{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3ab8f7c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import csv\n",
    "from pathlib import Path\n",
    "import os\n",
    "import sys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8c22494f",
   "metadata": {},
   "outputs": [],
   "source": [
    "module_path = os.path.abspath(os.path.join(\"..\"))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "eb31e9a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_PATH = Path.cwd().parent / \"data\"\n",
    "TMP_PATH: Path = DATA_PATH / \"tmp\"\n",
    "OUTPUT_PATH = DATA_PATH / \"score\" / \"csv\" / \"tiles\"\n",
    "CENSUS_USA_CSV = DATA_PATH / \"census\" / \"csv\" / \"us.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "95a5f8d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "cbg_usa_df = pd.read_csv(\n",
    "    CENSUS_USA_CSV,\n",
    "    names=[\"GEOID10\"],\n",
    "    dtype={\"GEOID10\": \"string\"},\n",
    "    low_memory=False,\n",
    "    header=None,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bdd9ab60",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GEOID10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100010414002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100010415002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100010417011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100010417012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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      ],
      "text/plain": [
       "        GEOID10\n",
       "0  100010414002\n",
       "1  100010415002\n",
       "2  100010417011\n",
       "3  100010417012\n",
       "4  100010422011"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cbg_usa_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "05a40080",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GEOID10    string\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cbg_usa_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "114af777",
   "metadata": {},
   "outputs": [],
   "source": [
    "score_df = pd.read_csv(\n",
    "    OUTPUT_PATH / \"usa.csv\",\n",
    "    dtype={\"GEOID10\": \"string\"},\n",
    "    low_memory=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d5f3ebd4",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>GEOID10</th>\n",
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       "      <th>Score E (top 25th percentile)</th>\n",
       "      <th>GEOID</th>\n",
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       "      <td>10001</td>\n",
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       "      <td>10001</td>\n",
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       "      <th>220256</th>\n",
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       "      <td>0.921941</td>\n",
       "      <td>True</td>\n",
       "      <td>34007</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Camden County</td>\n",
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       "    <tr>\n",
       "      <th>220257</th>\n",
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       "      <td>0.934490</td>\n",
       "      <td>True</td>\n",
       "      <td>34007</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Camden County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220258</th>\n",
       "      <td>340076015005</td>\n",
       "      <td>0.889613</td>\n",
       "      <td>True</td>\n",
       "      <td>34007</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Camden County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220259</th>\n",
       "      <td>340076091032</td>\n",
       "      <td>0.627822</td>\n",
       "      <td>False</td>\n",
       "      <td>34007</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Camden County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220260</th>\n",
       "      <td>340076053002</td>\n",
       "      <td>0.762237</td>\n",
       "      <td>True</td>\n",
       "      <td>34007</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Camden County</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>220261 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             GEOID10  Score E (percentile)  Score E (top 25th percentile)  \\\n",
       "0       100010414002              0.808889                           True   \n",
       "1       100010415002              0.555160                          False   \n",
       "2       100010417011              0.272392                          False   \n",
       "3       100010417012              0.345686                          False   \n",
       "4       100010422011              0.472567                          False   \n",
       "...              ...                   ...                            ...   \n",
       "220256  340076020004              0.921941                           True   \n",
       "220257  340076017002              0.934490                           True   \n",
       "220258  340076015005              0.889613                           True   \n",
       "220259  340076091032              0.627822                          False   \n",
       "220260  340076053002              0.762237                           True   \n",
       "\n",
       "        GEOID State Abbreviation    County Name  \n",
       "0       10001                 DE    Kent County  \n",
       "1       10001                 DE    Kent County  \n",
       "2       10001                 DE    Kent County  \n",
       "3       10001                 DE    Kent County  \n",
       "4       10001                 DE    Kent County  \n",
       "...       ...                ...            ...  \n",
       "220256  34007                 NJ  Camden County  \n",
       "220257  34007                 NJ  Camden County  \n",
       "220258  34007                 NJ  Camden County  \n",
       "220259  34007                 NJ  Camden County  \n",
       "220260  34007                 NJ  Camden County  \n",
       "\n",
       "[220261 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f84f9e1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GEOID10                           string\n",
       "Score E (percentile)             float64\n",
       "Score E (top 25th percentile)       bool\n",
       "GEOID                              int64\n",
       "State Abbreviation                object\n",
       "County Name                       object\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8d61e29e",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_df = cbg_usa_df.merge(score_df, on=\"GEOID10\", how=\"left\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7e8c2f2a",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "             GEOID10  Score E (percentile) Score E (top 25th percentile)  \\\n",
       "0       100010414002              0.808889                          True   \n",
       "1       100010415002              0.555160                         False   \n",
       "2       100010417011              0.272392                         False   \n",
       "3       100010417012              0.345686                         False   \n",
       "4       100010422011              0.472567                         False   \n",
       "...              ...                   ...                           ...   \n",
       "220329  340076020004              0.921941                          True   \n",
       "220330  340076017002              0.934490                          True   \n",
       "220331  340076015005              0.889613                          True   \n",
       "220332  340076091032              0.627822                         False   \n",
       "220333  340076053002              0.762237                          True   \n",
       "\n",
       "          GEOID State Abbreviation    County Name  \n",
       "0       10001.0                 DE    Kent County  \n",
       "1       10001.0                 DE    Kent County  \n",
       "2       10001.0                 DE    Kent County  \n",
       "3       10001.0                 DE    Kent County  \n",
       "4       10001.0                 DE    Kent County  \n",
       "...         ...                ...            ...  \n",
       "220329  34007.0                 NJ  Camden County  \n",
       "220330  34007.0                 NJ  Camden County  \n",
       "220331  34007.0                 NJ  Camden County  \n",
       "220332  34007.0                 NJ  Camden County  \n",
       "220333  34007.0                 NJ  Camden County  \n",
       "\n",
       "[220334 rows x 6 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e81b1321",
   "metadata": {},
   "outputs": [
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>174140</th>\n",
       "      <td>040190029031</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>174143</th>\n",
       "      <td>040190027012</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>174184</th>\n",
       "      <td>040190027011</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>174242</th>\n",
       "      <td>040194105021</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>174243</th>\n",
       "      <td>040194105011</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",
       "<p>73 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             GEOID10  Score E (percentile) Score E (top 25th percentile)  \\\n",
       "10614   515150501002                   NaN                           NaN   \n",
       "10615   515150501003                   NaN                           NaN   \n",
       "10627   515150501001                   NaN                           NaN   \n",
       "10628   515150501005                   NaN                           NaN   \n",
       "10629   515150501004                   NaN                           NaN   \n",
       "...              ...                   ...                           ...   \n",
       "174140  040190029031                   NaN                           NaN   \n",
       "174143  040190027012                   NaN                           NaN   \n",
       "174184  040190027011                   NaN                           NaN   \n",
       "174242  040194105021                   NaN                           NaN   \n",
       "174243  040194105011                   NaN                           NaN   \n",
       "\n",
       "        GEOID State Abbreviation County Name  \n",
       "10614     NaN                NaN         NaN  \n",
       "10615     NaN                NaN         NaN  \n",
       "10627     NaN                NaN         NaN  \n",
       "10628     NaN                NaN         NaN  \n",
       "10629     NaN                NaN         NaN  \n",
       "...       ...                ...         ...  \n",
       "174140    NaN                NaN         NaN  \n",
       "174143    NaN                NaN         NaN  \n",
       "174184    NaN                NaN         NaN  \n",
       "174242    NaN                NaN         NaN  \n",
       "174243    NaN                NaN         NaN  \n",
       "\n",
       "[73 rows x 6 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df[merged_df[\"Score E (percentile)\"].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1a7b71d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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