IN-CORE_1dv2_Joplin_EstimateAddressPoints_2019-07-11.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore Building Inventory to Find Residential Structures \n",
    "Steps required to make the Probabilistic Housing Unit Allocation work.\n",
    "\n",
    "Building footprint data now includes blockid, placeid, puma, parcelid and parcel data\n",
    "With all of this information it should be possible to explore the building footprint data to find most likely residential structures.\n",
    "\n",
    "With a good count of structures the number of housing units estimated by the Census can be distributed to building footprints.\n",
    "\n",
    "To Do:\n",
    "1. Read in cleaned building footprint data with census block and parcel data\n",
    "2. Identify Residential Structures\n",
    "3. Count residential structures by block\n",
    "4. Estimate the number of residential housing units (addressp points) in each structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\nathanael99\\AppData\\Local\\Continuum\\anaconda3\\envs\\pyincore20190618\\lib\\site-packages\\pysal\\model\\spvcm\\abstracts.py:10: UserWarning: The `dill` module is required to use the sqlite backend fully.\n",
      "  from .sqlite import head_to_sql, start_sql\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pysal as ps\n",
    "import math as math\n",
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import shapely\n",
    "import folium as fm # folium has more dynamic maps - but requires internet connection\n",
    "import os # For saving output to path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python Version      3.7.3 (default, Apr 24 2019, 15:29:51) [MSC v.1915 64 bit (AMD64)]\n",
      "pysal version:      2.0.0\n",
      "numpy version:      1.16.4\n",
      "geopandas version:  0.5.0\n",
      "pandas version:     0.24.2\n",
      "shapely version:    1.6.4.post1\n",
      "folium version:     0.9.1\n"
     ]
    }
   ],
   "source": [
    "# Display versions being used - important information for replication\n",
    "import sys\n",
    "print(\"Python Version     \", sys.version)\n",
    "print(\"pysal version:     \", ps.__version__)\n",
    "print(\"numpy version:     \", np.__version__)\n",
    "print(\"geopandas version: \", gpd.__version__)\n",
    "print(\"pandas version:    \", pd.__version__)\n",
    "print(\"shapely version:   \", shapely.__version__)\n",
    "print(\"folium version:    \", fm.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store Program Name for output files to have the same name\n",
    "programname = \"IN-CORE_1dv2_Joplin_EstimateAddressPoints_2019-07-11\"\n",
    "# Make directory to save output\n",
    "if not os.path.exists(programname):\n",
    "    os.mkdir(programname)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obtain data from previous program - Building Inventory with Parcel ID\n",
    "The previous program (IN-CORE_1cv2_Joplin_CleanBuildingInventory_2019) combined parcel data with the building inventory. With this information residential buildings can be identified with greater certaintity.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>bldg_id</th>\n",
       "      <th>parid</th>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th>STATEFP10</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>TRACTCE10</th>\n",
       "      <th>PUMGEOID10</th>\n",
       "      <th>PUMNAME10</th>\n",
       "      <th>PLCGEOID10</th>\n",
       "      <th>...</th>\n",
       "      <th>Zoning</th>\n",
       "      <th>APRBLDG</th>\n",
       "      <th>APRLAND</th>\n",
       "      <th>APRTOT</th>\n",
       "      <th>CLASS</th>\n",
       "      <th>STRUCTURE</th>\n",
       "      <th>YRBLT</th>\n",
       "      <th>classv2</th>\n",
       "      <th>taxsheetv2</th>\n",
       "      <th>prclbldsum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>B0000001</td>\n",
       "      <td>P16703610001025000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>R1</td>\n",
       "      <td>43070.0</td>\n",
       "      <td>11770.0</td>\n",
       "      <td>54840.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1945.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>B0000002</td>\n",
       "      <td>P16703610001028000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>R1</td>\n",
       "      <td>62810.0</td>\n",
       "      <td>9450.0</td>\n",
       "      <td>72260.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1966.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>B0000003</td>\n",
       "      <td>P16703610001027000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>CO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>B0000004</td>\n",
       "      <td>P16703610001029000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>R1</td>\n",
       "      <td>77220.0</td>\n",
       "      <td>8890.0</td>\n",
       "      <td>86110.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>B0000005</td>\n",
       "      <td>P16703610001059000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>C1</td>\n",
       "      <td>48820.0</td>\n",
       "      <td>11470.0</td>\n",
       "      <td>60290.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1955.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0   bldg_id               parid        BLOCKID10  STATEFP10  \\\n",
       "0           0  B0000001  P16703610001025000  290970102003000       29.0   \n",
       "1           1  B0000002  P16703610001028000  290970102003000       29.0   \n",
       "2           2  B0000003  P16703610001027000  290970102003000       29.0   \n",
       "3           3  B0000004  P16703610001029000  290970102003000       29.0   \n",
       "4           4  B0000005  P16703610001059000  290970102003000       29.0   \n",
       "\n",
       "   COUNTYFP10  TRACTCE10  PUMGEOID10                      PUMNAME10  \\\n",
       "0        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "1        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "2        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "3        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "4        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "\n",
       "   PLCGEOID10  ... Zoning  APRBLDG  APRLAND   APRTOT  CLASS  STRUCTURE  \\\n",
       "0   2937592.0  ...     R1  43070.0  11770.0  54840.0    NaN        NaN   \n",
       "1   2937592.0  ...     R1  62810.0   9450.0  72260.0    NaN        NaN   \n",
       "2   2937592.0  ...     CO      NaN      NaN      NaN    NaN        NaN   \n",
       "3   2937592.0  ...     R1  77220.0   8890.0  86110.0    NaN        NaN   \n",
       "4   2937592.0  ...     C1  48820.0  11470.0  60290.0    NaN        NaN   \n",
       "\n",
       "    YRBLT  classv2  taxsheetv2  prclbldsum  \n",
       "0  1945.0      NaN    2010 Res         1.0  \n",
       "1  1966.0      NaN    2010 Res         1.0  \n",
       "2     NaN      NaN         NaN         1.0  \n",
       "3  1965.0      NaN    2010 Res         1.0  \n",
       "4  1955.0      NaN    2010 Res         1.0  \n",
       "\n",
       "[5 rows x 62 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "source_program = \"IN-CORE_1cv2_Joplin_CleanBuildingInventory_2019-07-11\"\n",
    "building_csv = source_program+\"/\"+source_program+\"_EPSG4326.csv\"\n",
    "building_df = pd.read_csv(building_csv)\n",
    "building_gdf = gpd.GeoDataFrame(building_df)\n",
    "building_gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Unnamed: 0',\n",
       " 'bldg_id',\n",
       " 'parid',\n",
       " 'BLOCKID10',\n",
       " 'STATEFP10',\n",
       " 'COUNTYFP10',\n",
       " 'TRACTCE10',\n",
       " 'PUMGEOID10',\n",
       " 'PUMNAME10',\n",
       " 'PLCGEOID10',\n",
       " 'PLCNAME10',\n",
       " 'ADDRESS1',\n",
       " 'HOUSE_NO',\n",
       " 'archtype',\n",
       " 'objectid',\n",
       " 'parid_card',\n",
       " 'struct_typ',\n",
       " 'str_prob',\n",
       " 'year_built',\n",
       " 'no_stories',\n",
       " 'a_stories',\n",
       " 'b_stories',\n",
       " 'bsmt_type',\n",
       " 'sq_foot',\n",
       " 'gsq_foot',\n",
       " 'occ_type',\n",
       " 'occ_detail',\n",
       " 'major_occ',\n",
       " 'broad_occ',\n",
       " 'appr_bldg',\n",
       " 'repl_cst',\n",
       " 'str_cst',\n",
       " 'nstra_cst',\n",
       " 'nstrd_cst',\n",
       " 'dgn_lvl',\n",
       " 'cont_val',\n",
       " 'efacility',\n",
       " 'dwell_unit',\n",
       " 'str_typ2',\n",
       " 'occ_typ2',\n",
       " 'tract_id',\n",
       " 'guid',\n",
       " 'x',\n",
       " 'y',\n",
       " 'geometry',\n",
       " 'rppnt4326',\n",
       " 'bply4326',\n",
       " 'gsq_meter',\n",
       " 'HOUSING10',\n",
       " 'apcount',\n",
       " 'gqpop10',\n",
       " 'POP10',\n",
       " 'Zoning',\n",
       " 'APRBLDG',\n",
       " 'APRLAND',\n",
       " 'APRTOT',\n",
       " 'CLASS',\n",
       " 'STRUCTURE',\n",
       " 'YRBLT',\n",
       " 'classv2',\n",
       " 'taxsheetv2',\n",
       " 'prclbldsum']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check Columns\n",
    "cols = [col for col in building_gdf]\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     0\n",
       "unique    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Geomtry type needs to be converted to geo series polygons\n",
    "building_gdf['geometry'].geom_type.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count       28152\n",
       "unique          2\n",
       "top       Polygon\n",
       "freq        28148\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use shapely.wkt loads to convert WKT to GeoSeries\n",
    "from shapely.wkt import loads\n",
    "\n",
    "building_gdf['rppnt4326'] = building_gdf['rppnt4326'].apply(lambda x: loads(x))\n",
    "building_gdf['bply4326'] = building_gdf['bply4326'].apply(lambda x: loads(x))\n",
    "building_gdf['geometry'] = building_gdf['geometry'].apply(lambda x: loads(x))\n",
    "building_gdf['geometry'].geom_type.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Geodata frame requires geometry and CRS to be set\n",
    "building_gdf = building_gdf.set_geometry(building_gdf['geometry'])\n",
    "building_gdf.crs = {'init':'epsg:4326'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>bldg_id</th>\n",
       "      <th>parid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>28152</td>\n",
       "      <td>24496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>28152</td>\n",
       "      <td>18409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>B0012554</td>\n",
       "      <td>P16702620002006000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         bldg_id               parid\n",
       "count      28152               24496\n",
       "unique     28152               18409\n",
       "top     B0012554  P16702620002006000\n",
       "freq           1                  61"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check Unique IDs and Foreign Keys\n",
    "building_gdf[['bldg_id','parid']].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Limit Number of Buildings to Most Likely Residential Structures\n",
    "Based on parcel data (from Jasper County) make assumptions about buildings that might be residential buildings. \n",
    "\n",
    "The goal is to reduce the number of buildings that are counted as residential address points and limit the allocation of housing units to buildings that are commercial.\n",
    "\n",
    "The Joplin building data covers 2 counties - Jasper and Newton. There is parcel and zoning data for Jasper County but not for Newton County. In Newton county building footprint (square feet) may provide some details for residential structures."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore Parcel Zoning and Tax Data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>classv2</th>\n",
       "      <th>A</th>\n",
       "      <th>C</th>\n",
       "      <th>CR</th>\n",
       "      <th>E</th>\n",
       "      <th>EC</th>\n",
       "      <th>ER</th>\n",
       "      <th>R</th>\n",
       "      <th>RC</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>0</td>\n",
       "      <td>93</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>0</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>0</td>\n",
       "      <td>224</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>3</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>0</td>\n",
       "      <td>357</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>21</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7311</td>\n",
       "      <td>0</td>\n",
       "      <td>7394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1715</td>\n",
       "      <td>0</td>\n",
       "      <td>1795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>763</td>\n",
       "      <td>8</td>\n",
       "      <td>804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>124</td>\n",
       "      <td>0</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>1</td>\n",
       "      <td>954</td>\n",
       "      <td>55</td>\n",
       "      <td>112</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10286</td>\n",
       "      <td>11</td>\n",
       "      <td>11421</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "classv2  A    C  CR    E  EC  ER      R  RC  Total\n",
       "Zoning                                            \n",
       "C1       0   93   2    7   0   0     70   0    172\n",
       "C1-PD    0   26   0    2   0   0      0   0     28\n",
       "C2       0   76   1    7   0   0     25   0    109\n",
       "C2-PD    0   13   0    0   0   0      2   0     15\n",
       "C3       0  224  11    5   0   0     36   3    279\n",
       "C3-PD    0    8   0    0   0   0      3   0     11\n",
       "CO       0   21   2    2   0   0     47   0     72\n",
       "CO-PD    0   23   0    0   0   0      0   0     23\n",
       "M1       0    1   0    0   0   0      0   0      1\n",
       "M1-PD    0    0   0    0   0   0     11   0     11\n",
       "M2       0  357  11    9   0   0     79   0    456\n",
       "M2-PD    0   10   0    0   0   0      0   0     10\n",
       "R1       1   29  21   31   0   1   7311   0   7394\n",
       "R1-PD    0    0   0    0   0   0     18   0     18\n",
       "R2       0   54   0   26   0   0   1715   0   1795\n",
       "R2-PD    0    0   0   11   0   0     78   0     89\n",
       "R3       0   19   3   10   1   0    763   8    804\n",
       "R3-PD    0    0   4    2   0   0    124   0    130\n",
       "R4       0    0   0    0   0   0      4   0      4\n",
       "Total    1  954  55  112   1   1  10286  11  11421"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['Zoning'], building_gdf['classv2'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A parcel in Jasper County can have one of four class tyeps (A,C,E, and R). At this point there is not a codebook that explicitly describes these meanings of A, C, E, and R - however we can assume that R = Residential and C = Commercial. E probably means Exempt. \n",
    "The Class codes CR, EC, ER, and RC come from the collapsed Tax data. These parcels have mixed class information. \n",
    "\n",
    "The cross tabulation between Class and Parcel Zoning provides some evidence that this assumption is correct. For Class R parcels 7,311 are R-1 Single-Family Residential. 1,715 are R-2 Two-Family Residential, 763 are R-3 Apartment House."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>apcount</th>\n",
       "      <th>False</th>\n",
       "      <th>True</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>17</td>\n",
       "      <td>299</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>5</td>\n",
       "      <td>35</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>78</td>\n",
       "      <td>106</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>49</td>\n",
       "      <td>448</td>\n",
       "      <td>497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>4</td>\n",
       "      <td>19</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>19</td>\n",
       "      <td>127</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>7</td>\n",
       "      <td>25</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>3</td>\n",
       "      <td>35</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>262</td>\n",
       "      <td>529</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>62</td>\n",
       "      <td>12730</td>\n",
       "      <td>12792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>34</td>\n",
       "      <td>3927</td>\n",
       "      <td>3961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>19</td>\n",
       "      <td>1409</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>1</td>\n",
       "      <td>198</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>577</td>\n",
       "      <td>20078</td>\n",
       "      <td>20655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "apcount   False   True  Total\n",
       "Zoning                       \n",
       "C1           17    299    316\n",
       "C1-PD         5     35     40\n",
       "C2           78    106    184\n",
       "C2-PD         4     21     25\n",
       "C3           49    448    497\n",
       "C3-PD         4     19     23\n",
       "CO           19    127    146\n",
       "CO-PD         7     25     32\n",
       "M1           11      3     14\n",
       "M1-PD         3     35     38\n",
       "M2          262    529    791\n",
       "M2-PD         2     13     15\n",
       "MULTIPLE      0      2      2\n",
       "R1           62  12730  12792\n",
       "R1-PD         0     30     30\n",
       "R2           34   3927   3961\n",
       "R2-PD         0    114    114\n",
       "R3           19   1409   1428\n",
       "R3-PD         1    198    199\n",
       "R4            0      8      8\n",
       "Total       577  20078  20655"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Buildings by zoning where there is housing\n",
    "pd.crosstab(columns=[building_gdf['apcount']>0],index=[building_gdf['Zoning']], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>apcount</th>\n",
       "      <th>False</th>\n",
       "      <th>True</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>classv2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>389</td>\n",
       "      <td>1023</td>\n",
       "      <td>1412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CR</th>\n",
       "      <td>9</td>\n",
       "      <td>124</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>25</td>\n",
       "      <td>107</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ER</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>14</td>\n",
       "      <td>12730</td>\n",
       "      <td>12744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RC</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>437</td>\n",
       "      <td>14010</td>\n",
       "      <td>14447</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "apcount  False   True  Total\n",
       "classv2                     \n",
       "A            0      1      1\n",
       "C          389   1023   1412\n",
       "CR           9    124    133\n",
       "E           25    107    132\n",
       "EC           0      1      1\n",
       "ER           0      1      1\n",
       "R           14  12730  12744\n",
       "RC           0     23     23\n",
       "Total      437  14010  14447"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Buildings by class where there is housing\n",
    "pd.crosstab(columns=[building_gdf['apcount']>0],index=[building_gdf['classv2']], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>taxsheetv2</th>\n",
       "      <th>2010 Comm</th>\n",
       "      <th>2010 Comm2010 Res</th>\n",
       "      <th>2010 Res</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>classv2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>1365</td>\n",
       "      <td>21</td>\n",
       "      <td>26</td>\n",
       "      <td>1412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CR</th>\n",
       "      <td>8</td>\n",
       "      <td>118</td>\n",
       "      <td>7</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>75</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ER</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>188</td>\n",
       "      <td>54</td>\n",
       "      <td>12502</td>\n",
       "      <td>12744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RC</th>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>1624</td>\n",
       "      <td>211</td>\n",
       "      <td>12612</td>\n",
       "      <td>14447</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "taxsheetv2  2010 Comm  2010 Comm2010 Res  2010 Res  Total\n",
       "classv2                                                  \n",
       "A                   0                  0         1      1\n",
       "C                1365                 21        26   1412\n",
       "CR                  8                118         7    133\n",
       "E                  50                  7        75    132\n",
       "EC                  0                  1         0      1\n",
       "ER                  0                  0         1      1\n",
       "R                 188                 54     12502  12744\n",
       "RC                 13                 10         0     23\n",
       "Total            1624                211     12612  14447"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['classv2'], building_gdf['taxsheetv2'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>COUNTYFP10</th>\n",
       "      <th>97.0</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>classv2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>1412</td>\n",
       "      <td>1412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CR</th>\n",
       "      <td>133</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>132</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ER</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>12744</td>\n",
       "      <td>12744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RC</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>14447</td>\n",
       "      <td>14447</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "COUNTYFP10   97.0  Total\n",
       "classv2                 \n",
       "A               1      1\n",
       "C            1412   1412\n",
       "CR            133    133\n",
       "E             132    132\n",
       "EC              1      1\n",
       "ER              1      1\n",
       "R           12744  12744\n",
       "RC             23     23\n",
       "Total       14447  14447"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['classv2'], building_gdf['COUNTYFP10'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>taxsheetv2</th>\n",
       "      <th>2010 Comm</th>\n",
       "      <th>2010 Comm2010 Res</th>\n",
       "      <th>2010 Res</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>144</td>\n",
       "      <td>5</td>\n",
       "      <td>141</td>\n",
       "      <td>290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>123</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>328</td>\n",
       "      <td>14</td>\n",
       "      <td>86</td>\n",
       "      <td>428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>84</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>524</td>\n",
       "      <td>16</td>\n",
       "      <td>163</td>\n",
       "      <td>703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>53</td>\n",
       "      <td>33</td>\n",
       "      <td>12353</td>\n",
       "      <td>12439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>69</td>\n",
       "      <td>2</td>\n",
       "      <td>3749</td>\n",
       "      <td>3820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>102</td>\n",
       "      <td>13</td>\n",
       "      <td>1243</td>\n",
       "      <td>1358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>98</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>1553</td>\n",
       "      <td>84</td>\n",
       "      <td>18136</td>\n",
       "      <td>19773</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "taxsheetv2  2010 Comm  2010 Comm2010 Res  2010 Res  Total\n",
       "Zoning                                                   \n",
       "C1                144                  5       141    290\n",
       "C1-PD              29                  0        10     39\n",
       "C2                123                  1        25    149\n",
       "C2-PD              22                  0         0     22\n",
       "C3                328                 14        86    428\n",
       "C3-PD              16                  0         5     21\n",
       "CO                 36                  0        84    120\n",
       "CO-PD              32                  0         0     32\n",
       "M1                  4                  0         0      4\n",
       "M1-PD               4                  0        29     33\n",
       "M2                524                 16       163    703\n",
       "M2-PD              12                  0         2     14\n",
       "R1                 53                 33     12353  12439\n",
       "R1-PD               0                  0        30     30\n",
       "R2                 69                  2      3749   3820\n",
       "R2-PD               0                  0       112    112\n",
       "R3                102                 13      1243   1358\n",
       "R3-PD              55                  0        98    153\n",
       "R4                  0                  0         6      6\n",
       "Total            1553                 84     18136  19773"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['Zoning'], building_gdf['taxsheetv2'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>archtype</th>\n",
       "      <th>1</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>157</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>24</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "      <td>65</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>32</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>150</td>\n",
       "      <td>12</td>\n",
       "      <td>185</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>82</td>\n",
       "      <td>497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>98</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>192</td>\n",
       "      <td>4</td>\n",
       "      <td>121</td>\n",
       "      <td>297</td>\n",
       "      <td>74</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>77</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>12509</td>\n",
       "      <td>2</td>\n",
       "      <td>47</td>\n",
       "      <td>33</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>35</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>115</td>\n",
       "      <td>12792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>3854</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>54</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>3961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>1328</td>\n",
       "      <td>24</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>191</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>18727</td>\n",
       "      <td>58</td>\n",
       "      <td>548</td>\n",
       "      <td>505</td>\n",
       "      <td>104</td>\n",
       "      <td>35</td>\n",
       "      <td>21</td>\n",
       "      <td>7</td>\n",
       "      <td>21</td>\n",
       "      <td>68</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>21</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>491</td>\n",
       "      <td>20655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "archtype      1   5    6    7    8   9  10  11  12  13  14  15  16  17  18  \\\n",
       "Zoning                                                                       \n",
       "C1          157   0   55   24    5   1   0   0   0   2   3   1   2   5   0   \n",
       "C1-PD        11   2    9    1    0   1   0   0   1   0   0   0   0   0   0   \n",
       "C2           43   1   65    7    5   1   0   0   0   7   7   0   9   0   7   \n",
       "C2-PD         0   4   14    3    0   0   1   0   0   0   2   0   0   0   0   \n",
       "C3          150  12  185   50    2   0   0   0   0   5   3   4   4   0   0   \n",
       "C3-PD         6   0    8    5    0   0   0   0   0   0   0   1   1   0   0   \n",
       "CO           98   4    9    0    0   0   0   0  16   2   0   0   0   0   0   \n",
       "CO-PD         1   0    6    3    0   0   0   0   1   0   0   0   0   0   0   \n",
       "M1            0   0    3    5    0   0   0   0   0   0   0   0   0   0   0   \n",
       "M1-PD        32   0    0    4    0   0   0   0   0   0   0   0   1   0   0   \n",
       "M2          192   4  121  297   74   2   1   6   0   6   5   2   3   0   1   \n",
       "M2-PD         4   0    0    8    0   0   0   0   0   0   0   0   0   0   0   \n",
       "MULTIPLE      1   0    1    0    0   0   0   0   0   0   0   0   0   0   0   \n",
       "R1        12509   2   47   33   11  17  14   1   2  35   3   2   0   1   0   \n",
       "R1-PD        30   0    0    0    0   0   0   0   0   0   0   0   0   0   0   \n",
       "R2         3854   0   10   54    4  11   1   0   0   4   0   0   0   0   0   \n",
       "R2-PD       114   0    0    0    0   0   0   0   0   0   0   0   0   0   0   \n",
       "R3         1328  24   14   11    3   2   4   0   1   7   2   0   0   0   0   \n",
       "R3-PD       191   5    1    0    0   0   0   0   0   0   0   0   1   0   0   \n",
       "R4            6   0    0    0    0   0   0   0   0   0   0   0   0   0   0   \n",
       "Total     18727  58  548  505  104  35  21   7  21  68  25  10  21   6   8   \n",
       "\n",
       "archtype   19  Total  \n",
       "Zoning                \n",
       "C1         61    316  \n",
       "C1-PD      15     40  \n",
       "C2         32    184  \n",
       "C2-PD       1     25  \n",
       "C3         82    497  \n",
       "C3-PD       2     23  \n",
       "CO         17    146  \n",
       "CO-PD      21     32  \n",
       "M1          6     14  \n",
       "M1-PD       1     38  \n",
       "M2         77    791  \n",
       "M2-PD       3     15  \n",
       "MULTIPLE    0      2  \n",
       "R1        115  12792  \n",
       "R1-PD       0     30  \n",
       "R2         23   3961  \n",
       "R2-PD       0    114  \n",
       "R3         32   1428  \n",
       "R3-PD       1    199  \n",
       "R4          2      8  \n",
       "Total     491  20655  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['Zoning'], building_gdf['archtype'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>archtype</th>\n",
       "      <th>1</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>classv2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>156</td>\n",
       "      <td>10</td>\n",
       "      <td>341</td>\n",
       "      <td>481</td>\n",
       "      <td>112</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>253</td>\n",
       "      <td>1412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CR</th>\n",
       "      <td>58</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ER</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>12479</td>\n",
       "      <td>37</td>\n",
       "      <td>35</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>109</td>\n",
       "      <td>12744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RC</th>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>12782</td>\n",
       "      <td>65</td>\n",
       "      <td>399</td>\n",
       "      <td>605</td>\n",
       "      <td>114</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>21</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>15</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>394</td>\n",
       "      <td>14447</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "archtype      1   5    6    7    8  9  10  12  13  14  15  16  17  18   19  \\\n",
       "classv2                                                                      \n",
       "A             1   0    0    0    0  0   0   0   0   0   0   0   0   0    0   \n",
       "C           156  10  341  481  112  1   1   4   8   9  10  14   7   5  253   \n",
       "CR           58   2   11   48    0  2   0   0   0   0   0   0   0   0   12   \n",
       "E            78   1   12    4    2  1   0   1   8   3   1   1   0   0   20   \n",
       "EC            1   0    0    0    0  0   0   0   0   0   0   0   0   0    0   \n",
       "ER            1   0    0    0    0  0   0   0   0   0   0   0   0   0    0   \n",
       "R         12479  37   35   72    0  2   0   2   5   0   0   0   1   2  109   \n",
       "RC            8  15    0    0    0  0   0   0   0   0   0   0   0   0    0   \n",
       "Total     12782  65  399  605  114  6   1   7  21  12  11  15   8   7  394   \n",
       "\n",
       "archtype  Total  \n",
       "classv2          \n",
       "A             1  \n",
       "C          1412  \n",
       "CR          133  \n",
       "E           132  \n",
       "EC            1  \n",
       "ER            1  \n",
       "R         12744  \n",
       "RC           23  \n",
       "Total     14447  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['classv2'], building_gdf['archtype'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Building archetypes maybe helpful for identifing residential structures.\n",
    "Table 1. Types of buildings assumed to exist in virtual community of Centerville\n",
    "Building type\tBuilding description\n",
    "- T1\tResidential wood building, small rectangular plan, gable roof, 1 story\n",
    "- T2\tResidential wood building, small square plan, gable roof, 2 stories\n",
    "- T3\tResidential wood building, medium rectangular plan, gable roof, 1 story\n",
    "- T4\tResidential wood building, medium rectangular plan, hip roof, 2 stories\n",
    "- T5\tResidential wood building, large rectangular plan, gable roof, 2 stories\n",
    "- T6\tBusiness and retail building (strip mall)\n",
    "- T7\tLight industrial building\n",
    "- T8\tHeavy industrial building\n",
    "- T9\tElementary/middle school (unreinforced masonry)\n",
    "- T10\tHigh school (reinforced masonry)\n",
    "- T11\tFire/police station\n",
    "- T12\tHospital\n",
    "- T13\tCommunity center/church\n",
    "- T14\tGovernment building\n",
    "- T15\tLarge big-box\n",
    "- T16\tSmall big-box\n",
    "- T17\tMobile home\n",
    "- T18\tShopping center\n",
    "- T19\tOffice building\n",
    "\n",
    "Source: Memari, M., Attary, N., Masoomi, H., Mahmoud, H., van de Lindt, J. W., Pilkington, S. F., & Ameri, M. R. (2018). Minimal building fragility portfolio for damage assessment of communities subjected to tornadoes. Journal of Structural Engineering, 144(7), 04018072."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>COUNTYFP10</th>\n",
       "      <th>97.0</th>\n",
       "      <th>145.0</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>archtype</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21889</td>\n",
       "      <td>2868</td>\n",
       "      <td>24757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>88</td>\n",
       "      <td>58</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>678</td>\n",
       "      <td>58</td>\n",
       "      <td>736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>880</td>\n",
       "      <td>83</td>\n",
       "      <td>963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>150</td>\n",
       "      <td>5</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>36</td>\n",
       "      <td>3</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>21</td>\n",
       "      <td>20</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>83</td>\n",
       "      <td>5</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>13</td>\n",
       "      <td>366</td>\n",
       "      <td>379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>608</td>\n",
       "      <td>93</td>\n",
       "      <td>701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>24583</td>\n",
       "      <td>3569</td>\n",
       "      <td>28152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "COUNTYFP10   97.0  145.0  Total\n",
       "archtype                       \n",
       "1           21889   2868  24757\n",
       "5              88     58    146\n",
       "6             678     58    736\n",
       "7             880     83    963\n",
       "8             150      5    155\n",
       "9              36      3     39\n",
       "10             50      0     50\n",
       "11              7      1      8\n",
       "12             21     20     41\n",
       "13             83      5     88\n",
       "14             25      3     28\n",
       "15             19      2     21\n",
       "16             27      3     30\n",
       "17             13    366    379\n",
       "18              9      1     10\n",
       "19            608     93    701\n",
       "Total       24583   3569  28152"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['archtype'], building_gdf['COUNTYFP10'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Planned use of Detailed Parcel and Building Foot Print Data\n",
    "\n",
    "### For Parcels with Zoning and Tax Data\n",
    "1. All R1 Parcels will be assigned 1 address point\n",
    "2. All R2 Parcels will be assigned 2 address points\n",
    "3. All R3 Parcels will be assigned 3 address points \n",
    "4. All R3 and R4 parcels will be prioritized to recieve additional address points.\n",
    "4. Small building footprints (less than 300 sq feet - will not be counted as residential structures)\n",
    "\n",
    "### For Parcels with Tax Data but no Zoning\n",
    "1. All Class R parcels will be prioritized as residential\n",
    "2. If a parcel is Class C and on the 2010 Commercial Tax Sheet the parcel will be assigned 0 residential address points\n",
    "3. If a parcel has no other information but was on the Residential Tax Sheet assume it is residential."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "building_gdf['residentialAP1'] = 0\n",
    "building_gdf['residentialAP1'].label = \"Residential Address Point Round 1\"\n",
    "building_gdf['residentialAP1'].note = \"Residential Address Point - first attempt to assign residential address points to buildings\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>316</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>497</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>146</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>791</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>0</td>\n",
       "      <td>12792</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3961</td>\n",
       "      <td>0</td>\n",
       "      <td>3961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>199</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>2123</td>\n",
       "      <td>12830</td>\n",
       "      <td>4075</td>\n",
       "      <td>1627</td>\n",
       "      <td>20655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1     0      1     2     3  Total\n",
       "Zoning                                        \n",
       "C1               316      0     0     0    316\n",
       "C1-PD             40      0     0     0     40\n",
       "C2               184      0     0     0    184\n",
       "C2-PD             25      0     0     0     25\n",
       "C3               497      0     0     0    497\n",
       "C3-PD             23      0     0     0     23\n",
       "CO               146      0     0     0    146\n",
       "CO-PD             32      0     0     0     32\n",
       "M1                14      0     0     0     14\n",
       "M1-PD             38      0     0     0     38\n",
       "M2               791      0     0     0    791\n",
       "M2-PD             15      0     0     0     15\n",
       "MULTIPLE           2      0     0     0      2\n",
       "R1                 0  12792     0     0  12792\n",
       "R1-PD              0     30     0     0     30\n",
       "R2                 0      0  3961     0   3961\n",
       "R2-PD              0      0   114     0    114\n",
       "R3                 0      0     0  1428   1428\n",
       "R3-PD              0      0     0   199    199\n",
       "R4                 0      8     0     0      8\n",
       "Total           2123  12830  4075  1627  20655"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf.loc[building_gdf['Zoning'] == \"R1\",'residentialAP1'] = 1\n",
    "building_gdf.loc[building_gdf['Zoning'] == \"R1-PD\",'residentialAP1'] = 1\n",
    "building_gdf.loc[building_gdf['Zoning'] == \"R2\",'residentialAP1'] = 2\n",
    "building_gdf.loc[building_gdf['Zoning'] == \"R2-PD\",'residentialAP1'] = 2\n",
    "building_gdf.loc[building_gdf['Zoning'] == \"R3\",'residentialAP1'] = 3\n",
    "building_gdf.loc[building_gdf['Zoning'] == \"R3-PD\",'residentialAP1'] = 3\n",
    "building_gdf.loc[building_gdf['Zoning'] == \"R4\",'residentialAP1'] = 1\n",
    "pd.crosstab(building_gdf['Zoning'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>244</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>158</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>447</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>97</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>27</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>701</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>0</td>\n",
       "      <td>12792</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3961</td>\n",
       "      <td>0</td>\n",
       "      <td>3961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>199</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>1820</td>\n",
       "      <td>13133</td>\n",
       "      <td>4075</td>\n",
       "      <td>1627</td>\n",
       "      <td>20655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1     0      1     2     3  Total\n",
       "Zoning                                        \n",
       "C1               244     72     0     0    316\n",
       "C1-PD             40      0     0     0     40\n",
       "C2               158     26     0     0    184\n",
       "C2-PD             23      2     0     0     25\n",
       "C3               447     50     0     0    497\n",
       "C3-PD             20      3     0     0     23\n",
       "CO                97     49     0     0    146\n",
       "CO-PD             32      0     0     0     32\n",
       "M1                14      0     0     0     14\n",
       "M1-PD             27     11     0     0     38\n",
       "M2               701     90     0     0    791\n",
       "M2-PD             15      0     0     0     15\n",
       "MULTIPLE           2      0     0     0      2\n",
       "R1                 0  12792     0     0  12792\n",
       "R1-PD              0     30     0     0     30\n",
       "R2                 0      0  3961     0   3961\n",
       "R2-PD              0      0   114     0    114\n",
       "R3                 0      0     0  1428   1428\n",
       "R3-PD              0      0     0   199    199\n",
       "R4                 0      8     0     0      8\n",
       "Total           1820  13133  4075  1627  20655"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf.loc[(building_gdf['classv2'].isin([\"R\",\"RC\",\"CR\"])) & (building_gdf['residentialAP1']==0),'residentialAP1'] = 1\n",
    "pd.crosstab(building_gdf['Zoning'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxsheetv2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010 Comm</th>\n",
       "      <td>1771</td>\n",
       "      <td>128</td>\n",
       "      <td>69</td>\n",
       "      <td>157</td>\n",
       "      <td>2125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 Comm2010 Res</th>\n",
       "      <td>19</td>\n",
       "      <td>182</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 Res</th>\n",
       "      <td>626</td>\n",
       "      <td>15016</td>\n",
       "      <td>3861</td>\n",
       "      <td>1341</td>\n",
       "      <td>20844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>2416</td>\n",
       "      <td>15326</td>\n",
       "      <td>3932</td>\n",
       "      <td>1511</td>\n",
       "      <td>23185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1        0      1     2     3  Total\n",
       "taxsheetv2                                       \n",
       "2010 Comm          1771    128    69   157   2125\n",
       "2010 Comm2010 Res    19    182     2    13    216\n",
       "2010 Res            626  15016  3861  1341  20844\n",
       "Total              2416  15326  3932  1511  23185"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['taxsheetv2'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxsheetv2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010 Comm</th>\n",
       "      <td>1771</td>\n",
       "      <td>128</td>\n",
       "      <td>69</td>\n",
       "      <td>157</td>\n",
       "      <td>2125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 Comm2010 Res</th>\n",
       "      <td>19</td>\n",
       "      <td>182</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 Res</th>\n",
       "      <td>0</td>\n",
       "      <td>15642</td>\n",
       "      <td>3861</td>\n",
       "      <td>1341</td>\n",
       "      <td>20844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>1790</td>\n",
       "      <td>15952</td>\n",
       "      <td>3932</td>\n",
       "      <td>1511</td>\n",
       "      <td>23185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1        0      1     2     3  Total\n",
       "taxsheetv2                                       \n",
       "2010 Comm          1771    128    69   157   2125\n",
       "2010 Comm2010 Res    19    182     2    13    216\n",
       "2010 Res              0  15642  3861  1341  20844\n",
       "Total              1790  15952  3932  1511  23185"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# If Parcel is on the 2010 Residential Tax Sheet but is zoning is not residential assume residential\n",
    "building_gdf.loc[(building_gdf['taxsheetv2']==\"2010 Res\") & \n",
    "                 (building_gdf['residentialAP1']==0),'residentialAP1'] = 1\n",
    "pd.crosstab(building_gdf['taxsheetv2'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxsheetv2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010 Comm</th>\n",
       "      <td>1818</td>\n",
       "      <td>81</td>\n",
       "      <td>69</td>\n",
       "      <td>157</td>\n",
       "      <td>2125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 Comm2010 Res</th>\n",
       "      <td>19</td>\n",
       "      <td>182</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 Res</th>\n",
       "      <td>0</td>\n",
       "      <td>15642</td>\n",
       "      <td>3861</td>\n",
       "      <td>1341</td>\n",
       "      <td>20844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>1837</td>\n",
       "      <td>15905</td>\n",
       "      <td>3932</td>\n",
       "      <td>1511</td>\n",
       "      <td>23185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1        0      1     2     3  Total\n",
       "taxsheetv2                                       \n",
       "2010 Comm          1818     81    69   157   2125\n",
       "2010 Comm2010 Res    19    182     2    13    216\n",
       "2010 Res              0  15642  3861  1341  20844\n",
       "Total              1837  15905  3932  1511  23185"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# If a parcel is Class C and on the 2010 Commercial Tax Sheet make Residential Address Point 0\n",
    "building_gdf.loc[(building_gdf['classv2'].isin([\"R\",\"RC\",\"CR\"])==False) & \n",
    "                 (building_gdf['taxsheetv2']==\"2010 Comm\") & \n",
    "                 (building_gdf['Zoning']==\"R1\"),'residentialAP1'] = 0\n",
    "pd.crosstab(building_gdf['taxsheetv2'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assume all buildings in Newton County are Residential"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97.0</th>\n",
       "      <td>2621</td>\n",
       "      <td>16260</td>\n",
       "      <td>4075</td>\n",
       "      <td>1627</td>\n",
       "      <td>24583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145.0</th>\n",
       "      <td>3569</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>6190</td>\n",
       "      <td>16260</td>\n",
       "      <td>4075</td>\n",
       "      <td>1627</td>\n",
       "      <td>28152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1     0      1     2     3  Total\n",
       "COUNTYFP10                                    \n",
       "97.0            2621  16260  4075  1627  24583\n",
       "145.0           3569      0     0     0   3569\n",
       "Total           6190  16260  4075  1627  28152"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf['COUNTYFP10'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97.0</th>\n",
       "      <td>2621</td>\n",
       "      <td>16260</td>\n",
       "      <td>4075</td>\n",
       "      <td>1627</td>\n",
       "      <td>24583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145.0</th>\n",
       "      <td>0</td>\n",
       "      <td>3569</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>2621</td>\n",
       "      <td>19829</td>\n",
       "      <td>4075</td>\n",
       "      <td>1627</td>\n",
       "      <td>28152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1     0      1     2     3  Total\n",
       "COUNTYFP10                                    \n",
       "97.0            2621  16260  4075  1627  24583\n",
       "145.0              0   3569     0     0   3569\n",
       "Total           2621  19829  4075  1627  28152"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For Newton County Make residentialAP1 = 1 to 1 for all buildings\n",
    "building_gdf.loc[building_gdf['COUNTYFP10'] == 145,'residentialAP1'] = 1\n",
    "pd.crosstab(building_gdf['COUNTYFP10'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assume all buildings with an area of less than 30 square meters is has no address point\n",
    "The building footprint data includes many small buildings that could be detached garages or sheds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>180</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>31</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>156</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>399</td>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>60</td>\n",
       "      <td>86</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>8</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>622</td>\n",
       "      <td>169</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>392</td>\n",
       "      <td>12400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>349</td>\n",
       "      <td>0</td>\n",
       "      <td>3612</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1    0      1     2     3\n",
       "Zoning                                \n",
       "C1              180    136     0     0\n",
       "C1-PD            31      9     0     0\n",
       "C2              156     28     0     0\n",
       "C2-PD            23      2     0     0\n",
       "C3              399     98     0     0\n",
       "C3-PD            18      5     0     0\n",
       "CO               60     86     0     0\n",
       "CO-PD            32      0     0     0\n",
       "M1               14      0     0     0\n",
       "M1-PD             8     30     0     0\n",
       "M2              622    169     0     0\n",
       "M2-PD            13      2     0     0\n",
       "MULTIPLE          2      0     0     0\n",
       "R1              392  12400     0     0\n",
       "R1-PD             0     30     0     0\n",
       "R2              349      0  3612     0\n",
       "R2-PD             0      0   114     0\n",
       "R3               54      0     0  1374\n",
       "R3-PD             0      0     0   199\n",
       "R4                0      8     0     0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove small buildings from residential bulding list\n",
    "building_gdf.loc[building_gdf['gsq_meter'] < 30,'residentialAP1'] = 0\n",
    "pd.crosstab(building_gdf['Zoning'], building_gdf['residentialAP1'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extend small square footage to buildings assumed to have 2 to 3 address points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2.815200e+04\n",
       "mean              inf\n",
       "std               NaN\n",
       "min      1.003998e+01\n",
       "25%      8.854690e+01\n",
       "50%      1.648335e+02\n",
       "75%      2.693805e+02\n",
       "max               inf\n",
       "Name: gsq_meter_by_AP, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Look at shape area divided by the number of address points\n",
    "building_gdf['gsq_meter_by_AP'] = building_gdf['gsq_meter'] / building_gdf['residentialAP1']\n",
    "building_gdf['gsq_meter_by_AP'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    764.000000\n",
       "mean      22.191337\n",
       "std        4.799981\n",
       "min       10.039977\n",
       "25%       18.200337\n",
       "50%       22.606294\n",
       "75%       26.255939\n",
       "max       29.985586\n",
       "Name: gsq_meter_by_AP, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf['gsq_meter_by_AP'].loc[building_gdf['gsq_meter_by_AP'] < 30 ].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>180</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>31</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>156</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>399</td>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>60</td>\n",
       "      <td>86</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>8</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>622</td>\n",
       "      <td>169</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>392</td>\n",
       "      <td>12400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>816</td>\n",
       "      <td>0</td>\n",
       "      <td>3145</td>\n",
       "      <td>0</td>\n",
       "      <td>3961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>111</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>346</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1082</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>197</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>3117</td>\n",
       "      <td>13003</td>\n",
       "      <td>3256</td>\n",
       "      <td>1279</td>\n",
       "      <td>20655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1     0      1     2     3  Total\n",
       "Zoning                                        \n",
       "C1               180    136     0     0    316\n",
       "C1-PD             31      9     0     0     40\n",
       "C2               156     28     0     0    184\n",
       "C2-PD             23      2     0     0     25\n",
       "C3               399     98     0     0    497\n",
       "C3-PD             18      5     0     0     23\n",
       "CO                60     86     0     0    146\n",
       "CO-PD             32      0     0     0     32\n",
       "M1                14      0     0     0     14\n",
       "M1-PD              8     30     0     0     38\n",
       "M2               622    169     0     0    791\n",
       "M2-PD             13      2     0     0     15\n",
       "MULTIPLE           2      0     0     0      2\n",
       "R1               392  12400     0     0  12792\n",
       "R1-PD              0     30     0     0     30\n",
       "R2               816      0  3145     0   3961\n",
       "R2-PD              3      0   111     0    114\n",
       "R3               346      0     0  1082   1428\n",
       "R3-PD              2      0     0   197    199\n",
       "R4                 0      8     0     0      8\n",
       "Total           3117  13003  3256  1279  20655"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove small buildings from residential bulding list\n",
    "building_gdf.loc[building_gdf['gsq_meter_by_AP'] < 30,'residentialAP1'] = 0\n",
    "pd.crosstab(building_gdf['Zoning'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>189</td>\n",
       "      <td>127</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>31</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>161</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>407</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>68</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>649</td>\n",
       "      <td>142</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>1781</td>\n",
       "      <td>11011</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>1099</td>\n",
       "      <td>0</td>\n",
       "      <td>2862</td>\n",
       "      <td>0</td>\n",
       "      <td>3961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>111</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>378</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1050</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>196</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>4884</td>\n",
       "      <td>11552</td>\n",
       "      <td>2973</td>\n",
       "      <td>1246</td>\n",
       "      <td>20655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1     0      1     2     3  Total\n",
       "Zoning                                        \n",
       "C1               189    127     0     0    316\n",
       "C1-PD             31      9     0     0     40\n",
       "C2               161     23     0     0    184\n",
       "C2-PD             23      2     0     0     25\n",
       "C3               407     90     0     0    497\n",
       "C3-PD             18      5     0     0     23\n",
       "CO                68     78     0     0    146\n",
       "CO-PD             32      0     0     0     32\n",
       "M1                14      0     0     0     14\n",
       "M1-PD              9     29     0     0     38\n",
       "M2               649    142     0     0    791\n",
       "M2-PD             14      1     0     0     15\n",
       "MULTIPLE           2      0     0     0      2\n",
       "R1              1781  11011     0     0  12792\n",
       "R1-PD              1     29     0     0     30\n",
       "R2              1099      0  2862     0   3961\n",
       "R2-PD              3      0   111     0    114\n",
       "R3               378      0     0  1050   1428\n",
       "R3-PD              3      0     0   196    199\n",
       "R4                 2      6     0     0      8\n",
       "Total           4884  11552  2973  1246  20655"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For Parcels with Designation Residential remove smaller building on parcel\n",
    "# It looks like in the Building Inventory if there is no House Number the building is tha auxillary building\n",
    "building_gdf.loc[(building_gdf['prclbldsum'] == 2) &\n",
    "                 (building_gdf['HOUSE_NO'].isna()),'residentialAP1'] = 0\n",
    "pd.crosstab(building_gdf['Zoning'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoning</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C1</th>\n",
       "      <td>189</td>\n",
       "      <td>127</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C1-PD</th>\n",
       "      <td>31</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2</th>\n",
       "      <td>161</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C2-PD</th>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3</th>\n",
       "      <td>407</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C3-PD</th>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>68</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO-PD</th>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1</th>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M1-PD</th>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2</th>\n",
       "      <td>649</td>\n",
       "      <td>142</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M2-PD</th>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTIPLE</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>1781</td>\n",
       "      <td>11011</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R1-PD</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>1099</td>\n",
       "      <td>0</td>\n",
       "      <td>2862</td>\n",
       "      <td>0</td>\n",
       "      <td>3961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2-PD</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>111</td>\n",
       "      <td>0</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>378</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1050</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3-PD</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>196</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R4</th>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>4884</td>\n",
       "      <td>11552</td>\n",
       "      <td>2973</td>\n",
       "      <td>1246</td>\n",
       "      <td>20655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1     0      1     2     3  Total\n",
       "Zoning                                        \n",
       "C1               189    127     0     0    316\n",
       "C1-PD             31      9     0     0     40\n",
       "C2               161     23     0     0    184\n",
       "C2-PD             23      2     0     0     25\n",
       "C3               407     90     0     0    497\n",
       "C3-PD             18      5     0     0     23\n",
       "CO                68     78     0     0    146\n",
       "CO-PD             32      0     0     0     32\n",
       "M1                14      0     0     0     14\n",
       "M1-PD              9     29     0     0     38\n",
       "M2               649    142     0     0    791\n",
       "M2-PD             14      1     0     0     15\n",
       "MULTIPLE           2      0     0     0      2\n",
       "R1              1781  11011     0     0  12792\n",
       "R1-PD              1     29     0     0     30\n",
       "R2              1099      0  2862     0   3961\n",
       "R2-PD              3      0   111     0    114\n",
       "R3               378      0     0  1050   1428\n",
       "R3-PD              3      0     0   196    199\n",
       "R4                 2      6     0     0      8\n",
       "Total           4884  11552  2973  1246  20655"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# If Address Point Count (Housing10 + Group Quarters) from Census is 0 then Residential Address Point is also 0\n",
    "building_gdf.loc[building_gdf['apcount'] == 0,'residentialAP1'] = 0\n",
    "pd.crosstab(building_gdf['Zoning'], building_gdf['residentialAP1'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Residential Address Point Count')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare Residential Address Point Count to Square Footage\n",
    "x = building_gdf['gsq_meter']\n",
    "y = building_gdf['residentialAP1']\n",
    "plt.scatter(x, y)\n",
    "plt.xlabel(\"Ground Square Meters\")\n",
    "plt.ylabel(\"Residential Address Point Count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>residentialAP1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6614.0</td>\n",
       "      <td>393.756252</td>\n",
       "      <td>1770.592690</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>48.146949</td>\n",
       "      <td>79.762566</td>\n",
       "      <td>227.718975</td>\n",
       "      <td>90132.331610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17319.0</td>\n",
       "      <td>222.148552</td>\n",
       "      <td>350.278464</td>\n",
       "      <td>30.494645</td>\n",
       "      <td>131.283606</td>\n",
       "      <td>183.643994</td>\n",
       "      <td>249.581940</td>\n",
       "      <td>20216.545735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2973.0</td>\n",
       "      <td>171.762246</td>\n",
       "      <td>250.293965</td>\n",
       "      <td>60.472302</td>\n",
       "      <td>112.259530</td>\n",
       "      <td>142.225596</td>\n",
       "      <td>176.481417</td>\n",
       "      <td>6711.545752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1246.0</td>\n",
       "      <td>229.738183</td>\n",
       "      <td>296.770005</td>\n",
       "      <td>90.225096</td>\n",
       "      <td>130.671126</td>\n",
       "      <td>168.991018</td>\n",
       "      <td>248.391296</td>\n",
       "      <td>8173.997830</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  count        mean          std        min         25%  \\\n",
       "residentialAP1                                                            \n",
       "0                6614.0  393.756252  1770.592690   0.000336   48.146949   \n",
       "1               17319.0  222.148552   350.278464  30.494645  131.283606   \n",
       "2                2973.0  171.762246   250.293965  60.472302  112.259530   \n",
       "3                1246.0  229.738183   296.770005  90.225096  130.671126   \n",
       "\n",
       "                       50%         75%           max  \n",
       "residentialAP1                                        \n",
       "0                79.762566  227.718975  90132.331610  \n",
       "1               183.643994  249.581940  20216.545735  \n",
       "2               142.225596  176.481417   6711.545752  \n",
       "3               168.991018  248.391296   8173.997830  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf['gsq_meter'].groupby(building_gdf['residentialAP1']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>bldg_id</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>HOUSING10</th>\n",
       "      <th>apcount</th>\n",
       "      <th>HOUSE_NO</th>\n",
       "      <th>prclbldsum</th>\n",
       "      <th>Zoning</th>\n",
       "      <th>classv2</th>\n",
       "      <th>taxsheetv2</th>\n",
       "      <th>gsq_meter</th>\n",
       "      <th>residentialAP1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B0000001</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2519</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>107.940427</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B0000002</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2515</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>169.494274</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B0000003</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2511</td>\n",
       "      <td>1.0</td>\n",
       "      <td>CO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.622453</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B0000004</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2511</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>185.178358</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B0000005</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2501</td>\n",
       "      <td>1.0</td>\n",
       "      <td>C1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>202.291430</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>B0000006</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2419</td>\n",
       "      <td>1.0</td>\n",
       "      <td>C1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>189.289577</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>B0000007</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2401</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>212.088491</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>B0000008</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2400</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>228.627892</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>B0000009</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2408</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>220.681636</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>B0000010</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2420</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>345.690083</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>B0000011</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2508</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>R</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>165.511221</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>B0000012</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2512</td>\n",
       "      <td>2.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>127.251227</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>B0000014</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2518</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>R</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>127.895030</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>B0000015</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2221</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R3-PD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>150.642202</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>B0000016</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2301</td>\n",
       "      <td>1.0</td>\n",
       "      <td>C1-PD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>169.669840</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>B0000017</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2331</td>\n",
       "      <td>1.0</td>\n",
       "      <td>C1-PD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>222.126191</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>B0000018</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2401</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>250.465266</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>B0000019</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2425</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>209.737357</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>B0000020</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2429</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>466.817381</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>B0000021</td>\n",
       "      <td>97.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2431</td>\n",
       "      <td>1.0</td>\n",
       "      <td>R1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010 Res</td>\n",
       "      <td>185.645246</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     bldg_id  COUNTYFP10  HOUSING10  apcount HOUSE_NO  prclbldsum Zoning  \\\n",
       "0   B0000001        97.0      103.0    103.0     2519         1.0     R1   \n",
       "1   B0000002        97.0      103.0    103.0     2515         1.0     R1   \n",
       "2   B0000003        97.0      103.0    103.0     2511         1.0     CO   \n",
       "3   B0000004        97.0      103.0    103.0     2511         1.0     R1   \n",
       "4   B0000005        97.0      103.0    103.0     2501         1.0     C1   \n",
       "5   B0000006        97.0      103.0    103.0     2419         1.0     C1   \n",
       "6   B0000007        97.0      103.0    103.0     2401         1.0     R1   \n",
       "7   B0000008        97.0      103.0    103.0     2400         1.0     R1   \n",
       "8   B0000009        97.0      103.0    103.0     2408         1.0     R1   \n",
       "9   B0000010        97.0      103.0    103.0     2420         1.0     R1   \n",
       "10  B0000011        97.0      103.0    103.0     2508         1.0     R1   \n",
       "11  B0000012        97.0      103.0    103.0     2512         2.0     R1   \n",
       "12  B0000014        97.0      103.0    103.0     2518         1.0     R1   \n",
       "13  B0000015        97.0      103.0    103.0     2221         1.0  R3-PD   \n",
       "14  B0000016        97.0      103.0    103.0     2301         1.0  C1-PD   \n",
       "15  B0000017        97.0      103.0    103.0     2331         1.0  C1-PD   \n",
       "16  B0000018        97.0      103.0    103.0     2401         1.0     R1   \n",
       "17  B0000019        97.0      103.0    103.0     2425         1.0     R1   \n",
       "18  B0000020        97.0      103.0    103.0     2429         1.0     R1   \n",
       "19  B0000021        97.0      103.0    103.0     2431         1.0     R1   \n",
       "\n",
       "   classv2 taxsheetv2   gsq_meter  residentialAP1  \n",
       "0      NaN   2010 Res  107.940427               1  \n",
       "1      NaN   2010 Res  169.494274               1  \n",
       "2      NaN        NaN   93.622453               0  \n",
       "3      NaN   2010 Res  185.178358               1  \n",
       "4      NaN   2010 Res  202.291430               1  \n",
       "5      NaN   2010 Res  189.289577               1  \n",
       "6      NaN   2010 Res  212.088491               1  \n",
       "7      NaN   2010 Res  228.627892               1  \n",
       "8      NaN   2010 Res  220.681636               1  \n",
       "9      NaN   2010 Res  345.690083               1  \n",
       "10       R   2010 Res  165.511221               1  \n",
       "11     NaN   2010 Res  127.251227               1  \n",
       "12       R   2010 Res  127.895030               1  \n",
       "13     NaN   2010 Res  150.642202               3  \n",
       "14     NaN   2010 Res  169.669840               1  \n",
       "15     NaN   2010 Res  222.126191               1  \n",
       "16     NaN   2010 Res  250.465266               1  \n",
       "17     NaN   2010 Res  209.737357               1  \n",
       "18     NaN   2010 Res  466.817381               1  \n",
       "19     NaN   2010 Res  185.645246               1  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf[['bldg_id','COUNTYFP10','HOUSING10','apcount','HOUSE_NO','prclbldsum',\n",
    "              'Zoning','classv2','taxsheetv2','gsq_meter','residentialAP1']].head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sum Residential Addresspoints (first attempt) by blockid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\nathanael99\\AppData\\Local\\Continuum\\anaconda3\\envs\\pyincore20190618\\lib\\site-packages\\ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  after removing the cwd from sys.path.\n"
     ]
    },
    {
     "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>residentialAP1</th>\n",
       "      <th>bldgcount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>290970101001000</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001001</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001002</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001003</th>\n",
       "      <td>29</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001006</th>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 residentialAP1  bldgcount\n",
       "BLOCKID10                                 \n",
       "290970101001000               5          5\n",
       "290970101001001               2          2\n",
       "290970101001002               3          4\n",
       "290970101001003              29         33\n",
       "290970101001006               5         10"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sum Buildings over the column BLOCKID.\n",
    "# https://www.geeksforgeeks.org/python-pandas-dataframe-sum/\n",
    "block_rap1_gdf = building_gdf[['BLOCKID10','residentialAP1']]\n",
    "block_rap1_gdf['bldgcount'] = 1\n",
    "block_rap1_gdf_sum = block_rap1_gdf.groupby(['BLOCKID10']).sum()\n",
    "block_rap1_gdf_sum.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1829.000000\n",
       "mean       14.763805\n",
       "std        17.273099\n",
       "min         0.000000\n",
       "25%         5.000000\n",
       "50%        12.000000\n",
       "75%        19.000000\n",
       "max       217.000000\n",
       "Name: residentialAP1, dtype: float64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "block_rap1_gdf_sum['residentialAP1'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge Sum of Estimated Sum of Address Points with Census Block Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Unnamed: 0</th>\n",
       "      <th>STATEFP10</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>TRACTCE10</th>\n",
       "      <th>BLOCKCE</th>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th>PARTFLG</th>\n",
       "      <th>HOUSING10</th>\n",
       "      <th>POP10</th>\n",
       "      <th>geometry</th>\n",
       "      <th>...</th>\n",
       "      <th>blk104269</th>\n",
       "      <th>blockid</th>\n",
       "      <th>apcount</th>\n",
       "      <th>pop10</th>\n",
       "      <th>gqpop10</th>\n",
       "      <th>popdiff</th>\n",
       "      <th>PLCGEOID10</th>\n",
       "      <th>PLCNAME10</th>\n",
       "      <th>PUMGEOID10</th>\n",
       "      <th>PUMNAME10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1047</td>\n",
       "      <td>290970121001047</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>POLYGON ((-94.13775 37.32550000000001, -94.138...</td>\n",
       "      <td>...</td>\n",
       "      <td>POLYGON ((-94.13775 37.32550000000001, -94.138...</td>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1050</td>\n",
       "      <td>290970121001050</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>POLYGON ((-94.137637 37.328675, -94.119315 37....</td>\n",
       "      <td>...</td>\n",
       "      <td>POLYGON ((-94.137637 37.328675, -94.119315 37....</td>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1094</td>\n",
       "      <td>290970121001094</td>\n",
       "      <td>N</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>POLYGON ((-94.214761 37.293836, -94.230751 37....</td>\n",
       "      <td>...</td>\n",
       "      <td>POLYGON ((-94.214761 37.293836, -94.230751 37....</td>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1093</td>\n",
       "      <td>290970121001093</td>\n",
       "      <td>N</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>POLYGON ((-94.197294 37.27723599999999, -94.19...</td>\n",
       "      <td>...</td>\n",
       "      <td>POLYGON ((-94.197294 37.27723599999999, -94.19...</td>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1130</td>\n",
       "      <td>290970121001130</td>\n",
       "      <td>N</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>POLYGON ((-94.151792 37.276275, -94.1519139999...</td>\n",
       "      <td>...</td>\n",
       "      <td>POLYGON ((-94.151792 37.276275, -94.1519139999...</td>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  STATEFP10  COUNTYFP10  TRACTCE10  BLOCKCE        BLOCKID10  \\\n",
       "0           0         29          97      12100     1047  290970121001047   \n",
       "1           1         29          97      12100     1050  290970121001050   \n",
       "2           2         29          97      12100     1094  290970121001094   \n",
       "3           3         29          97      12100     1093  290970121001093   \n",
       "4           4         29          97      12100     1130  290970121001130   \n",
       "\n",
       "  PARTFLG  HOUSING10  POP10  \\\n",
       "0       N          2      4   \n",
       "1       N          3      7   \n",
       "2       N          4     13   \n",
       "3       N          5      5   \n",
       "4       N          4      9   \n",
       "\n",
       "                                            geometry  ...  \\\n",
       "0  POLYGON ((-94.13775 37.32550000000001, -94.138...  ...   \n",
       "1  POLYGON ((-94.137637 37.328675, -94.119315 37....  ...   \n",
       "2  POLYGON ((-94.214761 37.293836, -94.230751 37....  ...   \n",
       "3  POLYGON ((-94.197294 37.27723599999999, -94.19...  ...   \n",
       "4  POLYGON ((-94.151792 37.276275, -94.1519139999...  ...   \n",
       "\n",
       "                                           blk104269       blockid apcount  \\\n",
       "0  POLYGON ((-94.13775 37.32550000000001, -94.138...  2.909701e+14     2.0   \n",
       "1  POLYGON ((-94.137637 37.328675, -94.119315 37....  2.909701e+14     3.0   \n",
       "2  POLYGON ((-94.214761 37.293836, -94.230751 37....  2.909701e+14     4.0   \n",
       "3  POLYGON ((-94.197294 37.27723599999999, -94.19...  2.909701e+14     5.0   \n",
       "4  POLYGON ((-94.151792 37.276275, -94.1519139999...  2.909701e+14     4.0   \n",
       "\n",
       "   pop10  gqpop10  popdiff  PLCGEOID10  PLCNAME10  PUMGEOID10  \\\n",
       "0    4.0      0.0      0.0         NaN        NaN     2902800   \n",
       "1    7.0      0.0      0.0         NaN        NaN     2902800   \n",
       "2   13.0      0.0      0.0         NaN        NaN     2902800   \n",
       "3    5.0      0.0      0.0         NaN        NaN     2902800   \n",
       "4    9.0      0.0      0.0         NaN        NaN     2902800   \n",
       "\n",
       "                       PUMNAME10  \n",
       "0  Jasper & Newton Counties PUMA  \n",
       "1  Jasper & Newton Counties PUMA  \n",
       "2  Jasper & Newton Counties PUMA  \n",
       "3  Jasper & Newton Counties PUMA  \n",
       "4  Jasper & Newton Counties PUMA  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in Census Block Data\n",
    "source_program = 'IN-CORE_1av2_Joplin_CleanBlockData_2019-07-10'\n",
    "census_blocks_csv = source_program+\"/\"+source_program+\"EPSG4269.csv\"\n",
    "census_blocks_df = pd.read_csv(census_blocks_csv)\n",
    "census_blocks_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>BLOCKID10</th>\n",
       "      <th>residentialAP1</th>\n",
       "      <th>apcount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4.790000e+02</td>\n",
       "      <td>479.000000</td>\n",
       "      <td>479.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.910343e+14</td>\n",
       "      <td>11.812109</td>\n",
       "      <td>11.812109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.635169e+11</td>\n",
       "      <td>7.719872</td>\n",
       "      <td>7.719872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>11.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.914502e+14</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>65.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          BLOCKID10  residentialAP1     apcount\n",
       "count  4.790000e+02      479.000000  479.000000\n",
       "mean   2.910343e+14       11.812109   11.812109\n",
       "std    1.635169e+11        7.719872    7.719872\n",
       "min    2.909701e+14        1.000000    1.000000\n",
       "25%    2.909701e+14        7.000000    7.000000\n",
       "50%    2.909701e+14       11.000000   11.000000\n",
       "75%    2.909701e+14       16.000000   16.000000\n",
       "max    2.914502e+14       65.000000   65.000000"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge Sum of Residential Address Points with Census Counts\n",
    "census_blocks_df_rap1 = pd.merge(census_blocks_df, block_rap1_gdf_sum,\n",
    "                                  left_on='BLOCKID10', right_on='BLOCKID10', how='left')\n",
    "displaycols = ['BLOCKID10','residentialAP1','apcount']\n",
    "condition = census_blocks_df_rap1['residentialAP1']==census_blocks_df_rap1['apcount']\n",
    "census_blocks_df_rap1[displaycols].loc[condition].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Error Check 1 - Are there Blocks in Joplin that have Housing Units by the Estimated Number of Housing Units is 0 or Missing?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Housing Unit Count')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare Bldg Count to Housing 10\n",
    "x = census_blocks_df_rap1['residentialAP1']\n",
    "y = census_blocks_df_rap1['apcount']\n",
    "plt.scatter(x, y)\n",
    "plt.xlabel(\"Residential Address Count Round 1\")\n",
    "plt.ylabel(\"Housing Unit Count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Error Check Options\n",
    "### Two Areas to Focus on Inside Joplin Area and Outside Joplin Area\n",
    "#### For places outside of Joplin Census Boundary there could be Buildings\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "census_blocks_df_rap1.loc[census_blocks_df_rap1['PLCNAME10'] == \"Joplin\",'Joplin'] = \"Joplin\"\n",
    "census_blocks_df_rap1.loc[census_blocks_df_rap1['PLCNAME10'] != \"Joplin\",'Joplin'] = \"Not Joplin\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>Joplin</th>\n",
       "      <th>Joplin</th>\n",
       "      <th>Not Joplin</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>222</td>\n",
       "      <td>16</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>451</td>\n",
       "      <td>28</td>\n",
       "      <td>479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>702</td>\n",
       "      <td>44</td>\n",
       "      <td>746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>235</td>\n",
       "      <td>92</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5. HU &gt; 0, AP = 0</th>\n",
       "      <td>26</td>\n",
       "      <td>13</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <td>31</td>\n",
       "      <td>4702</td>\n",
       "      <td>4733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <td>358</td>\n",
       "      <td>2701</td>\n",
       "      <td>3059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>2025</td>\n",
       "      <td>7596</td>\n",
       "      <td>9621</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Joplin                               Joplin  Not Joplin  Total\n",
       "ErrorCheck1                                                   \n",
       "1. HU=0                                 222          16    238\n",
       "2. HU=AP                                451          28    479\n",
       "3. HU<AP                                702          44    746\n",
       "4. HU>AP                                235          92    327\n",
       "5. HU > 0, AP = 0                        26          13     39\n",
       "8. HU > 0, Building Count = Missing      31        4702   4733\n",
       "9. HU = 0, Building Count = Missing     358        2701   3059\n",
       "Total                                  2025        7596   9621"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def block_error_check_addresspoints(census_blocks_df, expected_count, estimated_count,building_count, ErrorCheck):\n",
    "    # Create Error Varaible\n",
    "    census_blocks_df[ErrorCheck] = \"0. Not Checked\"\n",
    "\n",
    "    basecondition = (census_blocks_df[ErrorCheck] == \"0. Not Checked\")\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count].isna())\n",
    "                         & basecondition, ErrorCheck] = \"1. HU=0\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count] == census_blocks_df[estimated_count])\n",
    "                         & basecondition, ErrorCheck] = \"2. HU=AP\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count] < census_blocks_df[estimated_count])\n",
    "                         & basecondition, ErrorCheck] = \"3. HU<AP\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count] > census_blocks_df[estimated_count])\n",
    "                         & basecondition, ErrorCheck] = \"4. HU>AP\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count] > 0) & (census_blocks_df[estimated_count] == 0)\n",
    "                         & basecondition, ErrorCheck] = \"5. HU > 0, AP = 0\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count] > 0) & (census_blocks_df[estimated_count].isna()) & \n",
    "                         (census_blocks_df[building_count] > 0)\n",
    "                         , ErrorCheck] = \"6. HU > 0, AP = Missing, But buildings present\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count] > 0) & (census_blocks_df[estimated_count].isna())\n",
    "                         , ErrorCheck] = \"7. HU > 0, AP = Missing\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count] > 0) & (census_blocks_df[building_count].isna())\n",
    "                         , ErrorCheck] = \"8. HU > 0, Building Count = Missing\"\n",
    "    census_blocks_df.loc[(census_blocks_df[expected_count].isna()) & (census_blocks_df[building_count].isna())\n",
    "                         , ErrorCheck] = \"9. HU = 0, Building Count = Missing\"\n",
    "    \n",
    "block_error_check_addresspoints(census_blocks_df_rap1,'apcount','residentialAP1','bldgcount','ErrorCheck1')\n",
    "pd.crosstab(census_blocks_df_rap1['ErrorCheck1'], census_blocks_df_rap1['Joplin'],\n",
    "            margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>238.0</td>\n",
       "      <td>1.239496</td>\n",
       "      <td>2.638044</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>479.0</td>\n",
       "      <td>11.812109</td>\n",
       "      <td>7.719872</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>746.0</td>\n",
       "      <td>19.599196</td>\n",
       "      <td>14.792305</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>127.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>327.0</td>\n",
       "      <td>19.660550</td>\n",
       "      <td>28.819372</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>217.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5. HU &gt; 0, AP = 0</th>\n",
       "      <td>39.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     count       mean        std  min   25%  \\\n",
       "ErrorCheck1                                                                   \n",
       "1. HU=0                              238.0   1.239496   2.638044  0.0   0.0   \n",
       "2. HU=AP                             479.0  11.812109   7.719872  1.0   7.0   \n",
       "3. HU<AP                             746.0  19.599196  14.792305  2.0  10.0   \n",
       "4. HU>AP                             327.0  19.660550  28.819372  1.0   7.0   \n",
       "5. HU > 0, AP = 0                     39.0   0.000000   0.000000  0.0   0.0   \n",
       "8. HU > 0, Building Count = Missing    0.0        NaN        NaN  NaN   NaN   \n",
       "9. HU = 0, Building Count = Missing    0.0        NaN        NaN  NaN   NaN   \n",
       "\n",
       "                                      50%   75%    max  \n",
       "ErrorCheck1                                             \n",
       "1. HU=0                               0.0   1.0   19.0  \n",
       "2. HU=AP                             11.0  16.0   65.0  \n",
       "3. HU<AP                             16.0  26.0  127.0  \n",
       "4. HU>AP                             12.0  19.0  217.0  \n",
       "5. HU > 0, AP = 0                     0.0   0.0    0.0  \n",
       "8. HU > 0, Building Count = Missing   NaN   NaN    NaN  \n",
       "9. HU = 0, Building Count = Missing   NaN   NaN    NaN  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at estimated Address Points by Error\n",
    "census_blocks_df_rap1['residentialAP1'].groupby(census_blocks_df_rap1['ErrorCheck1']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>BLOCKID10</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>PLCNAME10</th>\n",
       "      <th>residentialAP1</th>\n",
       "      <th>apcount</th>\n",
       "      <th>bldgcount</th>\n",
       "      <th>ErrorCheck1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>290970110003000</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>290970110005021</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>290970102001002</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>290970101001063</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>290970102002009</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>290970119003035</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>733</th>\n",
       "      <td>290970110003002</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>290970101001071</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1049</th>\n",
       "      <td>290970102002010</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1500</th>\n",
       "      <td>290970106001016</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1501</th>\n",
       "      <td>290970101001078</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>290970102002032</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2213</th>\n",
       "      <td>290970106004000</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2776</th>\n",
       "      <td>290970110003013</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2844</th>\n",
       "      <td>290970101001075</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2958</th>\n",
       "      <td>290970101001041</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3416</th>\n",
       "      <td>290970110002028</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3541</th>\n",
       "      <td>290970101001040</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3957</th>\n",
       "      <td>290970109003002</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4014</th>\n",
       "      <td>290970104003050</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4021</th>\n",
       "      <td>290970107001036</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4110</th>\n",
       "      <td>290970110002027</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4114</th>\n",
       "      <td>290970110005026</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4176</th>\n",
       "      <td>290970101001060</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4692</th>\n",
       "      <td>290970109003000</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5103</th>\n",
       "      <td>290970114002008</td>\n",
       "      <td>97</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5. HU &gt; 0, AP = 0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            BLOCKID10  COUNTYFP10 PLCNAME10  residentialAP1  apcount  \\\n",
       "51    290970110003000          97    Joplin             0.0      8.0   \n",
       "64    290970110005021          97    Joplin             0.0      2.0   \n",
       "102   290970102001002          97    Joplin             0.0      1.0   \n",
       "124   290970101001063          97    Joplin             0.0    130.0   \n",
       "356   290970102002009          97    Joplin             0.0      1.0   \n",
       "478   290970119003035          97    Joplin             0.0      1.0   \n",
       "733   290970110003002          97    Joplin             0.0     39.0   \n",
       "798   290970101001071          97    Joplin             0.0     13.0   \n",
       "1049  290970102002010          97    Joplin             0.0      3.0   \n",
       "1500  290970106001016          97    Joplin             0.0     36.0   \n",
       "1501  290970101001078          97    Joplin             0.0      1.0   \n",
       "1718  290970102002032          97    Joplin             0.0      1.0   \n",
       "2213  290970106004000          97    Joplin             0.0      3.0   \n",
       "2776  290970110003013          97    Joplin             0.0      1.0   \n",
       "2844  290970101001075          97    Joplin             0.0     30.0   \n",
       "2958  290970101001041          97    Joplin             0.0      1.0   \n",
       "3416  290970110002028          97    Joplin             0.0      2.0   \n",
       "3541  290970101001040          97    Joplin             0.0      3.0   \n",
       "3957  290970109003002          97    Joplin             0.0      1.0   \n",
       "4014  290970104003050          97    Joplin             0.0      1.0   \n",
       "4021  290970107001036          97    Joplin             0.0     67.0   \n",
       "4110  290970110002027          97    Joplin             0.0      5.0   \n",
       "4114  290970110005026          97    Joplin             0.0      1.0   \n",
       "4176  290970101001060          97    Joplin             0.0      2.0   \n",
       "4692  290970109003000          97    Joplin             0.0      1.0   \n",
       "5103  290970114002008          97    Joplin             0.0      6.0   \n",
       "\n",
       "      bldgcount        ErrorCheck1  \n",
       "51          4.0  5. HU > 0, AP = 0  \n",
       "64          1.0  5. HU > 0, AP = 0  \n",
       "102         7.0  5. HU > 0, AP = 0  \n",
       "124         2.0  5. HU > 0, AP = 0  \n",
       "356         5.0  5. HU > 0, AP = 0  \n",
       "478         2.0  5. HU > 0, AP = 0  \n",
       "733         4.0  5. HU > 0, AP = 0  \n",
       "798         9.0  5. HU > 0, AP = 0  \n",
       "1049        2.0  5. HU > 0, AP = 0  \n",
       "1500        3.0  5. HU > 0, AP = 0  \n",
       "1501        5.0  5. HU > 0, AP = 0  \n",
       "1718        2.0  5. HU > 0, AP = 0  \n",
       "2213        7.0  5. HU > 0, AP = 0  \n",
       "2776        1.0  5. HU > 0, AP = 0  \n",
       "2844        8.0  5. HU > 0, AP = 0  \n",
       "2958        1.0  5. HU > 0, AP = 0  \n",
       "3416        3.0  5. HU > 0, AP = 0  \n",
       "3541        2.0  5. HU > 0, AP = 0  \n",
       "3957        1.0  5. HU > 0, AP = 0  \n",
       "4014        1.0  5. HU > 0, AP = 0  \n",
       "4021        3.0  5. HU > 0, AP = 0  \n",
       "4110        5.0  5. HU > 0, AP = 0  \n",
       "4114        2.0  5. HU > 0, AP = 0  \n",
       "4176        7.0  5. HU > 0, AP = 0  \n",
       "4692       27.0  5. HU > 0, AP = 0  \n",
       "5103        2.0  5. HU > 0, AP = 0  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For the 29 blocks with 0 address points and HU greater than 0 look at adding address points\n",
    "displaycols = ['BLOCKID10','COUNTYFP10','PLCNAME10','residentialAP1','apcount','bldgcount','ErrorCheck1']\n",
    "condition = (census_blocks_df_rap1['ErrorCheck1'] == \"5. HU > 0, AP = 0\") & (census_blocks_df_rap1['Joplin']==\"Joplin\")\n",
    "census_blocks_df_rap1[displaycols].loc[condition]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "census_blocks_df_rap1['DiffCount1'] = census_blocks_df_rap1['apcount'] - census_blocks_df_rap1['residentialAP1']\n",
    "census_blocks_df_rap1 = census_blocks_df_rap1.rename(index=str, columns={\n",
    "    \"residentialAP1\": \"residentialAP1_sum\", \n",
    "    \"bldgcount\": \"bldgcount1_sum\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count        28152\n",
       "unique       28152\n",
       "top       B0012554\n",
       "freq             1\n",
       "Name: bldg_id, dtype: object"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge Block level data with building level data\n",
    "keepcolumns = ['BLOCKID10','residentialAP1_sum','bldgcount1_sum','DiffCount1','ErrorCheck1']\n",
    "\n",
    "building_gdf_round2 = pd.merge(building_gdf, census_blocks_df_rap1[keepcolumns], \n",
    "                                  left_on='BLOCKID10', right_on='BLOCKID10', how='left')\n",
    "# Convert Pandas Data Frame from Merge to Geodataframe\n",
    "building_gdf_round2 = gpd.GeoDataFrame(building_gdf_round2, crs=building_gdf.crs)\n",
    "# Check Merge to make sure all buildings are in the dataset\n",
    "building_gdf_round2['bldg_id'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distribute Missing Address Points to Buildings Based on Area\n",
    "\\begin{equation*}\n",
    "\\frac{Area_k}{\\left( \\sum_{k=1}^n Area_k \\right)}*DiffCount_i\n",
    "\\end{equation*}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>669</td>\n",
       "      <td>185</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>813</td>\n",
       "      <td>5485</td>\n",
       "      <td>37</td>\n",
       "      <td>33</td>\n",
       "      <td>6368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>3104</td>\n",
       "      <td>6493</td>\n",
       "      <td>2753</td>\n",
       "      <td>874</td>\n",
       "      <td>13224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>1772</td>\n",
       "      <td>5156</td>\n",
       "      <td>158</td>\n",
       "      <td>319</td>\n",
       "      <td>7405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5. HU &gt; 0, AP = 0</th>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>6614</td>\n",
       "      <td>17319</td>\n",
       "      <td>2973</td>\n",
       "      <td>1246</td>\n",
       "      <td>28152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1        0      1     2     3  Total\n",
       "ErrorCheck1                                      \n",
       "1. HU=0             669    185    25    20    899\n",
       "2. HU=AP            813   5485    37    33   6368\n",
       "3. HU<AP           3104   6493  2753   874  13224\n",
       "4. HU>AP           1772   5156   158   319   7405\n",
       "5. HU > 0, AP = 0   256      0     0     0    256\n",
       "Total              6614  17319  2973  1246  28152"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For Error Check = 5. HU > 0, AP = 0 - Make Each Building that is in the block a residential address point\n",
    "pd.crosstab(building_gdf_round2['ErrorCheck1'], building_gdf_round2['residentialAP1'],\n",
    "            margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>residentialAP1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>669</td>\n",
       "      <td>185</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>813</td>\n",
       "      <td>5485</td>\n",
       "      <td>37</td>\n",
       "      <td>33</td>\n",
       "      <td>6368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>3104</td>\n",
       "      <td>6493</td>\n",
       "      <td>2753</td>\n",
       "      <td>874</td>\n",
       "      <td>13224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>1772</td>\n",
       "      <td>5156</td>\n",
       "      <td>158</td>\n",
       "      <td>319</td>\n",
       "      <td>7405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5. HU &gt; 0, AP = 0</th>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>6358</td>\n",
       "      <td>17575</td>\n",
       "      <td>2973</td>\n",
       "      <td>1246</td>\n",
       "      <td>28152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "residentialAP1        0      1     2     3  Total\n",
       "ErrorCheck1                                      \n",
       "1. HU=0             669    185    25    20    899\n",
       "2. HU=AP            813   5485    37    33   6368\n",
       "3. HU<AP           3104   6493  2753   874  13224\n",
       "4. HU>AP           1772   5156   158   319   7405\n",
       "5. HU > 0, AP = 0     0    256     0     0    256\n",
       "Total              6358  17575  2973  1246  28152"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For Error Code 5 Make each Building a Residential Building\n",
    "building_gdf_round2.loc[(building_gdf_round2['ErrorCheck1'] == \"5. HU > 0, AP = 0\"),'residentialAP1']=1\n",
    "pd.crosstab(building_gdf_round2['ErrorCheck1'], building_gdf_round2['residentialAP1'],\n",
    "            margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>BLOCKID10</th>\n",
       "      <th>Res_Area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.815200e+04</td>\n",
       "      <td>28152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.910310e+14</td>\n",
       "      <td>169.613007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.597421e+11</td>\n",
       "      <td>316.466313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>68.111269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>145.945821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.909701e+14</td>\n",
       "      <td>218.512466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.914502e+14</td>\n",
       "      <td>20216.545735</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          BLOCKID10      Res_Area\n",
       "count  2.815200e+04  28152.000000\n",
       "mean   2.910310e+14    169.613007\n",
       "std    1.597421e+11    316.466313\n",
       "min    2.909701e+14      0.000000\n",
       "25%    2.909701e+14     68.111269\n",
       "50%    2.909701e+14    145.945821\n",
       "75%    2.909701e+14    218.512466\n",
       "max    2.914502e+14  20216.545735"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calcuate sum of Residential Area By Block\n",
    "building_gdf_round2['Res_Area'] = 0\n",
    "building_gdf_round2.loc[(building_gdf_round2['residentialAP1']>=1), 'Res_Area'] = building_gdf_round2['gsq_meter']\n",
    "building_gdf_round2_area = building_gdf_round2[['BLOCKID10','Res_Area']]\n",
    "building_gdf_round2_area.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>Sum_Res_Area</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>290970101001000</th>\n",
       "      <td>581.023359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001001</th>\n",
       "      <td>228.126477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001002</th>\n",
       "      <td>755.359780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001003</th>\n",
       "      <td>3404.343351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001006</th>\n",
       "      <td>789.038971</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Sum_Res_Area\n",
       "BLOCKID10                    \n",
       "290970101001000    581.023359\n",
       "290970101001001    228.126477\n",
       "290970101001002    755.359780\n",
       "290970101001003   3404.343351\n",
       "290970101001006    789.038971"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf_round2_area_sum = building_gdf_round2_area.groupby(['BLOCKID10']).sum()\n",
    "building_gdf_round2_area_sum = building_gdf_round2_area_sum.rename(columns={\"Res_Area\": \"Sum_Res_Area\"})\n",
    "building_gdf_round2_area_sum.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count        28152\n",
       "unique       28152\n",
       "top       B0012554\n",
       "freq             1\n",
       "Name: bldg_id, dtype: object"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf_round2_v2 = pd.merge(building_gdf_round2, building_gdf_round2_area_sum, \n",
    "                                  left_on='BLOCKID10', right_on='BLOCKID10', how='outer')\n",
    "# Convert Pandas Data Frame from Merge to Geodataframe\n",
    "building_gdf_round2_v2 = gpd.GeoDataFrame(building_gdf_round2_v2, crs=building_gdf.crs)\n",
    "building_gdf_round2_v2['bldg_id'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    27253.000000\n",
       "mean        -0.023557\n",
       "std          1.579951\n",
       "min        -13.077827\n",
       "25%         -0.121259\n",
       "50%          0.000000\n",
       "75%         -0.000000\n",
       "max        112.000000\n",
       "Name: residentialAP2, dtype: float64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate Number of Address Points Each Building Should Have based on Housing Unit Count Difference\n",
    "building_gdf_round2_v2['residentialAP2'] = (building_gdf_round2_v2['Res_Area'] / building_gdf_round2_v2['Sum_Res_Area']) * building_gdf_round2_v2['DiffCount1'] \n",
    "building_gdf_round2_v2['residentialAP2'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Estimate new Housing Unit Count in Building\n",
    "Using the distributed difference in address points, round the value and add to the intial estimate.\n",
    "\n",
    "For blocks where the housing unit and address points are equal (Error 2) or for blocks where the number of address points is greater than the number of Housing Units (Error 3) use the estimate from Round 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>ErrorCheck1</th>\n",
       "      <th>1. HU=0</th>\n",
       "      <th>2. HU=AP</th>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <th>5. HU &gt; 0, AP = 0</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>residentialAP2v2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>899</td>\n",
       "      <td>813</td>\n",
       "      <td>3104</td>\n",
       "      <td>1772</td>\n",
       "      <td>0</td>\n",
       "      <td>6588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>0</td>\n",
       "      <td>5485</td>\n",
       "      <td>6493</td>\n",
       "      <td>4166</td>\n",
       "      <td>187</td>\n",
       "      <td>16331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>2753</td>\n",
       "      <td>829</td>\n",
       "      <td>38</td>\n",
       "      <td>3657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>874</td>\n",
       "      <td>238</td>\n",
       "      <td>9</td>\n",
       "      <td>1154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>115</td>\n",
       "      <td>7</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>1</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>899</td>\n",
       "      <td>6368</td>\n",
       "      <td>13224</td>\n",
       "      <td>7405</td>\n",
       "      <td>256</td>\n",
       "      <td>28152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ErrorCheck1       1. HU=0  2. HU=AP  3. HU<AP  4. HU>AP  5. HU > 0, AP = 0  \\\n",
       "residentialAP2v2                                                             \n",
       "0.0                   899       813      3104      1772                  0   \n",
       "1.0                     0      5485      6493      4166                187   \n",
       "2.0                     0        37      2753       829                 38   \n",
       "3.0                     0        33       874       238                  9   \n",
       "4.0                     0         0         0       115                  7   \n",
       "5.0                     0         0         0        81                  1   \n",
       "6.0                     0         0         0        42                  1   \n",
       "7.0                     0         0         0        21                  1   \n",
       "8.0                     0         0         0        28                  1   \n",
       "9.0                     0         0         0        21                  0   \n",
       "10.0                    0         0         0        16                  3   \n",
       "11.0                    0         0         0        20                  0   \n",
       "12.0                    0         0         0        13                  0   \n",
       "13.0                    0         0         0         8                  0   \n",
       "14.0                    0         0         0         5                  0   \n",
       "15.0                    0         0         0         3                  1   \n",
       "16.0                    0         0         0         4                  0   \n",
       "17.0                    0         0         0         3                  0   \n",
       "18.0                    0         0         0         1                  0   \n",
       "19.0                    0         0         0         1                  0   \n",
       "20.0                    0         0         0         1                  0   \n",
       "21.0                    0         0         0         2                  0   \n",
       "22.0                    0         0         0         1                  1   \n",
       "23.0                    0         0         0         1                  1   \n",
       "25.0                    0         0         0         1                  0   \n",
       "28.0                    0         0         0         1                  0   \n",
       "30.0                    0         0         0         1                  0   \n",
       "31.0                    0         0         0         1                  0   \n",
       "32.0                    0         0         0         0                  1   \n",
       "33.0                    0         0         0         1                  1   \n",
       "35.0                    0         0         0         1                  0   \n",
       "36.0                    0         0         0         1                  0   \n",
       "37.0                    0         0         0         2                  0   \n",
       "38.0                    0         0         0         2                  0   \n",
       "41.0                    0         0         0         1                  0   \n",
       "66.0                    0         0         0         0                  2   \n",
       "92.0                    0         0         0         1                  0   \n",
       "113.0                   0         0         0         0                  1   \n",
       "Total                 899      6368     13224      7405                256   \n",
       "\n",
       "ErrorCheck1       Total  \n",
       "residentialAP2v2         \n",
       "0.0                6588  \n",
       "1.0               16331  \n",
       "2.0                3657  \n",
       "3.0                1154  \n",
       "4.0                 122  \n",
       "5.0                  82  \n",
       "6.0                  43  \n",
       "7.0                  22  \n",
       "8.0                  29  \n",
       "9.0                  21  \n",
       "10.0                 19  \n",
       "11.0                 20  \n",
       "12.0                 13  \n",
       "13.0                  8  \n",
       "14.0                  5  \n",
       "15.0                  4  \n",
       "16.0                  4  \n",
       "17.0                  3  \n",
       "18.0                  1  \n",
       "19.0                  1  \n",
       "20.0                  1  \n",
       "21.0                  2  \n",
       "22.0                  2  \n",
       "23.0                  2  \n",
       "25.0                  1  \n",
       "28.0                  1  \n",
       "30.0                  1  \n",
       "31.0                  1  \n",
       "32.0                  1  \n",
       "33.0                  2  \n",
       "35.0                  1  \n",
       "36.0                  1  \n",
       "37.0                  2  \n",
       "38.0                  2  \n",
       "41.0                  1  \n",
       "66.0                  2  \n",
       "92.0                  1  \n",
       "113.0                 1  \n",
       "Total             28152  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf_round2_v2['residentialAP2v2'] = round(building_gdf_round2_v2['residentialAP2'],0) + building_gdf_round2_v2['residentialAP1']\n",
    "# If Round 1 had a match between Address Points and Housing Units use Round 1\n",
    "building_gdf_round2_v2.loc[(building_gdf_round2_v2['ErrorCheck1'] == \"2. HU=AP\"),'residentialAP2v2'] = building_gdf_round2_v2['residentialAP1']\n",
    "# If Round 1 had a more Address Points than Housing Units Use Round 1\n",
    "building_gdf_round2_v2.loc[(building_gdf_round2_v2['ErrorCheck1'] == \"3. HU<AP\"),'residentialAP2v2'] = building_gdf_round2_v2['residentialAP1']\n",
    "\n",
    "# If Estiamted number of Census Housing Units is 0 make AP 0\n",
    "building_gdf_round2_v2.loc[(building_gdf_round2_v2['ErrorCheck1'] == \"1. HU=0\"),'residentialAP2v2'] = 0\n",
    "\n",
    "pd.crosstab(building_gdf_round2_v2['residentialAP2v2'], building_gdf_round2_v2['ErrorCheck1'],\n",
    "            margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sum Residential Addresspoints (second attempt) by blockid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\nathanael99\\AppData\\Local\\Continuum\\anaconda3\\envs\\pyincore20190618\\lib\\site-packages\\ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  after removing the cwd from sys.path.\n"
     ]
    },
    {
     "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>residentialAP2v2</th>\n",
       "      <th>bldgcountv2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>290970101001000</th>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001001</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001002</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001003</th>\n",
       "      <td>29.0</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001006</th>\n",
       "      <td>5.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 residentialAP2v2  bldgcountv2\n",
       "BLOCKID10                                     \n",
       "290970101001000               5.0            5\n",
       "290970101001001               2.0            2\n",
       "290970101001002               3.0            4\n",
       "290970101001003              29.0           33\n",
       "290970101001006               5.0           10"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sum Buildings over the column BLOCKID.\n",
    "# https://www.geeksforgeeks.org/python-pandas-dataframe-sum/\n",
    "block_rap2_gdf = building_gdf_round2_v2[['BLOCKID10','residentialAP2v2']]\n",
    "block_rap2_gdf['bldgcountv2'] = 1\n",
    "block_rap2_gdf_sum = block_rap2_gdf.groupby(['BLOCKID10']).sum()\n",
    "block_rap2_gdf_sum.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1829.000000\n",
       "mean       16.814106\n",
       "std        24.179476\n",
       "min         0.000000\n",
       "25%         6.000000\n",
       "50%        12.000000\n",
       "75%        20.000000\n",
       "max       334.000000\n",
       "Name: residentialAP2v2, dtype: float64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "block_rap2_gdf_sum['residentialAP2v2'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Error Check Round 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>Unnamed: 0</th>\n",
       "      <th>STATEFP10</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>TRACTCE10</th>\n",
       "      <th>BLOCKCE</th>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th>PARTFLG</th>\n",
       "      <th>HOUSING10</th>\n",
       "      <th>POP10</th>\n",
       "      <th>geometry</th>\n",
       "      <th>...</th>\n",
       "      <th>popdiff</th>\n",
       "      <th>PLCGEOID10</th>\n",
       "      <th>PLCNAME10</th>\n",
       "      <th>PUMGEOID10</th>\n",
       "      <th>PUMNAME10</th>\n",
       "      <th>residentialAP1_sum</th>\n",
       "      <th>bldgcount1_sum</th>\n",
       "      <th>Joplin</th>\n",
       "      <th>ErrorCheck1</th>\n",
       "      <th>DiffCount1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1047</td>\n",
       "      <td>290970121001047</td>\n",
       "      <td>N</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>POLYGON ((-94.13775 37.32550000000001, -94.138...</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not Joplin</td>\n",
       "      <td>8. HU &gt; 0, Building Count = Missing</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1050</td>\n",
       "      <td>290970121001050</td>\n",
       "      <td>N</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>POLYGON ((-94.137637 37.328675, -94.119315 37....</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not Joplin</td>\n",
       "      <td>8. HU &gt; 0, Building Count = Missing</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1094</td>\n",
       "      <td>290970121001094</td>\n",
       "      <td>N</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>POLYGON ((-94.214761 37.293836, -94.230751 37....</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not Joplin</td>\n",
       "      <td>8. HU &gt; 0, Building Count = Missing</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1093</td>\n",
       "      <td>290970121001093</td>\n",
       "      <td>N</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>POLYGON ((-94.197294 37.27723599999999, -94.19...</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not Joplin</td>\n",
       "      <td>8. HU &gt; 0, Building Count = Missing</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>97</td>\n",
       "      <td>12100</td>\n",
       "      <td>1130</td>\n",
       "      <td>290970121001130</td>\n",
       "      <td>N</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>POLYGON ((-94.151792 37.276275, -94.1519139999...</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2902800</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not Joplin</td>\n",
       "      <td>8. HU &gt; 0, Building Count = Missing</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  STATEFP10  COUNTYFP10  TRACTCE10  BLOCKCE        BLOCKID10  \\\n",
       "0           0         29          97      12100     1047  290970121001047   \n",
       "1           1         29          97      12100     1050  290970121001050   \n",
       "2           2         29          97      12100     1094  290970121001094   \n",
       "3           3         29          97      12100     1093  290970121001093   \n",
       "4           4         29          97      12100     1130  290970121001130   \n",
       "\n",
       "  PARTFLG  HOUSING10  POP10  \\\n",
       "0       N          2      4   \n",
       "1       N          3      7   \n",
       "2       N          4     13   \n",
       "3       N          5      5   \n",
       "4       N          4      9   \n",
       "\n",
       "                                            geometry  ...  popdiff PLCGEOID10  \\\n",
       "0  POLYGON ((-94.13775 37.32550000000001, -94.138...  ...      0.0        NaN   \n",
       "1  POLYGON ((-94.137637 37.328675, -94.119315 37....  ...      0.0        NaN   \n",
       "2  POLYGON ((-94.214761 37.293836, -94.230751 37....  ...      0.0        NaN   \n",
       "3  POLYGON ((-94.197294 37.27723599999999, -94.19...  ...      0.0        NaN   \n",
       "4  POLYGON ((-94.151792 37.276275, -94.1519139999...  ...      0.0        NaN   \n",
       "\n",
       "  PLCNAME10  PUMGEOID10                      PUMNAME10  residentialAP1_sum  \\\n",
       "0       NaN     2902800  Jasper & Newton Counties PUMA                 NaN   \n",
       "1       NaN     2902800  Jasper & Newton Counties PUMA                 NaN   \n",
       "2       NaN     2902800  Jasper & Newton Counties PUMA                 NaN   \n",
       "3       NaN     2902800  Jasper & Newton Counties PUMA                 NaN   \n",
       "4       NaN     2902800  Jasper & Newton Counties PUMA                 NaN   \n",
       "\n",
       "   bldgcount1_sum      Joplin                          ErrorCheck1 DiffCount1  \n",
       "0             NaN  Not Joplin  8. HU > 0, Building Count = Missing        NaN  \n",
       "1             NaN  Not Joplin  8. HU > 0, Building Count = Missing        NaN  \n",
       "2             NaN  Not Joplin  8. HU > 0, Building Count = Missing        NaN  \n",
       "3             NaN  Not Joplin  8. HU > 0, Building Count = Missing        NaN  \n",
       "4             NaN  Not Joplin  8. HU > 0, Building Count = Missing        NaN  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_blocks_df_rap1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9.621000e+03\n",
       "mean     2.911818e+14\n",
       "std      2.383822e+11\n",
       "min      2.909701e+14\n",
       "25%      2.909701e+14\n",
       "50%      2.909701e+14\n",
       "75%      2.914502e+14\n",
       "max      2.914502e+14\n",
       "Name: BLOCKID10, dtype: float64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_blocks_df_rap1['BLOCKID10'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9.621000e+03\n",
       "mean     2.911818e+14\n",
       "std      2.383822e+11\n",
       "min      2.909701e+14\n",
       "25%      2.909701e+14\n",
       "50%      2.909701e+14\n",
       "75%      2.914502e+14\n",
       "max      2.914502e+14\n",
       "Name: BLOCKID10, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge Sum of Residential Address Points with Census Counts\n",
    "census_blocks_df_rap2 = pd.merge(census_blocks_df_rap1, block_rap2_gdf_sum,\n",
    "                                  left_on='BLOCKID10', right_on='BLOCKID10', how='left')\n",
    "census_blocks_df_rap2['BLOCKID10'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Error Check 2 - Are there Blocks in Joplin that have Housing Units by the Estimated Number of Housing Units is 0 or Missing?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Housing Unit Count')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare Bldg Count to Housing 10\n",
    "x = census_blocks_df_rap2['residentialAP2v2']\n",
    "y = census_blocks_df_rap2['apcount']\n",
    "plt.scatter(x, y)\n",
    "plt.xlabel(\"Residential Address Count Round 2\")\n",
    "plt.ylabel(\"Housing Unit Count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Error Check Options - Round 2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>ErrorCheck2</th>\n",
       "      <th>1. HU=0</th>\n",
       "      <th>2. HU=AP</th>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>238</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>746</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>0</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>232</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5. HU &gt; 0, AP = 0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4733</td>\n",
       "      <td>0</td>\n",
       "      <td>4733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3059</td>\n",
       "      <td>3059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>238</td>\n",
       "      <td>545</td>\n",
       "      <td>814</td>\n",
       "      <td>232</td>\n",
       "      <td>4733</td>\n",
       "      <td>3059</td>\n",
       "      <td>9621</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ErrorCheck2                          1. HU=0  2. HU=AP  3. HU<AP  4. HU>AP  \\\n",
       "ErrorCheck1                                                                  \n",
       "1. HU=0                                  238         0         0         0   \n",
       "2. HU=AP                                   0       479         0         0   \n",
       "3. HU<AP                                   0         0       746         0   \n",
       "4. HU>AP                                   0        66        29       232   \n",
       "5. HU > 0, AP = 0                          0         0        39         0   \n",
       "8. HU > 0, Building Count = Missing        0         0         0         0   \n",
       "9. HU = 0, Building Count = Missing        0         0         0         0   \n",
       "Total                                    238       545       814       232   \n",
       "\n",
       "ErrorCheck2                          8. HU > 0, Building Count = Missing  \\\n",
       "ErrorCheck1                                                                \n",
       "1. HU=0                                                                0   \n",
       "2. HU=AP                                                               0   \n",
       "3. HU<AP                                                               0   \n",
       "4. HU>AP                                                               0   \n",
       "5. HU > 0, AP = 0                                                      0   \n",
       "8. HU > 0, Building Count = Missing                                 4733   \n",
       "9. HU = 0, Building Count = Missing                                    0   \n",
       "Total                                                               4733   \n",
       "\n",
       "ErrorCheck2                          9. HU = 0, Building Count = Missing  \\\n",
       "ErrorCheck1                                                                \n",
       "1. HU=0                                                                0   \n",
       "2. HU=AP                                                               0   \n",
       "3. HU<AP                                                               0   \n",
       "4. HU>AP                                                               0   \n",
       "5. HU > 0, AP = 0                                                      0   \n",
       "8. HU > 0, Building Count = Missing                                    0   \n",
       "9. HU = 0, Building Count = Missing                                 3059   \n",
       "Total                                                               3059   \n",
       "\n",
       "ErrorCheck2                          Total  \n",
       "ErrorCheck1                                 \n",
       "1. HU=0                                238  \n",
       "2. HU=AP                               479  \n",
       "3. HU<AP                               746  \n",
       "4. HU>AP                               327  \n",
       "5. HU > 0, AP = 0                       39  \n",
       "8. HU > 0, Building Count = Missing   4733  \n",
       "9. HU = 0, Building Count = Missing   3059  \n",
       "Total                                 9621  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "block_error_check_addresspoints(census_blocks_df_rap2,'apcount','residentialAP2v2','bldgcountv2','ErrorCheck2')\n",
    "pd.crosstab(census_blocks_df_rap2['ErrorCheck1'], census_blocks_df_rap2['ErrorCheck2'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>Joplin</th>\n",
       "      <th>Joplin</th>\n",
       "      <th>Not Joplin</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>222</td>\n",
       "      <td>16</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>485</td>\n",
       "      <td>60</td>\n",
       "      <td>545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>746</td>\n",
       "      <td>68</td>\n",
       "      <td>814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>183</td>\n",
       "      <td>49</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <td>31</td>\n",
       "      <td>4702</td>\n",
       "      <td>4733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <td>358</td>\n",
       "      <td>2701</td>\n",
       "      <td>3059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>2025</td>\n",
       "      <td>7596</td>\n",
       "      <td>9621</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Joplin                               Joplin  Not Joplin  Total\n",
       "ErrorCheck2                                                   \n",
       "1. HU=0                                 222          16    238\n",
       "2. HU=AP                                485          60    545\n",
       "3. HU<AP                                746          68    814\n",
       "4. HU>AP                                183          49    232\n",
       "8. HU > 0, Building Count = Missing      31        4702   4733\n",
       "9. HU = 0, Building Count = Missing     358        2701   3059\n",
       "Total                                  2025        7596   9621"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(census_blocks_df_rap2['ErrorCheck2'], census_blocks_df_rap2['Joplin'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Second Round has worked\n",
    "79 blocks moved from too few AP to the same number of AP and HU, and 32 have moved from more AP than HU.\n",
    "There are still 249 blocks with too few AP.\n",
    "54 blocks with missing AP now have more AP than HU."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>DiffCount1</th>\n",
       "      <th>DiffCount2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1591.000000</td>\n",
       "      <td>1591.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.403520</td>\n",
       "      <td>-2.945946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>16.947996</td>\n",
       "      <td>6.433176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-92.000000</td>\n",
       "      <td>-92.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-4.000000</td>\n",
       "      <td>-4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>261.000000</td>\n",
       "      <td>47.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DiffCount1   DiffCount2\n",
       "count  1591.000000  1591.000000\n",
       "mean     -0.403520    -2.945946\n",
       "std      16.947996     6.433176\n",
       "min     -92.000000   -92.000000\n",
       "25%      -4.000000    -4.000000\n",
       "50%       0.000000    -1.000000\n",
       "75%       0.000000     0.000000\n",
       "max     261.000000    47.000000"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_blocks_df_rap2['DiffCount2'] = census_blocks_df_rap2['apcount'] - census_blocks_df_rap2['residentialAP2v2']\n",
    "census_blocks_df_rap2[['DiffCount1','DiffCount2']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>545.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>814.0</td>\n",
       "      <td>-6.461916</td>\n",
       "      <td>6.984988</td>\n",
       "      <td>-92.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>-1.25</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>232.0</td>\n",
       "      <td>2.469828</td>\n",
       "      <td>4.433144</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     count      mean       std   min  25%  \\\n",
       "ErrorCheck2                                                                 \n",
       "1. HU=0                                0.0       NaN       NaN   NaN  NaN   \n",
       "2. HU=AP                             545.0  0.000000  0.000000   0.0  0.0   \n",
       "3. HU<AP                             814.0 -6.461916  6.984988 -92.0 -9.0   \n",
       "4. HU>AP                             232.0  2.469828  4.433144   1.0  1.0   \n",
       "8. HU > 0, Building Count = Missing    0.0       NaN       NaN   NaN  NaN   \n",
       "9. HU = 0, Building Count = Missing    0.0       NaN       NaN   NaN  NaN   \n",
       "\n",
       "                                     50%   75%   max  \n",
       "ErrorCheck2                                           \n",
       "1. HU=0                              NaN   NaN   NaN  \n",
       "2. HU=AP                             0.0  0.00   0.0  \n",
       "3. HU<AP                            -4.0 -1.25  -1.0  \n",
       "4. HU>AP                             1.0  2.00  47.0  \n",
       "8. HU > 0, Building Count = Missing  NaN   NaN   NaN  \n",
       "9. HU = 0, Building Count = Missing  NaN   NaN   NaN  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compare difference in county by Error Type\n",
    "census_blocks_df_rap2['DiffCount2'].groupby(census_blocks_df_rap2['ErrorCheck2']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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>BLOCKID10</th>\n",
       "      <th>apcount</th>\n",
       "      <th>bldgcount1_sum</th>\n",
       "      <th>bldgcountv2</th>\n",
       "      <th>DiffCount1</th>\n",
       "      <th>DiffCount2</th>\n",
       "      <th>residentialAP1_sum</th>\n",
       "      <th>residentialAP2v2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>290970108004008</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>290970108001010</td>\n",
       "      <td>14.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>290970108004020</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>290970110002024</td>\n",
       "      <td>43.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>290970102001006</td>\n",
       "      <td>66.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>290970105001008</td>\n",
       "      <td>212.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>183.0</td>\n",
       "      <td>189.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>290970105003007</td>\n",
       "      <td>25.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>290970104001049</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>290970109002055</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>290970108005013</td>\n",
       "      <td>16.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>290970108005026</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>290970108003032</td>\n",
       "      <td>19.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>290970108003044</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>290970107001030</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>290970106005018</td>\n",
       "      <td>25.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294</th>\n",
       "      <td>290970107003014</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>290970109002001</td>\n",
       "      <td>16.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>631</th>\n",
       "      <td>290970111001046</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>642</th>\n",
       "      <td>290970110004031</td>\n",
       "      <td>21.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>290970110001023</td>\n",
       "      <td>38.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>290970108004002</td>\n",
       "      <td>17.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>290970108002022</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>814</th>\n",
       "      <td>290970106005008</td>\n",
       "      <td>17.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>839</th>\n",
       "      <td>290970102004010</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>842</th>\n",
       "      <td>290970103002015</td>\n",
       "      <td>306.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>259.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>845</th>\n",
       "      <td>290970101003021</td>\n",
       "      <td>14.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>908</th>\n",
       "      <td>290970119001013</td>\n",
       "      <td>24.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>918</th>\n",
       "      <td>290970109002039</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>919</th>\n",
       "      <td>290970109002038</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>939</th>\n",
       "      <td>290970109004027</td>\n",
       "      <td>50.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4985</th>\n",
       "      <td>290970107002003</td>\n",
       "      <td>17.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5078</th>\n",
       "      <td>290970102001025</td>\n",
       "      <td>115.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5114</th>\n",
       "      <td>290970106002015</td>\n",
       "      <td>191.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5115</th>\n",
       "      <td>290970106003003</td>\n",
       "      <td>138.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>136.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5340</th>\n",
       "      <td>290970109004018</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5357</th>\n",
       "      <td>290970102001032</td>\n",
       "      <td>22.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5686</th>\n",
       "      <td>291450206011000</td>\n",
       "      <td>40.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5781</th>\n",
       "      <td>291450205023010</td>\n",
       "      <td>78.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5785</th>\n",
       "      <td>291450205012043</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5804</th>\n",
       "      <td>291450205022005</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6399</th>\n",
       "      <td>291450205023000</td>\n",
       "      <td>267.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>234.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6511</th>\n",
       "      <td>291450205023027</td>\n",
       "      <td>44.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6744</th>\n",
       "      <td>291450205021057</td>\n",
       "      <td>19.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6841</th>\n",
       "      <td>291450205021045</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6912</th>\n",
       "      <td>291450205012033</td>\n",
       "      <td>31.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7231</th>\n",
       "      <td>291450206011012</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7348</th>\n",
       "      <td>291450205021052</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7349</th>\n",
       "      <td>291450205021058</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7851</th>\n",
       "      <td>291450205013022</td>\n",
       "      <td>29.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7902</th>\n",
       "      <td>291450205021180</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7929</th>\n",
       "      <td>291450205023028</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8022</th>\n",
       "      <td>291450206011003</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>291450205012029</td>\n",
       "      <td>40.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8415</th>\n",
       "      <td>291450205021181</td>\n",
       "      <td>22.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8539</th>\n",
       "      <td>291450206011006</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8551</th>\n",
       "      <td>291450205012024</td>\n",
       "      <td>101.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9076</th>\n",
       "      <td>291450204001037</td>\n",
       "      <td>44.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9080</th>\n",
       "      <td>291450205022179</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9494</th>\n",
       "      <td>291450206011005</td>\n",
       "      <td>39.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9511</th>\n",
       "      <td>291450205012035</td>\n",
       "      <td>55.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>183 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            BLOCKID10  apcount  bldgcount1_sum  bldgcountv2  DiffCount1  \\\n",
       "32    290970108004008      5.0             5.0          5.0         1.0   \n",
       "33    290970108001010     14.0            16.0         16.0         1.0   \n",
       "35    290970108004020     15.0            16.0         16.0         1.0   \n",
       "40    290970110002024     43.0            18.0         18.0         4.0   \n",
       "76    290970102001006     66.0            70.0         70.0         4.0   \n",
       "155   290970105001008    212.0            95.0         95.0        29.0   \n",
       "160   290970105003007     25.0            31.0         31.0         2.0   \n",
       "175   290970104001049     10.0            15.0         15.0         1.0   \n",
       "239   290970109002055     16.0            16.0         16.0         1.0   \n",
       "263   290970108005013     16.0            17.0         17.0         1.0   \n",
       "264   290970108005026     13.0            14.0         14.0         1.0   \n",
       "270   290970108003032     19.0            24.0         24.0         2.0   \n",
       "272   290970108003044     13.0            12.0         12.0         1.0   \n",
       "275   290970107001030     15.0            16.0         16.0         1.0   \n",
       "278   290970106005018     25.0            26.0         26.0         1.0   \n",
       "294   290970107003014     25.0            25.0         25.0         1.0   \n",
       "560   290970109002001     16.0            14.0         14.0         2.0   \n",
       "631   290970111001046     13.0            16.0         16.0         1.0   \n",
       "642   290970110004031     21.0            21.0         21.0         3.0   \n",
       "728   290970110001023     38.0            26.0         26.0         1.0   \n",
       "752   290970108004002     17.0            21.0         21.0         2.0   \n",
       "754   290970108002022     15.0            11.0         11.0         4.0   \n",
       "814   290970106005008     17.0            22.0         22.0         1.0   \n",
       "839   290970102004010     11.0            12.0         12.0         2.0   \n",
       "842   290970103002015    306.0           218.0        218.0        94.0   \n",
       "845   290970101003021     14.0            20.0         20.0         1.0   \n",
       "908   290970119001013     24.0            23.0         23.0         1.0   \n",
       "918   290970109002039      8.0             8.0          8.0         2.0   \n",
       "919   290970109002038     10.0            12.0         12.0         1.0   \n",
       "939   290970109004027     50.0            18.0         18.0         2.0   \n",
       "...               ...      ...             ...          ...         ...   \n",
       "4985  290970107002003     17.0            18.0         18.0         2.0   \n",
       "5078  290970102001025    115.0           114.0        114.0         4.0   \n",
       "5114  290970106002015    191.0            16.0         16.0       146.0   \n",
       "5115  290970106003003    138.0            19.0         19.0        93.0   \n",
       "5340  290970109004018     12.0            15.0         15.0         1.0   \n",
       "5357  290970102001032     22.0             9.0          9.0        13.0   \n",
       "5686  291450206011000     40.0            37.0         37.0         3.0   \n",
       "5781  291450205023010     78.0            76.0         76.0         3.0   \n",
       "5785  291450205012043     15.0            14.0         14.0         1.0   \n",
       "5804  291450205022005      6.0             5.0          5.0         1.0   \n",
       "6399  291450205023000    267.0           281.0        281.0        50.0   \n",
       "6511  291450205023027     44.0            41.0         41.0         3.0   \n",
       "6744  291450205021057     19.0            14.0         14.0         5.0   \n",
       "6841  291450205021045     19.0            18.0         18.0         1.0   \n",
       "6912  291450205012033     31.0            26.0         26.0         5.0   \n",
       "7231  291450206011012     11.0             9.0          9.0         2.0   \n",
       "7348  291450205021052     14.0            11.0         11.0         3.0   \n",
       "7349  291450205021058      8.0             7.0          7.0         1.0   \n",
       "7851  291450205013022     29.0            28.0         28.0         1.0   \n",
       "7902  291450205021180     10.0             9.0          9.0         1.0   \n",
       "7929  291450205023028      6.0             5.0          5.0         1.0   \n",
       "8022  291450206011003      6.0             4.0          4.0         2.0   \n",
       "8376  291450205012029     40.0            39.0         39.0         1.0   \n",
       "8415  291450205021181     22.0            18.0         18.0         4.0   \n",
       "8539  291450206011006     20.0            16.0         16.0         4.0   \n",
       "8551  291450205012024    101.0            26.0         26.0        75.0   \n",
       "9076  291450204001037     44.0            33.0         33.0        13.0   \n",
       "9080  291450205022179      9.0             8.0          8.0         1.0   \n",
       "9494  291450206011005     39.0            32.0         32.0         7.0   \n",
       "9511  291450205012035     55.0            41.0         41.0        14.0   \n",
       "\n",
       "      DiffCount2  residentialAP1_sum  residentialAP2v2  \n",
       "32           1.0                 4.0               4.0  \n",
       "33           1.0                13.0              13.0  \n",
       "35           1.0                14.0              14.0  \n",
       "40           2.0                39.0              41.0  \n",
       "76           4.0                62.0              62.0  \n",
       "155         23.0               183.0             189.0  \n",
       "160          2.0                23.0              23.0  \n",
       "175          1.0                 9.0               9.0  \n",
       "239          1.0                15.0              15.0  \n",
       "263          1.0                15.0              15.0  \n",
       "264          1.0                12.0              12.0  \n",
       "270          2.0                17.0              17.0  \n",
       "272          1.0                12.0              12.0  \n",
       "275          1.0                14.0              14.0  \n",
       "278          1.0                24.0              24.0  \n",
       "294          1.0                24.0              24.0  \n",
       "560          2.0                14.0              14.0  \n",
       "631          1.0                12.0              12.0  \n",
       "642          3.0                18.0              18.0  \n",
       "728          1.0                37.0              37.0  \n",
       "752          2.0                15.0              15.0  \n",
       "754          2.0                11.0              13.0  \n",
       "814          1.0                16.0              16.0  \n",
       "839          2.0                 9.0               9.0  \n",
       "842         47.0               212.0             259.0  \n",
       "845          1.0                13.0              13.0  \n",
       "908          1.0                23.0              23.0  \n",
       "918          2.0                 6.0               6.0  \n",
       "919          1.0                 9.0               9.0  \n",
       "939          2.0                48.0              48.0  \n",
       "...          ...                 ...               ...  \n",
       "4985         2.0                15.0              15.0  \n",
       "5078         4.0               111.0             111.0  \n",
       "5114         1.0                45.0             190.0  \n",
       "5115         2.0                45.0             136.0  \n",
       "5340         1.0                11.0              11.0  \n",
       "5357         1.0                 9.0              21.0  \n",
       "5686         3.0                37.0              37.0  \n",
       "5781         3.0                75.0              75.0  \n",
       "5785         1.0                14.0              14.0  \n",
       "5804         1.0                 5.0               5.0  \n",
       "6399        33.0               217.0             234.0  \n",
       "6511         3.0                41.0              41.0  \n",
       "6744         4.0                14.0              15.0  \n",
       "6841         1.0                18.0              18.0  \n",
       "6912         5.0                26.0              26.0  \n",
       "7231         2.0                 9.0               9.0  \n",
       "7348         3.0                11.0              11.0  \n",
       "7349         1.0                 7.0               7.0  \n",
       "7851         1.0                28.0              28.0  \n",
       "7902         1.0                 9.0               9.0  \n",
       "7929         1.0                 5.0               5.0  \n",
       "8022         1.0                 4.0               5.0  \n",
       "8376         1.0                39.0              39.0  \n",
       "8415         4.0                18.0              18.0  \n",
       "8539         3.0                16.0              17.0  \n",
       "8551         2.0                26.0              99.0  \n",
       "9076         6.0                31.0              38.0  \n",
       "9080         1.0                 8.0               8.0  \n",
       "9494         6.0                32.0              33.0  \n",
       "9511        10.0                41.0              45.0  \n",
       "\n",
       "[183 rows x 8 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For the 205 blocks that still have too few APs - looks like 72 out of 94 are in joplin\n",
    "displaycols = ['BLOCKID10','apcount','bldgcount1_sum','bldgcountv2','DiffCount1','DiffCount2','residentialAP1_sum','residentialAP2v2']\n",
    "census_blocks_df_rap2[displaycols].loc[\n",
    "    (census_blocks_df_rap2['ErrorCheck1'] == \"4. HU>AP\") &\n",
    "    (census_blocks_df_rap2['ErrorCheck2'] ==  \"4. HU>AP\") &\n",
    "    (census_blocks_df_rap2['Joplin']==\"Joplin\")]"
   ]
  },
  {
   "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>DiffCount1</th>\n",
       "      <th>DiffCount2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1591.000000</td>\n",
       "      <td>1591.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.403520</td>\n",
       "      <td>-2.945946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>16.947996</td>\n",
       "      <td>6.433176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-92.000000</td>\n",
       "      <td>-92.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-4.000000</td>\n",
       "      <td>-4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>261.000000</td>\n",
       "      <td>47.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DiffCount1   DiffCount2\n",
       "count  1591.000000  1591.000000\n",
       "mean     -0.403520    -2.945946\n",
       "std      16.947996     6.433176\n",
       "min     -92.000000   -92.000000\n",
       "25%      -4.000000    -4.000000\n",
       "50%       0.000000    -1.000000\n",
       "75%       0.000000     0.000000\n",
       "max     261.000000    47.000000"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_blocks_df_rap2[['DiffCount1','DiffCount2']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merge Block level data with building level data\n",
    "census_blocks_df_rap2 = census_blocks_df_rap2.rename(index=str, columns={\n",
    "    \"residentialAP2v2\": \"residentialAP2v2_sum\", \n",
    "    \"bldgcountv2\": \"bldgcountv2_sum\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count        28152\n",
       "unique       28152\n",
       "top       B0012554\n",
       "freq             1\n",
       "Name: bldg_id, dtype: object"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keepcolumns = ['BLOCKID10','residentialAP2v2_sum','bldgcountv2_sum','DiffCount2','ErrorCheck2']\n",
    "building_gdf_round2_v3 = pd.merge(building_gdf_round2_v2, census_blocks_df_rap2[keepcolumns], \n",
    "                                  left_on='BLOCKID10', right_on='BLOCKID10', how='left')\n",
    "# Convert Pandas Data Frame from Merge to Geodataframe\n",
    "building_gdf_round2_v3 = gpd.GeoDataFrame(building_gdf_round2_v3, crs=building_gdf.crs)\n",
    "building_gdf_round2_v3['bldg_id'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "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>Unnamed: 0</th>\n",
       "      <th>bldg_id</th>\n",
       "      <th>parid</th>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th>STATEFP10</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>TRACTCE10</th>\n",
       "      <th>PUMGEOID10</th>\n",
       "      <th>PUMNAME10</th>\n",
       "      <th>PLCGEOID10</th>\n",
       "      <th>...</th>\n",
       "      <th>DiffCount1</th>\n",
       "      <th>ErrorCheck1</th>\n",
       "      <th>Res_Area</th>\n",
       "      <th>Sum_Res_Area</th>\n",
       "      <th>residentialAP2</th>\n",
       "      <th>residentialAP2v2</th>\n",
       "      <th>residentialAP2v2_sum</th>\n",
       "      <th>bldgcountv2_sum</th>\n",
       "      <th>DiffCount2</th>\n",
       "      <th>ErrorCheck2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>B0000001</td>\n",
       "      <td>P16703610001025000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "      <td>107.940427</td>\n",
       "      <td>23104.086156</td>\n",
       "      <td>-0.112126</td>\n",
       "      <td>1.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>B0000002</td>\n",
       "      <td>P16703610001028000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "      <td>169.494274</td>\n",
       "      <td>23104.086156</td>\n",
       "      <td>-0.176067</td>\n",
       "      <td>1.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>B0000003</td>\n",
       "      <td>P16703610001027000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23104.086156</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>B0000004</td>\n",
       "      <td>P16703610001029000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "      <td>185.178358</td>\n",
       "      <td>23104.086156</td>\n",
       "      <td>-0.192359</td>\n",
       "      <td>1.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>B0000005</td>\n",
       "      <td>P16703610001059000</td>\n",
       "      <td>290970102003000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>2902800.0</td>\n",
       "      <td>Jasper &amp; Newton Counties PUMA</td>\n",
       "      <td>2937592.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "      <td>202.291430</td>\n",
       "      <td>23104.086156</td>\n",
       "      <td>-0.210136</td>\n",
       "      <td>1.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>3. HU&lt;AP</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 76 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0   bldg_id               parid        BLOCKID10  STATEFP10  \\\n",
       "0           0  B0000001  P16703610001025000  290970102003000       29.0   \n",
       "1           1  B0000002  P16703610001028000  290970102003000       29.0   \n",
       "2           2  B0000003  P16703610001027000  290970102003000       29.0   \n",
       "3           3  B0000004  P16703610001029000  290970102003000       29.0   \n",
       "4           4  B0000005  P16703610001059000  290970102003000       29.0   \n",
       "\n",
       "   COUNTYFP10  TRACTCE10  PUMGEOID10                      PUMNAME10  \\\n",
       "0        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "1        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "2        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "3        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "4        97.0    10200.0   2902800.0  Jasper & Newton Counties PUMA   \n",
       "\n",
       "   PLCGEOID10  ... DiffCount1 ErrorCheck1    Res_Area  Sum_Res_Area  \\\n",
       "0   2937592.0  ...      -24.0    3. HU<AP  107.940427  23104.086156   \n",
       "1   2937592.0  ...      -24.0    3. HU<AP  169.494274  23104.086156   \n",
       "2   2937592.0  ...      -24.0    3. HU<AP    0.000000  23104.086156   \n",
       "3   2937592.0  ...      -24.0    3. HU<AP  185.178358  23104.086156   \n",
       "4   2937592.0  ...      -24.0    3. HU<AP  202.291430  23104.086156   \n",
       "\n",
       "   residentialAP2  residentialAP2v2  residentialAP2v2_sum  bldgcountv2_sum  \\\n",
       "0       -0.112126               1.0                 127.0            155.0   \n",
       "1       -0.176067               1.0                 127.0            155.0   \n",
       "2       -0.000000               0.0                 127.0            155.0   \n",
       "3       -0.192359               1.0                 127.0            155.0   \n",
       "4       -0.210136               1.0                 127.0            155.0   \n",
       "\n",
       "   DiffCount2  ErrorCheck2  \n",
       "0       -24.0     3. HU<AP  \n",
       "1       -24.0     3. HU<AP  \n",
       "2       -24.0     3. HU<AP  \n",
       "3       -24.0     3. HU<AP  \n",
       "4       -24.0     3. HU<AP  \n",
       "\n",
       "[5 rows x 76 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf_round2_v3.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### For Round 3 - \n",
    "I think the best option would be to simply add an additional address point to every structure in the block. This might cause some problems but it would also maximize the uncertainty in assigning housing unit data to buildings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Housing Unit Count')"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Difference in Count for Blocks with fewer AP than Housing Units\n",
    "x = building_gdf_round2_v3['DiffCount2'].loc[(building_gdf_round2_v3['ErrorCheck2']==\"4. HU>AP\")]\n",
    "y = building_gdf_round2_v3['apcount'].loc[(building_gdf_round2_v3['ErrorCheck2']==\"4. HU>AP\")]\n",
    "plt.scatter(x, y)\n",
    "plt.xlabel(\"Diff Count 2\")\n",
    "plt.ylabel(\"Housing Unit Count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Round 3 version of Address Point Estiamte\n",
    "building_gdf_round3_v1 = building_gdf_round2_v3\n",
    "building_gdf_round3_v1['residentialAP3v1'] = building_gdf_round3_v1['residentialAP2v2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5872.000000\n",
       "mean        1.030654\n",
       "std         1.292147\n",
       "min         0.000000\n",
       "25%         1.000000\n",
       "50%         1.000000\n",
       "75%         1.000000\n",
       "max        37.000000\n",
       "Name: residentialAP3v1, dtype: float64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf_round3_v1['residentialAP3v1'].loc[(building_gdf_round3_v1['ErrorCheck2']==\"4. HU>AP\")].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5872.000000\n",
       "mean        1.824591\n",
       "std         1.502699\n",
       "min         0.000000\n",
       "25%         2.000000\n",
       "50%         2.000000\n",
       "75%         2.000000\n",
       "max        38.000000\n",
       "Name: residentialAP3v1, dtype: float64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building_gdf_round3_v1.loc[(building_gdf_round3_v1['ErrorCheck2']==\"4. HU>AP\") &\n",
    "                          (building_gdf_round2_v3['residentialAP2v2']>=1),\n",
    "                           'residentialAP3v1'] = building_gdf_round3_v1['residentialAP3v1'] + 1\n",
    "building_gdf_round3_v1['residentialAP3v1'].loc[(building_gdf_round3_v1['ErrorCheck2']==\"4. HU>AP\")].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sum Residential Addresspoints (third attempt) by blockid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\nathanael99\\AppData\\Local\\Continuum\\anaconda3\\envs\\pyincore20190618\\lib\\site-packages\\ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  after removing the cwd from sys.path.\n"
     ]
    },
    {
     "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>residentialAP3v1</th>\n",
       "      <th>bldgcountv3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BLOCKID10</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>290970101001000</th>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001001</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001002</th>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001003</th>\n",
       "      <td>29.0</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290970101001006</th>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 residentialAP3v1  bldgcountv3\n",
       "BLOCKID10                                     \n",
       "290970101001000               5.0            5\n",
       "290970101001001               2.0            2\n",
       "290970101001002               3.0            4\n",
       "290970101001003              29.0           33\n",
       "290970101001006              10.0           10"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sum Buildings over the column BLOCKID.\n",
    "# https://www.geeksforgeeks.org/python-pandas-dataframe-sum/\n",
    "block_rap3_gdf = building_gdf_round3_v1[['BLOCKID10','residentialAP3v1']]\n",
    "block_rap3_gdf['bldgcountv3'] = 1\n",
    "block_rap3_gdf_sum = block_rap3_gdf.groupby(['BLOCKID10']).sum()\n",
    "block_rap3_gdf_sum.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1829.000000\n",
       "mean       19.363040\n",
       "std        31.013099\n",
       "min         0.000000\n",
       "25%         6.000000\n",
       "50%        13.000000\n",
       "75%        24.000000\n",
       "max       471.000000\n",
       "Name: residentialAP3v1, dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "block_rap3_gdf_sum['residentialAP3v1'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Error Check Round 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9.621000e+03\n",
       "mean     2.911818e+14\n",
       "std      2.383822e+11\n",
       "min      2.909701e+14\n",
       "25%      2.909701e+14\n",
       "50%      2.909701e+14\n",
       "75%      2.914502e+14\n",
       "max      2.914502e+14\n",
       "Name: BLOCKID10, dtype: float64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "census_blocks_df_rap2['BLOCKID10'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9.621000e+03\n",
       "mean     2.911818e+14\n",
       "std      2.383822e+11\n",
       "min      2.909701e+14\n",
       "25%      2.909701e+14\n",
       "50%      2.909701e+14\n",
       "75%      2.914502e+14\n",
       "max      2.914502e+14\n",
       "Name: BLOCKID10, dtype: float64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge Sum of Residential Address Points with Census Counts\n",
    "census_blocks_df_rap3 = pd.merge(census_blocks_df_rap2, block_rap3_gdf_sum,\n",
    "                                  left_on='BLOCKID10', right_on='BLOCKID10', how='left')\n",
    "census_blocks_df_rap3['BLOCKID10'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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>ErrorCheck3</th>\n",
       "      <th>1. HU=0</th>\n",
       "      <th>2. HU=AP</th>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>238</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>0</td>\n",
       "      <td>545</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>814</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. HU&gt;AP</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>232</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4733</td>\n",
       "      <td>0</td>\n",
       "      <td>4733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3059</td>\n",
       "      <td>3059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>238</td>\n",
       "      <td>545</td>\n",
       "      <td>1046</td>\n",
       "      <td>4733</td>\n",
       "      <td>3059</td>\n",
       "      <td>9621</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ErrorCheck3                          1. HU=0  2. HU=AP  3. HU<AP  \\\n",
       "ErrorCheck2                                                        \n",
       "1. HU=0                                  238         0         0   \n",
       "2. HU=AP                                   0       545         0   \n",
       "3. HU<AP                                   0         0       814   \n",
       "4. HU>AP                                   0         0       232   \n",
       "8. HU > 0, Building Count = Missing        0         0         0   \n",
       "9. HU = 0, Building Count = Missing        0         0         0   \n",
       "Total                                    238       545      1046   \n",
       "\n",
       "ErrorCheck3                          8. HU > 0, Building Count = Missing  \\\n",
       "ErrorCheck2                                                                \n",
       "1. HU=0                                                                0   \n",
       "2. HU=AP                                                               0   \n",
       "3. HU<AP                                                               0   \n",
       "4. HU>AP                                                               0   \n",
       "8. HU > 0, Building Count = Missing                                 4733   \n",
       "9. HU = 0, Building Count = Missing                                    0   \n",
       "Total                                                               4733   \n",
       "\n",
       "ErrorCheck3                          9. HU = 0, Building Count = Missing  \\\n",
       "ErrorCheck2                                                                \n",
       "1. HU=0                                                                0   \n",
       "2. HU=AP                                                               0   \n",
       "3. HU<AP                                                               0   \n",
       "4. HU>AP                                                               0   \n",
       "8. HU > 0, Building Count = Missing                                    0   \n",
       "9. HU = 0, Building Count = Missing                                 3059   \n",
       "Total                                                               3059   \n",
       "\n",
       "ErrorCheck3                          Total  \n",
       "ErrorCheck2                                 \n",
       "1. HU=0                                238  \n",
       "2. HU=AP                               545  \n",
       "3. HU<AP                               814  \n",
       "4. HU>AP                               232  \n",
       "8. HU > 0, Building Count = Missing   4733  \n",
       "9. HU = 0, Building Count = Missing   3059  \n",
       "Total                                 9621  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "block_error_check_addresspoints(census_blocks_df_rap3,'apcount','residentialAP3v1','bldgcountv3','ErrorCheck3')\n",
    "pd.crosstab(census_blocks_df_rap3['ErrorCheck2'], census_blocks_df_rap3['ErrorCheck3'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "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>Joplin</th>\n",
       "      <th>Joplin</th>\n",
       "      <th>Not Joplin</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ErrorCheck3</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. HU=0</th>\n",
       "      <td>222</td>\n",
       "      <td>16</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. HU=AP</th>\n",
       "      <td>485</td>\n",
       "      <td>60</td>\n",
       "      <td>545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. HU&lt;AP</th>\n",
       "      <td>929</td>\n",
       "      <td>117</td>\n",
       "      <td>1046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8. HU &gt; 0, Building Count = Missing</th>\n",
       "      <td>31</td>\n",
       "      <td>4702</td>\n",
       "      <td>4733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9. HU = 0, Building Count = Missing</th>\n",
       "      <td>358</td>\n",
       "      <td>2701</td>\n",
       "      <td>3059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>2025</td>\n",
       "      <td>7596</td>\n",
       "      <td>9621</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Joplin                               Joplin  Not Joplin  Total\n",
       "ErrorCheck3                                                   \n",
       "1. HU=0                                 222          16    238\n",
       "2. HU=AP                                485          60    545\n",
       "3. HU<AP                                929         117   1046\n",
       "8. HU > 0, Building Count = Missing      31        4702   4733\n",
       "9. HU = 0, Building Count = Missing     358        2701   3059\n",
       "Total                                  2025        7596   9621"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(census_blocks_df_rap3['ErrorCheck3'], census_blocks_df_rap3['Joplin'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>archtype</th>\n",
       "      <th>1</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>residentialAP3v1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>4427</td>\n",
       "      <td>30</td>\n",
       "      <td>604</td>\n",
       "      <td>659</td>\n",
       "      <td>141</td>\n",
       "      <td>20</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>28</td>\n",
       "      <td>38</td>\n",
       "      <td>21</td>\n",
       "      <td>18</td>\n",
       "      <td>24</td>\n",
       "      <td>90</td>\n",
       "      <td>6</td>\n",
       "      <td>437</td>\n",
       "      <td>6588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>11649</td>\n",
       "      <td>13</td>\n",
       "      <td>80</td>\n",
       "      <td>174</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>39</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>118</td>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>12268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>7003</td>\n",
       "      <td>16</td>\n",
       "      <td>22</td>\n",
       "      <td>85</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>156</td>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>7374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>1242</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>1358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>197</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>73</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.0</th>\n",
       "      <td>44</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7.0</th>\n",
       "      <td>16</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8.0</th>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.0</th>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.0</th>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11.0</th>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12.0</th>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13.0</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14.0</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15.0</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16.0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17.0</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18.0</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19.0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21.0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23.0</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25.0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37.0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38.0</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66.0</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113.0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>24757</td>\n",
       "      <td>146</td>\n",
       "      <td>736</td>\n",
       "      <td>963</td>\n",
       "      <td>155</td>\n",
       "      <td>39</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>41</td>\n",
       "      <td>88</td>\n",
       "      <td>28</td>\n",
       "      <td>21</td>\n",
       "      <td>30</td>\n",
       "      <td>379</td>\n",
       "      <td>10</td>\n",
       "      <td>701</td>\n",
       "      <td>28152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "archtype              1    5    6    7    8   9  10  11  12  13  14  15  16  \\\n",
       "residentialAP3v1                                                              \n",
       "0.0                4427   30  604  659  141  20  40   5  28  38  21  18  24   \n",
       "1.0               11649   13   80  174    8  13   7   3   9  39   3   3   2   \n",
       "2.0                7003   16   22   85    4   3   1   0   1   6   1   0   1   \n",
       "3.0                1242   13   18   19    1   2   2   0   1   4   2   0   0   \n",
       "4.0                 197   20    5   15    1   0   0   0   0   0   1   0   0   \n",
       "5.0                  73    3    0    4    0   0   0   0   1   0   0   0   1   \n",
       "6.0                  44    3    1    1    0   0   0   0   0   0   0   0   1   \n",
       "7.0                  16    8    0    1    0   0   0   0   0   0   0   0   1   \n",
       "8.0                  18   13    0    1    0   0   0   0   0   0   0   0   0   \n",
       "9.0                  10    6    0    3    0   0   0   0   0   1   0   0   0   \n",
       "10.0                 11    2    4    0    0   0   0   0   0   0   0   0   0   \n",
       "11.0                 13    7    0    0    0   0   0   0   0   0   0   0   0   \n",
       "12.0                 16    2    0    0    0   0   0   0   0   0   0   0   0   \n",
       "13.0                  7    1    1    0    0   0   0   0   0   0   0   0   0   \n",
       "14.0                  4    1    0    0    0   1   0   0   0   0   0   0   0   \n",
       "15.0                  5    0    0    0    0   0   0   0   1   0   0   0   0   \n",
       "16.0                  1    2    0    0    0   0   0   0   0   0   0   0   0   \n",
       "17.0                  2    0    0    1    0   0   0   0   0   0   0   0   0   \n",
       "18.0                  2    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "19.0                  0    1    0    0    0   0   0   0   0   0   0   0   0   \n",
       "21.0                  1    2    0    0    0   0   0   0   0   0   0   0   0   \n",
       "22.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "23.0                  0    2    0    0    0   0   0   0   0   0   0   0   0   \n",
       "25.0                  0    1    0    0    0   0   0   0   0   0   0   0   0   \n",
       "29.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "30.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "31.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "32.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "33.0                  1    0    1    0    0   0   0   0   0   0   0   0   0   \n",
       "35.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "36.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "37.0                  0    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "38.0                  3    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "41.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "66.0                  2    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "92.0                  1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "113.0                 1    0    0    0    0   0   0   0   0   0   0   0   0   \n",
       "Total             24757  146  736  963  155  39  50   8  41  88  28  21  30   \n",
       "\n",
       "archtype           17  18   19  Total  \n",
       "residentialAP3v1                       \n",
       "0.0                90   6  437   6588  \n",
       "1.0               118   0  147  12268  \n",
       "2.0               156   0   75   7374  \n",
       "3.0                15   0   39   1358  \n",
       "4.0                 0   1    1    241  \n",
       "5.0                 0   1    1     84  \n",
       "6.0                 0   0    1     51  \n",
       "7.0                 0   0    0     26  \n",
       "8.0                 0   0    0     32  \n",
       "9.0                 0   0    0     20  \n",
       "10.0                0   0    0     17  \n",
       "11.0                0   0    0     20  \n",
       "12.0                0   0    0     18  \n",
       "13.0                0   0    0      9  \n",
       "14.0                0   0    0      6  \n",
       "15.0                0   0    0      6  \n",
       "16.0                0   0    0      3  \n",
       "17.0                0   0    0      3  \n",
       "18.0                0   0    0      2  \n",
       "19.0                0   0    0      1  \n",
       "21.0                0   0    0      3  \n",
       "22.0                0   1    0      2  \n",
       "23.0                0   0    0      2  \n",
       "25.0                0   0    0      1  \n",
       "29.0                0   0    0      1  \n",
       "30.0                0   0    0      1  \n",
       "31.0                0   0    0      1  \n",
       "32.0                0   0    0      1  \n",
       "33.0                0   0    0      2  \n",
       "35.0                0   0    0      1  \n",
       "36.0                0   0    0      1  \n",
       "37.0                0   1    0      1  \n",
       "38.0                0   0    0      3  \n",
       "41.0                0   0    0      1  \n",
       "66.0                0   0    0      2  \n",
       "92.0                0   0    0      1  \n",
       "113.0               0   0    0      1  \n",
       "Total             379  10  701  28152  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(building_gdf_round3_v1['residentialAP3v1'], building_gdf_round3_v1['archtype'], margins=True, margins_name=\"Total\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Look at outliers in Archtype and Estimated counts\n",
    "Small residential structure with more than 10 housing unts. Especially example of 141 housing units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "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>BLOCKID10</th>\n",
       "      <th>bldg_id</th>\n",
       "      <th>archtype</th>\n",
       "      <th>PLCNAME10</th>\n",
       "      <th>COUNTYFP10</th>\n",
       "      <th>bldgcount1_sum</th>\n",
       "      <th>residentialAP3v1</th>\n",
       "      <th>apcount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12980</th>\n",
       "      <td>291450205012032</td>\n",
       "      <td>B0007913</td>\n",
       "      <td>5</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>145.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7972</th>\n",
       "      <td>290970103002027</td>\n",
       "      <td>B0023442</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>239.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10110</th>\n",
       "      <td>290970103002033</td>\n",
       "      <td>B0030074</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10109</th>\n",
       "      <td>290970103002033</td>\n",
       "      <td>B0030073</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11609</th>\n",
       "      <td>290970107001036</td>\n",
       "      <td>B0003766</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>67.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14182</th>\n",
       "      <td>290970106001016</td>\n",
       "      <td>B0012068</td>\n",
       "      <td>6</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10108</th>\n",
       "      <td>290970103002033</td>\n",
       "      <td>B0030072</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26149</th>\n",
       "      <td>291450205021078</td>\n",
       "      <td>B0025661</td>\n",
       "      <td>1</td>\n",
       "      <td>Shoal Creek Drive</td>\n",
       "      <td>145.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4532</th>\n",
       "      <td>290970110002025</td>\n",
       "      <td>B0019637</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6243</th>\n",
       "      <td>290970101001080</td>\n",
       "      <td>B0021601</td>\n",
       "      <td>18</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7982</th>\n",
       "      <td>290970103002027</td>\n",
       "      <td>B0023543</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>239.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10111</th>\n",
       "      <td>290970103002033</td>\n",
       "      <td>B0030075</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10112</th>\n",
       "      <td>290970103002033</td>\n",
       "      <td>B0030076</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4531</th>\n",
       "      <td>290970110002025</td>\n",
       "      <td>B0019636</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6016</th>\n",
       "      <td>290970101001063</td>\n",
       "      <td>B0021273</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6015</th>\n",
       "      <td>290970101001063</td>\n",
       "      <td>B0021272</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10146</th>\n",
       "      <td>290970104001006</td>\n",
       "      <td>B0030093</td>\n",
       "      <td>1</td>\n",
       "      <td>Joplin</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27516</th>\n",
       "      <td>290970104002019</td>\n",
       "      <td>B0028119</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>112.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             BLOCKID10   bldg_id  archtype          PLCNAME10  COUNTYFP10  \\\n",
       "12980  291450205012032  B0007913         5             Joplin       145.0   \n",
       "7972   290970103002027  B0023442         1             Joplin        97.0   \n",
       "10110  290970103002033  B0030074         1             Joplin        97.0   \n",
       "10109  290970103002033  B0030073         1             Joplin        97.0   \n",
       "11609  290970107001036  B0003766         1             Joplin        97.0   \n",
       "14182  290970106001016  B0012068         6             Joplin        97.0   \n",
       "10108  290970103002033  B0030072         1             Joplin        97.0   \n",
       "26149  291450205021078  B0025661         1  Shoal Creek Drive       145.0   \n",
       "4532   290970110002025  B0019637         1             Joplin        97.0   \n",
       "6243   290970101001080  B0021601        18             Joplin        97.0   \n",
       "7982   290970103002027  B0023543         1             Joplin        97.0   \n",
       "10111  290970103002033  B0030075         1             Joplin        97.0   \n",
       "10112  290970103002033  B0030076         1             Joplin        97.0   \n",
       "4531   290970110002025  B0019636         1             Joplin        97.0   \n",
       "6016   290970101001063  B0021273         1             Joplin        97.0   \n",
       "6015   290970101001063  B0021272         1             Joplin        97.0   \n",
       "10146  290970104001006  B0030093         1             Joplin        97.0   \n",
       "27516  290970104002019  B0028119         1                NaN        97.0   \n",
       "\n",
       "       bldgcount1_sum  residentialAP3v1  apcount  \n",
       "12980             2.0              25.0     48.0  \n",
       "7972             45.0              29.0    239.0  \n",
       "10110            32.0              30.0    180.0  \n",
       "10109            32.0              31.0    180.0  \n",
       "11609             3.0              32.0     67.0  \n",
       "14182             3.0              33.0     36.0  \n",
       "10108            32.0              33.0    180.0  \n",
       "26149             1.0              35.0     35.0  \n",
       "4532              4.0              36.0     77.0  \n",
       "6243              4.0              37.0     59.0  \n",
       "7982             45.0              38.0    239.0  \n",
       "10111            32.0              38.0    180.0  \n",
       "10112            32.0              38.0    180.0  \n",
       "4531              4.0              41.0     77.0  \n",
       "6016              2.0              66.0    130.0  \n",
       "6015              2.0              66.0    130.0  \n",
       "10146             3.0              92.0     98.0  \n",
       "27516             1.0             113.0    112.0  "
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "displaycols = ['BLOCKID10','bldg_id','archtype','PLCNAME10','COUNTYFP10','bldgcount1_sum','residentialAP3v1','apcount']\n",
    "condition = building_gdf_round3_v1['residentialAP3v1']> 24\n",
    "building_gdf_round3_v1[displaycols].loc[condition].sort_values(by=['residentialAP3v1'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Block ID 290970104002019\n",
    "Large block on the edge of Joplin. The block has only 1 building footprint - all of the housing units are assigned to the one building.\n",
    "\n",
    "### Block ID 290970104001006\n",
    "This is the large retirment home. The building type Archtype 1 - may not be the accurate building type.\n",
    "\n",
    "### Block ID 290970101001063\n",
    "This block also has a retirment home in tower. The Archtype 1 is not accurate.\n",
    "\n",
    "### Block ID 290970103002033\n",
    "This block is the campus of Missouri Southern State. There are apartments on campus. It might be possible to shift the residential units to the archtype 1 in this case.\n",
    "\n",
    "\n",
    "### Block ID 290970101001080\n",
    "Block has 4 buildings all appear to be shopping centers. The address 601 S MAIN ST is actually an apartment building. So the program is correct.\n",
    "\n",
    "### Block ID 290970103002027\n",
    "Block includes the rest of Missouri Southern State - with several dorms that are not being assigned any housing units. This might be a case where the dorm buildings could be identified and the Group Quarters Population could be distributed here. Otherwise this block does have a lot of apartment complexes and the program is distributing the bulck of the housing units to apartment buildings.\n",
    "The 2 buildings in block 290970103002027 -B0023442 and  B0023543 - are a large apartment complex called college view manor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save Work at this point - Save as CSV\n",
    "savefile = sys.path[0]+\"/\"+programname+\"/\"+programname+\"_huestimate_EPSG4326.csv\"\n",
    "building_gdf_round3_v1.to_csv(savefile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}