n",
       "      <td>0.031792</td>\n",
       "      <td>0.014451</td>\n",
       "      <td>0.297688</td>\n",
       "      <td>0.043353</td>\n",
       "      <td>0.057803</td>\n",
       "      <td>0.031792</td>\n",
       "      <td>0.465318</td>\n",
       "      <td>0.089595</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.075214</td>\n",
       "      <td>0.023932</td>\n",
       "      <td>0.023932</td>\n",
       "      <td>0.719658</td>\n",
       "      <td>0.157265</td>\n",
       "      <td>0.075214</td>\n",
       "      <td>0.015385</td>\n",
       "      <td>0.023932</td>\n",
       "      <td>0.131624</td>\n",
       "      <td>0.157265</td>\n",
       "      <td>0.104274</td>\n",
       "      <td>0.483761</td>\n",
       "      <td>0.008547</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9530</th>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.032164</td>\n",
       "      <td>0.067251</td>\n",
       "      <td>0.093567</td>\n",
       "      <td>0.751462</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.032164</td>\n",
       "      <td>0.067251</td>\n",
       "      <td>0.067251</td>\n",
       "      <td>0.751462</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.026316</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9532</th>\n",
       "      <td>0.019084</td>\n",
       "      <td>0.022901</td>\n",
       "      <td>0.061069</td>\n",
       "      <td>0.885496</td>\n",
       "      <td>0.011450</td>\n",
       "      <td>0.019084</td>\n",
       "      <td>0.022901</td>\n",
       "      <td>0.061069</td>\n",
       "      <td>0.011450</td>\n",
       "      <td>0.011450</td>\n",
       "      <td>0.755725</td>\n",
       "      <td>0.118321</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9533</th>\n",
       "      <td>0.072034</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.163136</td>\n",
       "      <td>0.468220</td>\n",
       "      <td>0.046610</td>\n",
       "      <td>0.072034</td>\n",
       "      <td>0.055085</td>\n",
       "      <td>0.163136</td>\n",
       "      <td>0.122881</td>\n",
       "      <td>0.046610</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.345339</td>\n",
       "      <td>0.194915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9534</th>\n",
       "      <td>0.131604</td>\n",
       "      <td>0.113353</td>\n",
       "      <td>0.061479</td>\n",
       "      <td>0.128722</td>\n",
       "      <td>0.564841</td>\n",
       "      <td>0.131604</td>\n",
       "      <td>0.015370</td>\n",
       "      <td>0.061479</td>\n",
       "      <td>0.002882</td>\n",
       "      <td>0.564841</td>\n",
       "      <td>0.051873</td>\n",
       "      <td>0.073967</td>\n",
       "      <td>0.097983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9536</th>\n",
       "      <td>0.004386</td>\n",
       "      <td>0.021930</td>\n",
       "      <td>0.135965</td>\n",
       "      <td>0.574561</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.004386</td>\n",
       "      <td>0.021930</td>\n",
       "      <td>0.135965</td>\n",
       "      <td>0.184211</td>\n",
       "      <td>0.263158</td>\n",
       "      <td>0.232456</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6568 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      pct_E5_Ret  pct_E5_Off  pct_E5_Ind  pct_E5_Svc  pct_E5_Ent  pct_E8_Ret  \\\n",
       "0       0.156379    0.060700    0.190329    0.372428    0.220165    0.156379   \n",
       "1       0.006776    0.000000    0.005491    0.924524    0.063208    0.006776   \n",
       "4       0.014451    0.297688    0.043353    0.612717    0.031792    0.014451   \n",
       "8       0.014451    0.297688    0.043353    0.612717    0.031792    0.014451   \n",
       "12      0.075214    0.023932    0.023932    0.719658    0.157265    0.075214   \n",
       "...          ...         ...         ...         ...         ...         ...   \n",
       "9530    0.055556    0.032164    0.067251    0.093567    0.751462    0.055556   \n",
       "9532    0.019084    0.022901    0.061069    0.885496    0.011450    0.019084   \n",
       "9533    0.072034    0.250000    0.163136    0.468220    0.046610    0.072034   \n",
       "9534    0.131604    0.113353    0.061479    0.128722    0.564841    0.131604   \n",
       "9536    0.004386    0.021930    0.135965    0.574561    0.263158    0.004386   \n",
       "\n",
       "      pct_E8_off  pct_E8_Ind  pct_E8_Svc  pct_E8_Ent  pct_E8_Ed  pct_E8_Hlth  \\\n",
       "0       0.060700    0.190329    0.335391    0.220165   0.000000     0.037037   \n",
       "1       0.000000    0.005491    0.018343    0.063208   0.000818     0.905363   \n",
       "4       0.297688    0.043353    0.057803    0.031792   0.465318     0.089595   \n",
       "8       0.297688    0.043353    0.057803    0.031792   0.465318     0.089595   \n",
       "12      0.015385    0.023932    0.131624    0.157265   0.104274     0.483761   \n",
       "...          ...         ...         ...         ...        ...          ...   \n",
       "9530    0.032164    0.067251    0.067251    0.751462   0.000000     0.026316   \n",
       "9532    0.022901    0.061069    0.011450    0.011450   0.755725     0.118321   \n",
       "9533    0.055085    0.163136    0.122881    0.046610   0.000000     0.345339   \n",
       "9534    0.015370    0.061479    0.002882    0.564841   0.051873     0.073967   \n",
       "9536    0.021930    0.135965    0.184211    0.263158   0.232456     0.157895   \n",
       "\n",
       "      pct_E8_Pub  \n",
       "0       0.000000  \n",
       "1       0.000000  \n",
       "4       0.000000  \n",
       "8       0.000000  \n",
       "12      0.008547  \n",
       "...          ...  \n",
       "9530    0.000000  \n",
       "9532    0.000000  \n",
       "9533    0.194915  \n",
       "9534    0.097983  \n",
       "9536    0.000000  \n",
       "\n",
       "[6568 rows x 13 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1[pct_employment_cols]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Design (D3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(86, 96)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.columns.slice_locs('D3A', 'D3BPO4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "design_cols = df1.columns[87:97]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>D3AAO</th>\n",
       "      <th>D3AMM</th>\n",
       "      <th>D3APO</th>\n",
       "      <th>D3B</th>\n",
       "      <th>D3BAO</th>\n",
       "      <th>D3BMM3</th>\n",
       "      <th>D3BMM4</th>\n",
       "      <th>D3BPO3</th>\n",
       "      <th>D3BPO4</th>\n",
       "      <th>D4A</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.962671</td>\n",
       "      <td>2.081332</td>\n",
       "      <td>12.761485</td>\n",
       "      <td>80.896852</td>\n",
       "      <td>2.236382</td>\n",
       "      <td>9.932338</td>\n",
       "      <td>5.865437</td>\n",
       "      <td>69.294921</td>\n",
       "      <td>22.186833</td>\n",
       "      <td>1213.228701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.230362</td>\n",
       "      <td>2.711260</td>\n",
       "      <td>9.292966</td>\n",
       "      <td>88.241150</td>\n",
       "      <td>7.576800</td>\n",
       "      <td>16.558875</td>\n",
       "      <td>13.073227</td>\n",
       "      <td>82.108396</td>\n",
       "      <td>37.976761</td>\n",
       "      <td>783.603346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.033017</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.296585</td>\n",
       "      <td>3.804942</td>\n",
       "      <td>11.309733</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.348963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.540670</td>\n",
       "      <td>0.783275</td>\n",
       "      <td>434.520000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.043947</td>\n",
       "      <td>1.094100</td>\n",
       "      <td>12.340091</td>\n",
       "      <td>58.376932</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.223524</td>\n",
       "      <td>0.414470</td>\n",
       "      <td>46.573230</td>\n",
       "      <td>7.015535</td>\n",
       "      <td>1073.570000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.833698</td>\n",
       "      <td>2.761875</td>\n",
       "      <td>19.866642</td>\n",
       "      <td>125.080112</td>\n",
       "      <td>1.142245</td>\n",
       "      <td>11.825651</td>\n",
       "      <td>6.070980</td>\n",
       "      <td>102.283434</td>\n",
       "      <td>26.026233</td>\n",
       "      <td>2000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>35.319543</td>\n",
       "      <td>28.413881</td>\n",
       "      <td>59.853592</td>\n",
       "      <td>930.130573</td>\n",
       "      <td>146.448102</td>\n",
       "      <td>162.064156</td>\n",
       "      <td>251.931476</td>\n",
       "      <td>911.625358</td>\n",
       "      <td>438.674602</td>\n",
       "      <td>2000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             D3AAO        D3AMM        D3APO          D3B        D3BAO  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.962671     2.081332    12.761485    80.896852     2.236382   \n",
       "std       2.230362     2.711260     9.292966    88.241150     7.576800   \n",
       "min       0.000000     0.000000     0.000000     0.033017     0.000000   \n",
       "25%       0.000000     0.296585     3.804942    11.309733     0.000000   \n",
       "50%       0.043947     1.094100    12.340091    58.376932     0.000000   \n",
       "75%       0.833698     2.761875    19.866642   125.080112     1.142245   \n",
       "max      35.319543    28.413881    59.853592   930.130573   146.448102   \n",
       "\n",
       "            D3BMM3       D3BMM4       D3BPO3       D3BPO4          D4A  \n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000  \n",
       "mean      9.932338     5.865437    69.294921    22.186833  1213.228701  \n",
       "std      16.558875    13.073227    82.108396    37.976761   783.603346  \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
       "25%       0.348963     0.000000     9.540670     0.783275   434.520000  \n",
       "50%       3.223524     0.414470    46.573230     7.015535  1073.570000  \n",
       "75%      11.825651     6.070980   102.283434    26.026233  2000.000000  \n",
       "max     162.064156   251.931476   911.625358   438.674602  2000.000000  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.iloc[:, 87:97].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More normally distributed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>D3A</th>\n",
       "      <th>D3AAO</th>\n",
       "      <th>D3AMM</th>\n",
       "      <th>D3APO</th>\n",
       "      <th>D3B</th>\n",
       "      <th>D3BAO</th>\n",
       "      <th>D3BMM3</th>\n",
       "      <th>D3BMM4</th>\n",
       "      <th>D3BPO3</th>\n",
       "      <th>D3BPO4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.520502</td>\n",
       "      <td>0.400049</td>\n",
       "      <td>0.859374</td>\n",
       "      <td>2.285180</td>\n",
       "      <td>3.624083</td>\n",
       "      <td>0.528951</td>\n",
       "      <td>1.562807</td>\n",
       "      <td>1.016596</td>\n",
       "      <td>3.431595</td>\n",
       "      <td>2.076888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.870382</td>\n",
       "      <td>0.621444</td>\n",
       "      <td>0.688415</td>\n",
       "      <td>0.932934</td>\n",
       "      <td>1.516880</td>\n",
       "      <td>0.883029</td>\n",
       "      <td>1.279717</td>\n",
       "      <td>1.216785</td>\n",
       "      <td>1.556969</td>\n",
       "      <td>1.526941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.183765</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.032483</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.828890</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.259734</td>\n",
       "      <td>1.569645</td>\n",
       "      <td>2.510389</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.299335</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.355241</td>\n",
       "      <td>0.578452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.816601</td>\n",
       "      <td>0.043008</td>\n",
       "      <td>0.739124</td>\n",
       "      <td>2.590774</td>\n",
       "      <td>4.083906</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.440670</td>\n",
       "      <td>0.346755</td>\n",
       "      <td>3.862270</td>\n",
       "      <td>2.081381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.226953</td>\n",
       "      <td>0.606335</td>\n",
       "      <td>1.324917</td>\n",
       "      <td>3.038152</td>\n",
       "      <td>4.836918</td>\n",
       "      <td>0.761854</td>\n",
       "      <td>2.551447</td>\n",
       "      <td>1.955999</td>\n",
       "      <td>4.637477</td>\n",
       "      <td>3.296807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.208527</td>\n",
       "      <td>3.592356</td>\n",
       "      <td>3.381467</td>\n",
       "      <td>4.108471</td>\n",
       "      <td>6.836400</td>\n",
       "      <td>4.993476</td>\n",
       "      <td>5.094144</td>\n",
       "      <td>5.533119</td>\n",
       "      <td>6.816325</td>\n",
       "      <td>6.086035</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               D3A        D3AAO        D3AMM        D3APO          D3B  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      2.520502     0.400049     0.859374     2.285180     3.624083   \n",
       "std       0.870382     0.621444     0.688415     0.932934     1.516880   \n",
       "min       0.183765     0.000000     0.000000     0.000000     0.032483   \n",
       "25%       1.828890     0.000000     0.259734     1.569645     2.510389   \n",
       "50%       2.816601     0.043008     0.739124     2.590774     4.083906   \n",
       "75%       3.226953     0.606335     1.324917     3.038152     4.836918   \n",
       "max       4.208527     3.592356     3.381467     4.108471     6.836400   \n",
       "\n",
       "             D3BAO       D3BMM3       D3BMM4       D3BPO3       D3BPO4  \n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000  \n",
       "mean      0.528951     1.562807     1.016596     3.431595     2.076888  \n",
       "std       0.883029     1.279717     1.216785     1.556969     1.526941  \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
       "25%       0.000000     0.299335     0.000000     2.355241     0.578452  \n",
       "50%       0.000000     1.440670     0.346755     3.862270     2.081381  \n",
       "75%       0.761854     2.551447     1.955999     4.637477     3.296807  \n",
       "max       4.993476     5.094144     5.533119     6.816325     6.086035  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.log1p(df1.loc[:, 'D3A':'D3BPO4']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1[['log_' + col for col in design_cols]] = np.log1p(df1.loc[:, 'D3A':'D3BPO4'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Transit Access (D4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>D4A</th>\n",
       "      <th>D4B025</th>\n",
       "      <th>D4B050</th>\n",
       "      <th>D4C</th>\n",
       "      <th>D4D</th>\n",
       "      <th>D4E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1213.228701</td>\n",
       "      <td>0.032314</td>\n",
       "      <td>0.080674</td>\n",
       "      <td>5.896553</td>\n",
       "      <td>43.237187</td>\n",
       "      <td>0.006362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>783.603346</td>\n",
       "      <td>0.142689</td>\n",
       "      <td>0.235226</td>\n",
       "      <td>13.616432</td>\n",
       "      <td>157.389688</td>\n",
       "      <td>0.085629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>434.520000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1073.570000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.670000</td>\n",
       "      <td>0.894316</td>\n",
       "      <td>0.000987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>17.549629</td>\n",
       "      <td>0.004099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2000.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>402.330000</td>\n",
       "      <td>3593.895311</td>\n",
       "      <td>5.734000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               D4A       D4B025       D4B050          D4C          D4D  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean   1213.228701     0.032314     0.080674     5.896553    43.237187   \n",
       "std     783.603346     0.142689     0.235226    13.616432   157.389688   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%     434.520000     0.000000     0.000000     0.000000     0.000000   \n",
       "50%    1073.570000     0.000000     0.000000     1.670000     0.894316   \n",
       "75%    2000.000000     0.000000     0.000000     6.000000    17.549629   \n",
       "max    2000.000000     1.000000     1.000000   402.330000  3593.895311   \n",
       "\n",
       "               D4E  \n",
       "count  6568.000000  \n",
       "mean      0.006362  \n",
       "std       0.085629  \n",
       "min       0.000000  \n",
       "25%       0.000000  \n",
       "50%       0.000987  \n",
       "75%       0.004099  \n",
       "max       5.734000  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.loc[:, 'D4A':'D4E'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1[['log_D4C', 'log_D4D', 'log_D4E']] = np.log1p(df1[['D4C', 'D4D', 'D4E']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Destination Accessibility (D5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(102, 114)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.columns.slice_locs('D5AR', 'D5DEI')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "design_cols = df1.columns[103:115]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>D5AE</th>\n",
       "      <th>D5BR</th>\n",
       "      <th>D5BE</th>\n",
       "      <th>D5CR</th>\n",
       "      <th>D5CRI</th>\n",
       "      <th>D5CE</th>\n",
       "      <th>D5CEI</th>\n",
       "      <th>D5DR</th>\n",
       "      <th>D5DRI</th>\n",
       "      <th>D5DE</th>\n",
       "      <th>D5DEI</th>\n",
       "      <th>D2A_Ranked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6.568000e+03</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>66814.646620</td>\n",
       "      <td>7.072618e+04</td>\n",
       "      <td>44088.434227</td>\n",
       "      <td>0.001998</td>\n",
       "      <td>0.370175</td>\n",
       "      <td>0.001948</td>\n",
       "      <td>0.407187</td>\n",
       "      <td>0.001630</td>\n",
       "      <td>0.112306</td>\n",
       "      <td>0.001578</td>\n",
       "      <td>0.121065</td>\n",
       "      <td>11.051918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>72466.561323</td>\n",
       "      <td>1.433480e+05</td>\n",
       "      <td>84663.767782</td>\n",
       "      <td>0.005823</td>\n",
       "      <td>0.251057</td>\n",
       "      <td>0.005366</td>\n",
       "      <td>0.258548</td>\n",
       "      <td>0.017315</td>\n",
       "      <td>0.188941</td>\n",
       "      <td>0.017433</td>\n",
       "      <td>0.195610</td>\n",
       "      <td>5.184039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>89.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>12555.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.163719</td>\n",
       "      <td>0.000164</td>\n",
       "      <td>0.196729</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>50407.000000</td>\n",
       "      <td>3.235000e+02</td>\n",
       "      <td>579.000000</td>\n",
       "      <td>0.000423</td>\n",
       "      <td>0.363731</td>\n",
       "      <td>0.000420</td>\n",
       "      <td>0.404276</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.000618</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.002154</td>\n",
       "      <td>11.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>96744.000000</td>\n",
       "      <td>6.524050e+04</td>\n",
       "      <td>48283.500000</td>\n",
       "      <td>0.001359</td>\n",
       "      <td>0.543041</td>\n",
       "      <td>0.001296</td>\n",
       "      <td>0.597752</td>\n",
       "      <td>0.000504</td>\n",
       "      <td>0.162911</td>\n",
       "      <td>0.000512</td>\n",
       "      <td>0.178562</td>\n",
       "      <td>15.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>484231.000000</td>\n",
       "      <td>1.127939e+06</td>\n",
       "      <td>617792.000000</td>\n",
       "      <td>0.091781</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.080836</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                D5AE          D5BR           D5BE         D5CR        D5CRI  \\\n",
       "count    6568.000000  6.568000e+03    6568.000000  6568.000000  6568.000000   \n",
       "mean    66814.646620  7.072618e+04   44088.434227     0.001998     0.370175   \n",
       "std     72466.561323  1.433480e+05   84663.767782     0.005823     0.251057   \n",
       "min        89.000000  0.000000e+00       0.000000     0.000000     0.000000   \n",
       "25%     12555.000000  0.000000e+00       0.000000     0.000159     0.163719   \n",
       "50%     50407.000000  3.235000e+02     579.000000     0.000423     0.363731   \n",
       "75%     96744.000000  6.524050e+04   48283.500000     0.001359     0.543041   \n",
       "max    484231.000000  1.127939e+06  617792.000000     0.091781     1.000000   \n",
       "\n",
       "              D5CE        D5CEI         D5DR        D5DRI         D5DE  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.001948     0.407187     0.001630     0.112306     0.001578   \n",
       "std       0.005366     0.258548     0.017315     0.188941     0.017433   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000164     0.196729     0.000000     0.000000     0.000000   \n",
       "50%       0.000420     0.404276     0.000002     0.000618     0.000004   \n",
       "75%       0.001296     0.597752     0.000504     0.162911     0.000512   \n",
       "max       0.080836     1.000000     1.000000     1.000000     1.000000   \n",
       "\n",
       "             D5DEI   D2A_Ranked  \n",
       "count  6568.000000  6568.000000  \n",
       "mean      0.121065    11.051918  \n",
       "std       0.195610     5.184039  \n",
       "min       0.000000     1.000000  \n",
       "25%       0.000000     7.000000  \n",
       "50%       0.002154    11.000000  \n",
       "75%       0.178562    15.000000  \n",
       "max       1.000000    20.000000  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.iloc[:, 103:115].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First 4 can take log transform."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['D5AE', 'D5BR', 'D5BE', 'D5CR'], dtype='object')"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "destination_cols1 = df1.columns[103:107]\n",
    "destination_cols1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>D5AE</th>\n",
       "      <th>D5BR</th>\n",
       "      <th>D5BE</th>\n",
       "      <th>D5CR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>10.237673</td>\n",
       "      <td>5.514937</td>\n",
       "      <td>5.390788</td>\n",
       "      <td>0.001979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.733499</td>\n",
       "      <td>5.495184</td>\n",
       "      <td>5.320261</td>\n",
       "      <td>0.005681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.499810</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>9.437954</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>10.827905</td>\n",
       "      <td>5.782284</td>\n",
       "      <td>6.363028</td>\n",
       "      <td>0.000423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>11.479834</td>\n",
       "      <td>11.085851</td>\n",
       "      <td>10.784866</td>\n",
       "      <td>0.001358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.090319</td>\n",
       "      <td>13.935904</td>\n",
       "      <td>13.333909</td>\n",
       "      <td>0.087810</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              D5AE         D5BR         D5BE         D5CR\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000\n",
       "mean     10.237673     5.514937     5.390788     0.001979\n",
       "std       1.733499     5.495184     5.320261     0.005681\n",
       "min       4.499810     0.000000     0.000000     0.000000\n",
       "25%       9.437954     0.000000     0.000000     0.000159\n",
       "50%      10.827905     5.782284     6.363028     0.000423\n",
       "75%      11.479834    11.085851    10.784866     0.001358\n",
       "max      13.090319    13.935904    13.333909     0.087810"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.log1p(df1.iloc[:, 103:107]).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1[['log_' + col for col in destination_cols1]] = np.log1p(df1[destination_cols1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The remaining features are already from 0 to 1 but can be power transformed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['D5CRI', 'D5CE', 'D5CEI', 'D5DR', 'D5DRI', 'D5DE', 'D5DEI',\n",
       "       'D2A_Ranked'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "destination_cols2 = df1.columns[107:115]\n",
    "destination_cols2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>D5CRI</th>\n",
       "      <th>D5CE</th>\n",
       "      <th>D5CEI</th>\n",
       "      <th>D5DR</th>\n",
       "      <th>D5DRI</th>\n",
       "      <th>D5DE</th>\n",
       "      <th>D5DEI</th>\n",
       "      <th>D2A_Ranked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.845905</td>\n",
       "      <td>0.457339</td>\n",
       "      <td>0.857652</td>\n",
       "      <td>0.238834</td>\n",
       "      <td>0.409946</td>\n",
       "      <td>0.240468</td>\n",
       "      <td>0.419376</td>\n",
       "      <td>1.255308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.190576</td>\n",
       "      <td>0.119457</td>\n",
       "      <td>0.189985</td>\n",
       "      <td>0.242845</td>\n",
       "      <td>0.409180</td>\n",
       "      <td>0.242787</td>\n",
       "      <td>0.415255</td>\n",
       "      <td>0.072716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.834469</td>\n",
       "      <td>0.418333</td>\n",
       "      <td>0.849937</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.214814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.903812</td>\n",
       "      <td>0.459596</td>\n",
       "      <td>0.913414</td>\n",
       "      <td>0.263441</td>\n",
       "      <td>0.477607</td>\n",
       "      <td>0.291689</td>\n",
       "      <td>0.541156</td>\n",
       "      <td>1.270982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.940770</td>\n",
       "      <td>0.514369</td>\n",
       "      <td>0.949844</td>\n",
       "      <td>0.468001</td>\n",
       "      <td>0.834056</td>\n",
       "      <td>0.468759</td>\n",
       "      <td>0.841742</td>\n",
       "      <td>1.311019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.777607</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.349283</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             D5CRI         D5CE        D5CEI         D5DR        D5DRI  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.845905     0.457339     0.857652     0.238834     0.409946   \n",
       "std       0.190576     0.119457     0.189985     0.242845     0.409180   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.834469     0.418333     0.849937     0.000000     0.000000   \n",
       "50%       0.903812     0.459596     0.913414     0.263441     0.477607   \n",
       "75%       0.940770     0.514369     0.949844     0.468001     0.834056   \n",
       "max       1.000000     0.777607     1.000000     1.000000     1.000000   \n",
       "\n",
       "              D5DE        D5DEI   D2A_Ranked  \n",
       "count  6568.000000  6568.000000  6568.000000  \n",
       "mean      0.240468     0.419376     1.255308  \n",
       "std       0.242787     0.415255     0.072716  \n",
       "min       0.000000     0.000000     1.000000  \n",
       "25%       0.000000     0.000000     1.214814  \n",
       "50%       0.291689     0.541156     1.270982  \n",
       "75%       0.468759     0.841742     1.311019  \n",
       "max       1.000000     1.000000     1.349283  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df1.iloc[:, 107:115]**0.1).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1[['pow_' + col for col in destination_cols2]] = (df1[destination_cols2])**0.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Target distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.log1p(df1['1week_avg']).plot(kind = 'hist');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['log_1week_avg'] = np.log1p(df1['1week_avg'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df1[['1week_avg', 'log_1week_avg']].hist()\n",
    "# plt.xlabel(\"value\")\n",
    "\n",
    "df1[['1week_avg', 'log_1week_avg']].plot(kind = 'kde', xlim = (-5, 30) );"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_context('talk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data = df1, x = '1week_avg', bins = 30)\n",
    "plt.title('Weekly Average Air Quality Distribution')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data = df1, x = 'log_1week_avg', bins = 30)\n",
    "plt.title('Weekly Log Average Air Quality Distribution')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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>pm_2.5</th>\n",
       "      <th>temp_f</th>\n",
       "      <th>age</th>\n",
       "      <th>1week_avg</th>\n",
       "      <th>fips_id</th>\n",
       "      <th>STATEFP</th>\n",
       "      <th>COUNTYFP</th>\n",
       "      <th>TRACTCE</th>\n",
       "      <th>BLKGRPCE</th>\n",
       "      <th>CSA</th>\n",
       "      <th>...</th>\n",
       "      <th>log_D5CR</th>\n",
       "      <th>pow_D5CRI</th>\n",
       "      <th>pow_D5CE</th>\n",
       "      <th>pow_D5CEI</th>\n",
       "      <th>pow_D5DR</th>\n",
       "      <th>pow_D5DRI</th>\n",
       "      <th>pow_D5DE</th>\n",
       "      <th>pow_D5DEI</th>\n",
       "      <th>pow_D2A_Ranked</th>\n",
       "      <th>log_1week_avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6.568000e+03</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6.568000e+03</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>5582.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "      <td>6568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>13.233127</td>\n",
       "      <td>81.187424</td>\n",
       "      <td>1.812476e+03</td>\n",
       "      <td>12.350295</td>\n",
       "      <td>6.153743e+10</td>\n",
       "      <td>6.098203</td>\n",
       "      <td>55.306486</td>\n",
       "      <td>232667.777253</td>\n",
       "      <td>2.103380</td>\n",
       "      <td>445.451272</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001979</td>\n",
       "      <td>0.845905</td>\n",
       "      <td>0.457339</td>\n",
       "      <td>0.857652</td>\n",
       "      <td>0.238834</td>\n",
       "      <td>0.409946</td>\n",
       "      <td>0.240468</td>\n",
       "      <td>0.419376</td>\n",
       "      <td>1.255308</td>\n",
       "      <td>2.381843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12.238945</td>\n",
       "      <td>13.263447</td>\n",
       "      <td>3.688110e+04</td>\n",
       "      <td>8.064147</td>\n",
       "      <td>6.141208e+09</td>\n",
       "      <td>0.614239</td>\n",
       "      <td>32.755082</td>\n",
       "      <td>241133.164411</td>\n",
       "      <td>1.162508</td>\n",
       "      <td>78.190914</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005681</td>\n",
       "      <td>0.190576</td>\n",
       "      <td>0.119457</td>\n",
       "      <td>0.189985</td>\n",
       "      <td>0.242845</td>\n",
       "      <td>0.409180</td>\n",
       "      <td>0.242787</td>\n",
       "      <td>0.415255</td>\n",
       "      <td>0.072716</td>\n",
       "      <td>0.714639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.073001e+10</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>142.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.070000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.440000</td>\n",
       "      <td>6.037140e+10</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>10901.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>472.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.834469</td>\n",
       "      <td>0.418333</td>\n",
       "      <td>0.849937</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.214814</td>\n",
       "      <td>2.006871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>10.580000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>11.690000</td>\n",
       "      <td>6.067006e+10</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>132200.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>488.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000423</td>\n",
       "      <td>0.903812</td>\n",
       "      <td>0.459596</td>\n",
       "      <td>0.913414</td>\n",
       "      <td>0.263441</td>\n",
       "      <td>0.477607</td>\n",
       "      <td>0.291689</td>\n",
       "      <td>0.541156</td>\n",
       "      <td>1.270982</td>\n",
       "      <td>2.540814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>23.702500</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>16.320000</td>\n",
       "      <td>6.085510e+10</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>442250.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>488.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001358</td>\n",
       "      <td>0.940770</td>\n",
       "      <td>0.514369</td>\n",
       "      <td>0.949844</td>\n",
       "      <td>0.468001</td>\n",
       "      <td>0.834056</td>\n",
       "      <td>0.468759</td>\n",
       "      <td>0.841742</td>\n",
       "      <td>1.311019</td>\n",
       "      <td>2.851862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>122.380000</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>1.982830e+06</td>\n",
       "      <td>121.000000</td>\n",
       "      <td>9.013881e+10</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>980200.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>536.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.087810</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.777607</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.349283</td>\n",
       "      <td>4.804021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 161 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            pm_2.5       temp_f           age    1week_avg       fips_id  \\\n",
       "count  6568.000000  6568.000000  6.568000e+03  6568.000000  6.568000e+03   \n",
       "mean     13.233127    81.187424  1.812476e+03    12.350295  6.153743e+10   \n",
       "std      12.238945    13.263447  3.688110e+04     8.064147  6.141208e+09   \n",
       "min       0.000000    29.000000  0.000000e+00     0.000000  1.073001e+10   \n",
       "25%       1.070000    76.000000  0.000000e+00     6.440000  6.037140e+10   \n",
       "50%      10.580000    82.000000  1.000000e+00    11.690000  6.067006e+10   \n",
       "75%      23.702500    89.000000  1.000000e+00    16.320000  6.085510e+10   \n",
       "max     122.380000   135.000000  1.982830e+06   121.000000  9.013881e+10   \n",
       "\n",
       "           STATEFP     COUNTYFP        TRACTCE     BLKGRPCE          CSA  ...  \\\n",
       "count  6568.000000  6568.000000    6568.000000  6568.000000  5582.000000  ...   \n",
       "mean      6.098203    55.306486  232667.777253     2.103380   445.451272  ...   \n",
       "std       0.614239    32.755082  241133.164411     1.162508    78.190914  ...   \n",
       "min       1.000000     1.000000     100.000000     1.000000   142.000000  ...   \n",
       "25%       6.000000    27.000000   10901.000000     1.000000   472.000000  ...   \n",
       "50%       6.000000    61.000000  132200.000000     2.000000   488.000000  ...   \n",
       "75%       6.000000    85.000000  442250.000000     3.000000   488.000000  ...   \n",
       "max       9.000000   125.000000  980200.000000     9.000000   536.000000  ...   \n",
       "\n",
       "          log_D5CR    pow_D5CRI     pow_D5CE    pow_D5CEI     pow_D5DR  \\\n",
       "count  6568.000000  6568.000000  6568.000000  6568.000000  6568.000000   \n",
       "mean      0.001979     0.845905     0.457339     0.857652     0.238834   \n",
       "std       0.005681     0.190576     0.119457     0.189985     0.242845   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000159     0.834469     0.418333     0.849937     0.000000   \n",
       "50%       0.000423     0.903812     0.459596     0.913414     0.263441   \n",
       "75%       0.001358     0.940770     0.514369     0.949844     0.468001   \n",
       "max       0.087810     1.000000     0.777607     1.000000     1.000000   \n",
       "\n",
       "         pow_D5DRI     pow_D5DE    pow_D5DEI  pow_D2A_Ranked  log_1week_avg  \n",
       "count  6568.000000  6568.000000  6568.000000     6568.000000    6568.000000  \n",
       "mean      0.409946     0.240468     0.419376        1.255308       2.381843  \n",
       "std       0.409180     0.242787     0.415255        0.072716       0.714639  \n",
       "min       0.000000     0.000000     0.000000        1.000000       0.000000  \n",
       "25%       0.000000     0.000000     0.000000        1.214814       2.006871  \n",
       "50%       0.477607     0.291689     0.541156        1.270982       2.540814  \n",
       "75%       0.834056     0.468759     0.841742        1.311019       2.851862  \n",
       "max       1.000000     1.000000     1.000000        1.349283       4.804021  \n",
       "\n",
       "[8 rows x 161 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>pm_2.5</th>\n",
       "      <th>temp_f</th>\n",
       "      <th>model</th>\n",
       "      <th>hidden</th>\n",
       "      <th>flagged</th>\n",
       "      <th>downgraded</th>\n",
       "      <th>age</th>\n",
       "      <th>is_owner</th>\n",
       "      <th>1week_avg</th>\n",
       "      <th>...</th>\n",
       "      <th>log_D5CR</th>\n",
       "      <th>pow_D5CRI</th>\n",
       "      <th>pow_D5CE</th>\n",
       "      <th>pow_D5CEI</th>\n",
       "      <th>pow_D5DR</th>\n",
       "      <th>pow_D5DRI</th>\n",
       "      <th>pow_D5DE</th>\n",
       "      <th>pow_D5DEI</th>\n",
       "      <th>pow_D2A_Ranked</th>\n",
       "      <th>log_1week_avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>#ValleyClimate</td>\n",
       "      <td>19.54</td>\n",
       "      <td>84.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>43.48</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002841</td>\n",
       "      <td>0.991947</td>\n",
       "      <td>0.553883</td>\n",
       "      <td>0.994245</td>\n",
       "      <td>0.572362</td>\n",
       "      <td>0.948110</td>\n",
       "      <td>0.563022</td>\n",
       "      <td>0.933045</td>\n",
       "      <td>1.349283</td>\n",
       "      <td>3.795040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>'S' St Between Inyo and Mono</td>\n",
       "      <td>18.52</td>\n",
       "      <td>93.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>41.81</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002836</td>\n",
       "      <td>0.991763</td>\n",
       "      <td>0.552428</td>\n",
       "      <td>0.991633</td>\n",
       "      <td>0.577695</td>\n",
       "      <td>0.956944</td>\n",
       "      <td>0.573469</td>\n",
       "      <td>0.950358</td>\n",
       "      <td>1.174619</td>\n",
       "      <td>3.756772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-------{---(@</td>\n",
       "      <td>18.84</td>\n",
       "      <td>81.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>11.38</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000283</td>\n",
       "      <td>0.899103</td>\n",
       "      <td>0.439787</td>\n",
       "      <td>0.908644</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.214814</td>\n",
       "      <td>2.516082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Carlmont</td>\n",
       "      <td>21.40</td>\n",
       "      <td>88.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>8.49</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000283</td>\n",
       "      <td>0.899103</td>\n",
       "      <td>0.439787</td>\n",
       "      <td>0.908644</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.214814</td>\n",
       "      <td>2.250239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>003 FK Parking Lot</td>\n",
       "      <td>0.17</td>\n",
       "      <td>135.0</td>\n",
       "      <td>PMS5003+PMS5003+BME280</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>8.93</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000679</td>\n",
       "      <td>0.945063</td>\n",
       "      <td>0.478952</td>\n",
       "      <td>0.950749</td>\n",
       "      <td>0.514757</td>\n",
       "      <td>0.776821</td>\n",
       "      <td>0.493659</td>\n",
       "      <td>0.782951</td>\n",
       "      <td>1.319508</td>\n",
       "      <td>2.295560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 171 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            name  pm_2.5  temp_f                   model  \\\n",
       "0                 #ValleyClimate   19.54    84.0  PMS5003+PMS5003+BME280   \n",
       "1   'S' St Between Inyo and Mono   18.52    93.0  PMS5003+PMS5003+BME280   \n",
       "4                  -------{---(@   18.84    81.0  PMS5003+PMS5003+BME280   \n",
       "8                       Carlmont   21.40    88.0  PMS5003+PMS5003+BME280   \n",
       "12            003 FK Parking Lot    0.17   135.0  PMS5003+PMS5003+BME280   \n",
       "\n",
       "    hidden  flagged  downgraded  age  is_owner  1week_avg  ...  log_D5CR  \\\n",
       "0    False    False       False    1     False      43.48  ...  0.002841   \n",
       "1    False    False       False    1     False      41.81  ...  0.002836   \n",
       "4    False    False       False    1     False      11.38  ...  0.000283   \n",
       "8    False    False       False    1     False       8.49  ...  0.000283   \n",
       "12   False    False       False    0     False       8.93  ...  0.000679   \n",
       "\n",
       "    pow_D5CRI  pow_D5CE  pow_D5CEI  pow_D5DR  pow_D5DRI  pow_D5DE  pow_D5DEI  \\\n",
       "0    0.991947  0.553883   0.994245  0.572362   0.948110  0.563022   0.933045   \n",
       "1    0.991763  0.552428   0.991633  0.577695   0.956944  0.573469   0.950358   \n",
       "4    0.899103  0.439787   0.908644  0.000000   0.000000  0.000000   0.000000   \n",
       "8    0.899103  0.439787   0.908644  0.000000   0.000000  0.000000   0.000000   \n",
       "12   0.945063  0.478952   0.950749  0.514757   0.776821  0.493659   0.782951   \n",
       "\n",
       "   pow_D2A_Ranked  log_1week_avg  \n",
       "0        1.349283       3.795040  \n",
       "1        1.174619       3.756772  \n",
       "4        1.214814       2.516082  \n",
       "8        1.214814       2.250239  \n",
       "12       1.319508       2.295560  \n",
       "\n",
       "[5 rows x 171 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.to_csv('data/air_walk_merged_clean.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_la = df1.query('CSA == 348')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37     474\n",
       "59     110\n",
       "111     91\n",
       "71      74\n",
       "65      71\n",
       "Name: COUNTYFP, dtype: int64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_la['COUNTYFP'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_la.to_csv('data/air_walk_merged_clean_LA.csv', index=False)"
   ]
  }
 ],
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