CIFTools User Guide.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cfc551a1",
   "metadata": {},
   "source": [
    "## `acs_sdoh`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7359ca67",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIFTools import acs_sdoh"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a200dbc",
   "metadata": {},
   "source": [
    "Using `acs_sdoh`, you can not just download data for Cancer_InFocus but also for your own data project.   \n",
    "Let's first take a look at how to download acs_sdoh data.   \n",
    "`acs_sdoh` takes following arguments:   \n",
    "* year: int\n",
    "* state_fips : str, int or list of str (2 digit state fips code)\n",
    "* query_level : str (possible values: 'state','county', 'tract','county subregion', 'block', 'zip'\n",
    "* key : census key\n",
    "\n",
    "You can sign up for the census key at : https://api.census.gov/data/key_signup.html\n",
    "\n",
    "In this tutorial, we will use the sample key that may already be expired by the time you read the tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0ab772e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "key = 'f1a4c4de1f35fe90fc1ceb60fd97b39c9a96e436' # provide the census api user key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d80eee42",
   "metadata": {},
   "outputs": [],
   "source": [
    "sdoh = acs_sdoh(2019, ['21','22'], 'puma', key = key)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87e1da56",
   "metadata": {},
   "source": [
    "The function that you may call to scrap data for Cancer_InFocus is `cancer_infocus_download`.   \n",
    "This function does not require any arguement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "46684cc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dictionary = sdoh.cancer_infocus_download()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "41e0e5f2",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PUMA_ID</th>\n",
       "      <th>PUMA_NAME</th>\n",
       "      <th>State</th>\n",
       "      <th>health_insurance_coverage_rate</th>\n",
       "      <th>medicaid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00100</td>\n",
       "      <td>Purchase Area Development District PUMA</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.943543</td>\n",
       "      <td>0.262831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00200</td>\n",
       "      <td>Pennyrile Area Development District (North) PUMA</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.935507</td>\n",
       "      <td>0.252209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00300</td>\n",
       "      <td>Pennyrile Area Development District (South) PUMA</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.907533</td>\n",
       "      <td>0.278923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00400</td>\n",
       "      <td>Barren River Area Development District (Outer)...</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.932068</td>\n",
       "      <td>0.305751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00500</td>\n",
       "      <td>Barren River Area Development District (Centra...</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.945148</td>\n",
       "      <td>0.232757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>02302</td>\n",
       "      <td>Regional Planning Commission 5--Jefferson Pari...</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.884315</td>\n",
       "      <td>0.337925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>02400</td>\n",
       "      <td>Regional Planning Commission 6--New Orleans Ci...</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.915558</td>\n",
       "      <td>0.335580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>02401</td>\n",
       "      <td>Regional Planning Commission 7--New Orleans Ci...</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.883772</td>\n",
       "      <td>0.361050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>02402</td>\n",
       "      <td>Regional Planning Commission 8--New Orleans Ci...</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.921396</td>\n",
       "      <td>0.214011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>02500</td>\n",
       "      <td>Regional Planning Commission 9--St. Bernard</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.904672</td>\n",
       "      <td>0.295947</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PUMA_ID                                          PUMA_NAME      State   \n",
       "0    00100            Purchase Area Development District PUMA   Kentucky  \\\n",
       "1    00200   Pennyrile Area Development District (North) PUMA   Kentucky   \n",
       "2    00300   Pennyrile Area Development District (South) PUMA   Kentucky   \n",
       "3    00400  Barren River Area Development District (Outer)...   Kentucky   \n",
       "4    00500  Barren River Area Development District (Centra...   Kentucky   \n",
       "..     ...                                                ...        ...   \n",
       "63   02302  Regional Planning Commission 5--Jefferson Pari...  Louisiana   \n",
       "64   02400  Regional Planning Commission 6--New Orleans Ci...  Louisiana   \n",
       "65   02401  Regional Planning Commission 7--New Orleans Ci...  Louisiana   \n",
       "66   02402  Regional Planning Commission 8--New Orleans Ci...  Louisiana   \n",
       "67   02500        Regional Planning Commission 9--St. Bernard  Louisiana   \n",
       "\n",
       "    health_insurance_coverage_rate  medicaid  \n",
       "0                         0.943543  0.262831  \n",
       "1                         0.935507  0.252209  \n",
       "2                         0.907533  0.278923  \n",
       "3                         0.932068  0.305751  \n",
       "4                         0.945148  0.232757  \n",
       "..                             ...       ...  \n",
       "63                        0.884315  0.337925  \n",
       "64                        0.915558  0.335580  \n",
       "65                        0.883772  0.361050  \n",
       "66                        0.921396  0.214011  \n",
       "67                        0.904672  0.295947  \n",
       "\n",
       "[68 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dictionary['insurance']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a51eef8",
   "metadata": {},
   "source": [
    "`cancer_infocus_download()` returns a dictionary object with pandas dataframe as values as well as the corresponding dataset names as keys. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d5250805",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['insurance', 'vacancy', 'poverty', 'transportation', 'employment', 'gini_index', 'rent_to_income', 'houses_before_1960', 'public_assistance', 'education', 'income', 'demographic_age', 'demographic_race'])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dictionary.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e37d0bf8",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>FIPS</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>Total</th>\n",
       "      <th>Under 18</th>\n",
       "      <th>18 to 64</th>\n",
       "      <th>Over 64</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11001</td>\n",
       "      <td>District of Columbia</td>\n",
       "      <td>District of Columbia</td>\n",
       "      <td>692683</td>\n",
       "      <td>0.178913</td>\n",
       "      <td>0.700296</td>\n",
       "      <td>0.120791</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "    FIPS                County                 State   Total  Under 18  \\\n",
       "0  11001  District of Columbia  District of Columbia  692683  0.178913   \n",
       "\n",
       "   18 to 64   Over 64  \n",
       "0  0.700296  0.120791  "
      ]
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     "execution_count": 6,
     "metadata": {},
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   "source": [
    "data_dictionary['demographic_age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "236becff",
   "metadata": {},
   "outputs": [
    {
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       "      <th>FIPS</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>no_vehicle</th>\n",
       "      <th>two_or_more_vehicle</th>\n",
       "      <th>three_or_more_vehicle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22001</td>\n",
       "      <td>Acadia Parish</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.012522</td>\n",
       "      <td>0.783917</td>\n",
       "      <td>0.345327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22003</td>\n",
       "      <td>Allen Parish</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.010760</td>\n",
       "      <td>0.783041</td>\n",
       "      <td>0.384327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22005</td>\n",
       "      <td>Ascension Parish</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.011004</td>\n",
       "      <td>0.837007</td>\n",
       "      <td>0.364278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>22007</td>\n",
       "      <td>Assumption Parish</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.024013</td>\n",
       "      <td>0.831469</td>\n",
       "      <td>0.397807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22009</td>\n",
       "      <td>Avoyelles Parish</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.023306</td>\n",
       "      <td>0.752653</td>\n",
       "      <td>0.318790</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    FIPS             County      State  no_vehicle  two_or_more_vehicle  \\\n",
       "0  22001      Acadia Parish  Louisiana    0.012522             0.783917   \n",
       "1  22003       Allen Parish  Louisiana    0.010760             0.783041   \n",
       "2  22005   Ascension Parish  Louisiana    0.011004             0.837007   \n",
       "3  22007  Assumption Parish  Louisiana    0.024013             0.831469   \n",
       "4  22009   Avoyelles Parish  Louisiana    0.023306             0.752653   \n",
       "\n",
       "   three_or_more_vehicle  \n",
       "0               0.345327  \n",
       "1               0.384327  \n",
       "2               0.364278  \n",
       "3               0.397807  \n",
       "4               0.318790  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dictionary['transportation'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3f035d3",
   "metadata": {},
   "source": [
    "### Query other dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4df5841e",
   "metadata": {},
   "source": [
    "To query other dataset, you may want to use `add_custom_table` function.   \n",
    "The function requires the following three arguments:\n",
    "* group_id: acs group id (e.g. B01001)\n",
    "    - you can provide multiple group ids in a list (e.g. \\[\"B01001\", \"C27007\"\\])\n",
    "    - However, all the acs groups must be in the same acs type\n",
    "* acs_type:\n",
    "    - '' : acs5\n",
    "    - 'profile' : acs5/profile\n",
    "    - 'subject' : acs5/subject\n",
    "    - for more information, please visit: https://api.census.gov/data.html\n",
    "* name: it will be a dictionary key for the dataset in the data_dictionary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3771ff0d",
   "metadata": {},
   "source": [
    "Using the decorator of the `add_custom_table` you define how the dataframe to be organized since it is downloaded from the census.   \n",
    "In the following example, the function does not change any from the raw data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c346a51b",
   "metadata": {},
   "outputs": [],
   "source": [
    "sdoh.clean_functions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d7d18042",
   "metadata": {},
   "outputs": [],
   "source": [
    "@sdoh.add_custom_table([\"C27007\", \"B27001\"], '', 'sample')\n",
    "def download_custom_data(df):\n",
    "    df = df.drop('B27001_001E', axis = 1)\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "baac2869",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dictionary = sdoh.download_all()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a49bb7ce",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>PUMA_ID</th>\n",
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       "      <th>State</th>\n",
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       "      <th>C27007_012E</th>\n",
       "      <th>C27007_013E</th>\n",
       "      <th>C27007_014E</th>\n",
       "      <th>C27007_015E</th>\n",
       "      <th>C27007_016E</th>\n",
       "      <th>C27007_017E</th>\n",
       "      <th>C27007_018E</th>\n",
       "      <th>C27007_019E</th>\n",
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       "      <th>C27007_021E</th>\n",
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       "      <th>0</th>\n",
       "      <td>00100</td>\n",
       "      <td>Purchase Area Development District PUMA</td>\n",
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       "      <td>6903</td>\n",
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       "      <td>56986</td>\n",
       "      <td>14467</td>\n",
       "      <td>42519</td>\n",
       "      <td>20350</td>\n",
       "      <td>2628</td>\n",
       "      <td>17722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00200</td>\n",
       "      <td>Pennyrile Area Development District (North) PUMA</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>51371</td>\n",
       "      <td>3861</td>\n",
       "      <td>3710</td>\n",
       "      <td>151</td>\n",
       "      <td>9114</td>\n",
       "      <td>8597</td>\n",
       "      <td>517</td>\n",
       "      <td>...</td>\n",
       "      <td>53772</td>\n",
       "      <td>11679</td>\n",
       "      <td>4807</td>\n",
       "      <td>6872</td>\n",
       "      <td>31239</td>\n",
       "      <td>7741</td>\n",
       "      <td>23498</td>\n",
       "      <td>10854</td>\n",
       "      <td>1734</td>\n",
       "      <td>9120</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00300</td>\n",
       "      <td>Pennyrile Area Development District (South) PUMA</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>45788</td>\n",
       "      <td>5549</td>\n",
       "      <td>5071</td>\n",
       "      <td>478</td>\n",
       "      <td>8901</td>\n",
       "      <td>8031</td>\n",
       "      <td>870</td>\n",
       "      <td>...</td>\n",
       "      <td>49446</td>\n",
       "      <td>13660</td>\n",
       "      <td>5377</td>\n",
       "      <td>8283</td>\n",
       "      <td>27462</td>\n",
       "      <td>7831</td>\n",
       "      <td>19631</td>\n",
       "      <td>8324</td>\n",
       "      <td>1391</td>\n",
       "      <td>6933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00400</td>\n",
       "      <td>Barren River Area Development District (Outer)...</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>84472</td>\n",
       "      <td>7113</td>\n",
       "      <td>6462</td>\n",
       "      <td>651</td>\n",
       "      <td>15031</td>\n",
       "      <td>13956</td>\n",
       "      <td>1075</td>\n",
       "      <td>...</td>\n",
       "      <td>87318</td>\n",
       "      <td>20653</td>\n",
       "      <td>10566</td>\n",
       "      <td>10087</td>\n",
       "      <td>50366</td>\n",
       "      <td>14442</td>\n",
       "      <td>35924</td>\n",
       "      <td>16299</td>\n",
       "      <td>2755</td>\n",
       "      <td>13544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00500</td>\n",
       "      <td>Barren River Area Development District (Centra...</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>62187</td>\n",
       "      <td>4760</td>\n",
       "      <td>4707</td>\n",
       "      <td>53</td>\n",
       "      <td>11248</td>\n",
       "      <td>11052</td>\n",
       "      <td>196</td>\n",
       "      <td>...</td>\n",
       "      <td>65156</td>\n",
       "      <td>16490</td>\n",
       "      <td>7028</td>\n",
       "      <td>9462</td>\n",
       "      <td>40011</td>\n",
       "      <td>8583</td>\n",
       "      <td>31428</td>\n",
       "      <td>8655</td>\n",
       "      <td>1227</td>\n",
       "      <td>7428</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  PUMA_ID                                          PUMA_NAME     State   \n",
       "0   00100            Purchase Area Development District PUMA  Kentucky  \\\n",
       "1   00200   Pennyrile Area Development District (North) PUMA  Kentucky   \n",
       "2   00300   Pennyrile Area Development District (South) PUMA  Kentucky   \n",
       "3   00400  Barren River Area Development District (Outer)...  Kentucky   \n",
       "4   00500  Barren River Area Development District (Centra...  Kentucky   \n",
       "\n",
       "  B27001_002E B27001_003E B27001_004E B27001_005E B27001_006E B27001_007E   \n",
       "0       93397        6903        6725         178       16009       15233  \\\n",
       "1       51371        3861        3710         151        9114        8597   \n",
       "2       45788        5549        5071         478        8901        8031   \n",
       "3       84472        7113        6462         651       15031       13956   \n",
       "4       62187        4760        4707          53       11248       11052   \n",
       "\n",
       "  B27001_008E  ... C27007_012E C27007_013E C27007_014E C27007_015E   \n",
       "0         776  ...       99244       21908        9617       12291  \\\n",
       "1         517  ...       53772       11679        4807        6872   \n",
       "2         870  ...       49446       13660        5377        8283   \n",
       "3        1075  ...       87318       20653       10566       10087   \n",
       "4         196  ...       65156       16490        7028        9462   \n",
       "\n",
       "  C27007_016E C27007_017E C27007_018E C27007_019E C27007_020E C27007_021E  \n",
       "0       56986       14467       42519       20350        2628       17722  \n",
       "1       31239        7741       23498       10854        1734        9120  \n",
       "2       27462        7831       19631        8324        1391        6933  \n",
       "3       50366       14442       35924       16299        2755       13544  \n",
       "4       40011        8583       31428        8655        1227        7428  \n",
       "\n",
       "[5 rows x 80 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dictionary['sample'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ed83d58e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['C27007', 'B27001']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdoh.config.acs_group"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bac6845d",
   "metadata": {},
   "source": [
    "### ACSConfig"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f2045311",
   "metadata": {},
   "source": [
    "When exploring an acs group, you may use `ACSConfig`.\n",
    "`ACSConfig` requires following arguements:\n",
    "* year : str or int\n",
    "* state_fips : a list of state fips or a single state fips as str\n",
    "* query_level: str\n",
    "* acs_group  : str or List[str]\n",
    "* acs_type   : str (optional)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d410310e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIF_Config import ACSConfig\n",
    "from pprint import pprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "89e7144a",
   "metadata": {},
   "outputs": [],
   "source": [
    "cfg = ACSConfig(2020, 21, 'tract', ['B15003', 'B27001'], acs_type = '')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d99d185d",
   "metadata": {},
   "source": [
    "ACSConfig can provide both variables within the group and their labels.   \n",
    "In addition, it also provides a table explaining details of each variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "47226b79",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['B15003', 'B27001']\n"
     ]
    }
   ],
   "source": [
    "print(cfg.acs_group)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c3a2faf5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['B15003_001E', 'B15003_002E', 'B15003_003E', 'B15003_004E', 'B15003_005E', 'B15003_006E', 'B15003_007E', 'B15003_008E', 'B15003_009E', 'B15003_010E', 'B15003_011E', 'B15003_012E', 'B15003_013E', 'B15003_014E', 'B15003_015E', 'B15003_016E', 'B15003_017E', 'B15003_018E', 'B15003_019E', 'B15003_020E', 'B15003_021E', 'B15003_022E', 'B15003_023E', 'B15003_024E', 'B15003_025E', 'B27001_001E', 'B27001_002E', 'B27001_003E', 'B27001_004E', 'B27001_005E', 'B27001_006E', 'B27001_007E', 'B27001_008E', 'B27001_009E', 'B27001_010E', 'B27001_011E', 'B27001_012E', 'B27001_013E', 'B27001_014E', 'B27001_015E', 'B27001_016E', 'B27001_017E', 'B27001_018E', 'B27001_019E', 'B27001_020E', 'B27001_021E', 'B27001_022E', 'B27001_023E', 'B27001_024E', 'B27001_025E', 'B27001_026E', 'B27001_027E', 'B27001_028E', 'B27001_029E', 'B27001_030E', 'B27001_031E', 'B27001_032E', 'B27001_033E', 'B27001_034E', 'B27001_035E', 'B27001_036E', 'B27001_037E', 'B27001_038E', 'B27001_039E', 'B27001_040E', 'B27001_041E', 'B27001_042E', 'B27001_043E', 'B27001_044E', 'B27001_045E', 'B27001_046E', 'B27001_047E', 'B27001_048E', 'B27001_049E', 'B27001_050E', 'B27001_051E', 'B27001_052E', 'B27001_053E', 'B27001_054E', 'B27001_055E', 'B27001_056E', 'B27001_057E']\n"
     ]
    }
   ],
   "source": [
    "print(cfg.variables)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ee3b69a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Total', 'No schooling completed', 'Nursery school', 'Kindergarten', '1st grade', '2nd grade', '3rd grade', '4th grade', '5th grade', '6th grade', '7th grade', '8th grade', '9th grade', '10th grade', '11th grade', '12th grade, no diploma', 'Regular high school diploma', 'GED or alternative credential', 'Some college, less than 1 year', 'Some college, 1 or more years, no degree', \"Associate's degree\", \"Bachelor's degree\", \"Master's degree\", 'Professional school degree', 'Doctorate degree', 'Total', 'Male', 'Total - Male - Under 6 years', 'Total - Male - Under 6 years - With health insurance coverage', 'Total - Male - Under 6 years - No health insurance coverage', 'Total - Male - 6 to 18 years', 'Total - Male - 6 to 18 years - With health insurance coverage', 'Total - Male - 6 to 18 years - No health insurance coverage', 'Total - Male - 19 to 25 years', 'Total - Male - 19 to 25 years - With health insurance coverage', 'Total - Male - 19 to 25 years - No health insurance coverage', 'Total - Male - 26 to 34 years', 'Total - Male - 26 to 34 years - With health insurance coverage', 'Total - Male - 26 to 34 years - No health insurance coverage', 'Total - Male - 35 to 44 years', 'Total - Male - 35 to 44 years - With health insurance coverage', 'Total - Male - 35 to 44 years - No health insurance coverage', 'Total - Male - 45 to 54 years', 'Total - Male - 45 to 54 years - With health insurance coverage', 'Total - Male - 45 to 54 years - No health insurance coverage', 'Total - Male - 55 to 64 years', 'Total - Male - 55 to 64 years - With health insurance coverage', 'Total - Male - 55 to 64 years - No health insurance coverage', 'Total - Male - 65 to 74 years', 'Total - Male - 65 to 74 years - With health insurance coverage', 'Total - Male - 65 to 74 years - No health insurance coverage', 'Total - Male - 75 years and over', 'Total - Male - 75 years and over - With health insurance coverage', 'Total - Male - 75 years and over - No health insurance coverage', 'Female', 'Total - Female - Under 6 years', 'Total - Female - Under 6 years - With health insurance coverage', 'Total - Female - Under 6 years - No health insurance coverage', 'Total - Female - 6 to 18 years', 'Total - Female - 6 to 18 years - With health insurance coverage', 'Total - Female - 6 to 18 years - No health insurance coverage', 'Total - Female - 19 to 25 years', 'Total - Female - 19 to 25 years - With health insurance coverage', 'Total - Female - 19 to 25 years - No health insurance coverage', 'Total - Female - 26 to 34 years', 'Total - Female - 26 to 34 years - With health insurance coverage', 'Total - Female - 26 to 34 years - No health insurance coverage', 'Total - Female - 35 to 44 years', 'Total - Female - 35 to 44 years - With health insurance coverage', 'Total - Female - 35 to 44 years - No health insurance coverage', 'Total - Female - 45 to 54 years', 'Total - Female - 45 to 54 years - With health insurance coverage', 'Total - Female - 45 to 54 years - No health insurance coverage', 'Total - Female - 55 to 64 years', 'Total - Female - 55 to 64 years - With health insurance coverage', 'Total - Female - 55 to 64 years - No health insurance coverage', 'Total - Female - 65 to 74 years', 'Total - Female - 65 to 74 years - With health insurance coverage', 'Total - Female - 65 to 74 years - No health insurance coverage', 'Total - Female - 75 years and over', 'Total - Female - 75 years and over - With health insurance coverage', 'Total - Female - 75 years and over - No health insurance coverage']\n"
     ]
    }
   ],
   "source": [
    "print(cfg.labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f5fc649a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>label</th>\n",
       "      <th>concept</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B27001_031E</td>\n",
       "      <td>Estimate!!Total:!!Female:!!Under 6 years:</td>\n",
       "      <td>HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B27001_032E</td>\n",
       "      <td>Estimate!!Total:!!Female:!!Under 6 years:!!Wit...</td>\n",
       "      <td>HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B27001_030E</td>\n",
       "      <td>Estimate!!Total:!!Female:</td>\n",
       "      <td>HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B27001_023E</td>\n",
       "      <td>Estimate!!Total:!!Male:!!55 to 64 years:!!No h...</td>\n",
       "      <td>HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B27001_024E</td>\n",
       "      <td>Estimate!!Total:!!Male:!!65 to 74 years:</td>\n",
       "      <td>HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>B15003_010E</td>\n",
       "      <td>Estimate!!Total:!!6th grade</td>\n",
       "      <td>EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>B15003_018E</td>\n",
       "      <td>Estimate!!Total:!!GED or alternative credential</td>\n",
       "      <td>EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>B15003_019E</td>\n",
       "      <td>Estimate!!Total:!!Some college, less than 1 year</td>\n",
       "      <td>EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>B15003_017E</td>\n",
       "      <td>Estimate!!Total:!!Regular high school diploma</td>\n",
       "      <td>EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>B15003_016E</td>\n",
       "      <td>Estimate!!Total:!!12th grade, no diploma</td>\n",
       "      <td>EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           name                                              label   \n",
       "0   B27001_031E          Estimate!!Total:!!Female:!!Under 6 years:  \\\n",
       "1   B27001_032E  Estimate!!Total:!!Female:!!Under 6 years:!!Wit...   \n",
       "2   B27001_030E                          Estimate!!Total:!!Female:   \n",
       "3   B27001_023E  Estimate!!Total:!!Male:!!55 to 64 years:!!No h...   \n",
       "4   B27001_024E           Estimate!!Total:!!Male:!!65 to 74 years:   \n",
       "..          ...                                                ...   \n",
       "77  B15003_010E                        Estimate!!Total:!!6th grade   \n",
       "78  B15003_018E    Estimate!!Total:!!GED or alternative credential   \n",
       "79  B15003_019E   Estimate!!Total:!!Some college, less than 1 year   \n",
       "80  B15003_017E      Estimate!!Total:!!Regular high school diploma   \n",
       "81  B15003_016E           Estimate!!Total:!!12th grade, no diploma   \n",
       "\n",
       "                                              concept  \n",
       "0      HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE  \n",
       "1      HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE  \n",
       "2      HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE  \n",
       "3      HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE  \n",
       "4      HEALTH INSURANCE COVERAGE STATUS BY SEX BY AGE  \n",
       "..                                                ...  \n",
       "77  EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...  \n",
       "78  EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...  \n",
       "79  EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...  \n",
       "80  EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...  \n",
       "81  EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 Y...  \n",
       "\n",
       "[82 rows x 3 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cfg.var_desc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5e45710",
   "metadata": {},
   "source": [
    "## Downloading facility data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aae9fd3e",
   "metadata": {},
   "source": [
    "To download facility data, you simply need to use `gen_facility_data` function.   \n",
    "The fuction requires only one arguement:\n",
    "* location : str or List\\[str\\] (abbreviation(s) of state name(s))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cec55a9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIFTools import gen_facility_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "df9052af",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Process is complete\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "downloading fqhc data file: 100%|██████████| 12.4M/12.4M [00:00<00:00, 16.3MiB/s]\n",
      "downloading hpsa data file: 100%|██████████| 15.6M/15.6M [00:00<00:00, 17.7MiB/s]\n",
      "downloading lcs data file: 100%|██████████| 343k/343k [00:00<00:00, 431kiB/s]MiB/s]\n",
      "downloading toxRel data file: 100%|██████████| 73.0M/73.0M [00:02<00:00, 35.7MiB/s]\n"
     ]
    }
   ],
   "source": [
    "facility_data = gen_facility_data(['KY','WV'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5eeee0bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['nppes', 'mammography', 'hpsa', 'fqhc', 'lung_cancer_screening', 'tri_facility', 'superfund_site'])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "facility_data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f5a5b780",
   "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>Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Address</th>\n",
       "      <th>State</th>\n",
       "      <th>Phone_number</th>\n",
       "      <th>Notes</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HPSA Correctional Facility</td>\n",
       "      <td>FCC - Hazelton</td>\n",
       "      <td>1640 Skyview Ln, Bruceton Mills, WV 26525</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>39.671864</td>\n",
       "      <td>-79.499303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>FAMILY HEALTHCARE ASSOCIATES</td>\n",
       "      <td>114 Main St, Man, WV 25635</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>37.743543</td>\n",
       "      <td>-81.874243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>BOONE MEMORIAL HOSPITAL FAMILY MEDICAL CENTER</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>38.048889</td>\n",
       "      <td>-81.806171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>ST MARYS EXPRESS CARE</td>\n",
       "      <td>201 2nd St, Saint Marys, WV 26170</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>39.389380</td>\n",
       "      <td>-81.207532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>FAMILY HEALTHCARE ASSOCIATES</td>\n",
       "      <td>205 Howard Ave, Mullens, WV 25882</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>37.583248</td>\n",
       "      <td>-81.381166</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>101</th>\n",
       "      <td>HPSA Federally Qualified Health Center Look A ...</td>\n",
       "      <td>Faith Healthcare, Inc</td>\n",
       "      <td>126 Franklin Rd, Monticello, KY 42633</td>\n",
       "      <td>KY</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>36.866140</td>\n",
       "      <td>-84.827390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>PHYSICIAN SERVICES OF MEMORIAL HOSPITAL</td>\n",
       "      <td>94 Marie Langdon Dr STE 4, Manchester, KY 40962</td>\n",
       "      <td>KY</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>37.162858</td>\n",
       "      <td>-83.760707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>FAMILY HEALTHCARE ASSOCIATES 7, LLC</td>\n",
       "      <td>422 N Highway 27, Whitley City, KY 42653</td>\n",
       "      <td>KY</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>36.817664</td>\n",
       "      <td>-84.486655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>FAMILY HEALTHCARE ASSOCIATES 8, LLC</td>\n",
       "      <td>305 Danville Ave, Stanford, KY 40484</td>\n",
       "      <td>KY</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>37.531983</td>\n",
       "      <td>-84.668236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>HPSA Rural Health Clinic</td>\n",
       "      <td>CUMBERLAND FAMILY CLINIC, PLLC</td>\n",
       "      <td>57 Hogue Rd, Pine Knot, KY 42635</td>\n",
       "      <td>KY</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>36.665255</td>\n",
       "      <td>-84.441750</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>106 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Type  \\\n",
       "0                           HPSA Correctional Facility   \n",
       "1                             HPSA Rural Health Clinic   \n",
       "2                             HPSA Rural Health Clinic   \n",
       "3                             HPSA Rural Health Clinic   \n",
       "4                             HPSA Rural Health Clinic   \n",
       "..                                                 ...   \n",
       "101  HPSA Federally Qualified Health Center Look A ...   \n",
       "102                           HPSA Rural Health Clinic   \n",
       "103                           HPSA Rural Health Clinic   \n",
       "104                           HPSA Rural Health Clinic   \n",
       "105                           HPSA Rural Health Clinic   \n",
       "\n",
       "                                              Name  \\\n",
       "0                                   FCC - Hazelton   \n",
       "1                     FAMILY HEALTHCARE ASSOCIATES   \n",
       "2    BOONE MEMORIAL HOSPITAL FAMILY MEDICAL CENTER   \n",
       "3                            ST MARYS EXPRESS CARE   \n",
       "4                     FAMILY HEALTHCARE ASSOCIATES   \n",
       "..                                             ...   \n",
       "101                          Faith Healthcare, Inc   \n",
       "102        PHYSICIAN SERVICES OF MEMORIAL HOSPITAL   \n",
       "103            FAMILY HEALTHCARE ASSOCIATES 7, LLC   \n",
       "104            FAMILY HEALTHCARE ASSOCIATES 8, LLC   \n",
       "105                 CUMBERLAND FAMILY CLINIC, PLLC   \n",
       "\n",
       "                                             Address State Phone_number Notes  \\\n",
       "0          1640 Skyview Ln, Bruceton Mills, WV 26525    WV         None         \n",
       "1                         114 Main St, Man, WV 25635    WV         None         \n",
       "2                                                NaN    WV         None         \n",
       "3                  201 2nd St, Saint Marys, WV 26170    WV         None         \n",
       "4                  205 Howard Ave, Mullens, WV 25882    WV         None         \n",
       "..                                               ...   ...          ...   ...   \n",
       "101            126 Franklin Rd, Monticello, KY 42633    KY         None         \n",
       "102  94 Marie Langdon Dr STE 4, Manchester, KY 40962    KY         None         \n",
       "103         422 N Highway 27, Whitley City, KY 42653    KY         None         \n",
       "104             305 Danville Ave, Stanford, KY 40484    KY         None         \n",
       "105                 57 Hogue Rd, Pine Knot, KY 42635    KY         None         \n",
       "\n",
       "      latitude  longitude  \n",
       "0    39.671864 -79.499303  \n",
       "1    37.743543 -81.874243  \n",
       "2    38.048889 -81.806171  \n",
       "3    39.389380 -81.207532  \n",
       "4    37.583248 -81.381166  \n",
       "..         ...        ...  \n",
       "101  36.866140 -84.827390  \n",
       "102  37.162858 -83.760707  \n",
       "103  36.817664 -84.486655  \n",
       "104  37.531983 -84.668236  \n",
       "105  36.665255 -84.441750  \n",
       "\n",
       "[106 rows x 8 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "facility_data['hpsa']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d2da59b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "all_facility = pd.concat(facility_data.values(), axis = 0).reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9f19bb60",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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>Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Address</th>\n",
       "      <th>State</th>\n",
       "      <th>Phone_number</th>\n",
       "      <th>Notes</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>FIPS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>Marilyn Moaga</td>\n",
       "      <td>2513 Sun Seeker Ct, Lexington, KY 40503</td>\n",
       "      <td>KY</td>\n",
       "      <td>859-523-4442</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>Jeannine M Keeler RN</td>\n",
       "      <td>650 Joel Dr, Fort Campbell, KY 42223</td>\n",
       "      <td>KY</td>\n",
       "      <td>270-956-0297</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>Samantha Bridges R.N. BSN</td>\n",
       "      <td>650 Joel Dr, Fort Campbell, KY 42223</td>\n",
       "      <td>KY</td>\n",
       "      <td>270-956-0489</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>Molly E Whitledge RN</td>\n",
       "      <td>650 Joel Dr, Fort Campbell, KY 42223</td>\n",
       "      <td>KY</td>\n",
       "      <td>270-798-8422</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>Carole P Whitledge APRN</td>\n",
       "      <td>800 Zorn Ave, Louisville, KY 40206</td>\n",
       "      <td>KY</td>\n",
       "      <td>502-287-5894</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3819</th>\n",
       "      <td>Superfund Site</td>\n",
       "      <td>WEST VIRGINIA ORDNANCE (USARMY)</td>\n",
       "      <td>ROUTE 1 BOX 125, POINT PLEASANT, WV 25550</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td>Currently on the Final NPL</td>\n",
       "      <td>38.926389</td>\n",
       "      <td>-82.076389</td>\n",
       "      <td>54053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3820</th>\n",
       "      <td>Superfund Site</td>\n",
       "      <td>SHAFFER EQUIPMENT/ARBUCKLE CREEK AREA</td>\n",
       "      <td>WV ROUTE 17 (A.K.A. MINDEN ROAD), MINDEN, WV 2...</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td>Currently on the Final NPL</td>\n",
       "      <td>37.97651</td>\n",
       "      <td>-81.1265</td>\n",
       "      <td>54019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3821</th>\n",
       "      <td>Superfund Site</td>\n",
       "      <td>VIENNA TETRACHLOROETHENE</td>\n",
       "      <td>30TH STREET, GRAND CENTRAL AVE, VIENNA, WV 26105</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td>Currently on the Final NPL</td>\n",
       "      <td>39.325167</td>\n",
       "      <td>-81.548778</td>\n",
       "      <td>54107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3822</th>\n",
       "      <td>Superfund Site</td>\n",
       "      <td>NORTH 25TH STREET GLASS AND ZINC</td>\n",
       "      <td>N. 25TH STREET, CLARKSBURG, WV 26301</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td>Currently on the Final NPL</td>\n",
       "      <td>39.297053</td>\n",
       "      <td>-80.357433</td>\n",
       "      <td>54033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3823</th>\n",
       "      <td>Superfund Site</td>\n",
       "      <td>RAVENSWOOD PCE</td>\n",
       "      <td>212 WALNUT STREET APPROX., RAVENSWOOD, WV 26164</td>\n",
       "      <td>WV</td>\n",
       "      <td>None</td>\n",
       "      <td>Currently on the Final NPL</td>\n",
       "      <td>38.951667</td>\n",
       "      <td>-81.761667</td>\n",
       "      <td>54035</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3824 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Type                                   Name  \\\n",
       "0     Gastroenterology                          Marilyn Moaga   \n",
       "1     Gastroenterology                   Jeannine M Keeler RN   \n",
       "2     Gastroenterology              Samantha Bridges R.N. BSN   \n",
       "3     Gastroenterology                   Molly E Whitledge RN   \n",
       "4     Gastroenterology                Carole P Whitledge APRN   \n",
       "...                ...                                    ...   \n",
       "3819    Superfund Site        WEST VIRGINIA ORDNANCE (USARMY)   \n",
       "3820    Superfund Site  SHAFFER EQUIPMENT/ARBUCKLE CREEK AREA   \n",
       "3821    Superfund Site               VIENNA TETRACHLOROETHENE   \n",
       "3822    Superfund Site       NORTH 25TH STREET GLASS AND ZINC   \n",
       "3823    Superfund Site                         RAVENSWOOD PCE   \n",
       "\n",
       "                                                Address State  Phone_number  \\\n",
       "0               2513 Sun Seeker Ct, Lexington, KY 40503    KY  859-523-4442   \n",
       "1                  650 Joel Dr, Fort Campbell, KY 42223    KY  270-956-0297   \n",
       "2                  650 Joel Dr, Fort Campbell, KY 42223    KY  270-956-0489   \n",
       "3                  650 Joel Dr, Fort Campbell, KY 42223    KY  270-798-8422   \n",
       "4                    800 Zorn Ave, Louisville, KY 40206    KY  502-287-5894   \n",
       "...                                                 ...   ...           ...   \n",
       "3819          ROUTE 1 BOX 125, POINT PLEASANT, WV 25550    WV          None   \n",
       "3820  WV ROUTE 17 (A.K.A. MINDEN ROAD), MINDEN, WV 2...    WV          None   \n",
       "3821   30TH STREET, GRAND CENTRAL AVE, VIENNA, WV 26105    WV          None   \n",
       "3822               N. 25TH STREET, CLARKSBURG, WV 26301    WV          None   \n",
       "3823    212 WALNUT STREET APPROX., RAVENSWOOD, WV 26164    WV          None   \n",
       "\n",
       "                           Notes   latitude  longitude   FIPS  \n",
       "0                                       NaN        NaN    NaN  \n",
       "1                                       NaN        NaN    NaN  \n",
       "2                                       NaN        NaN    NaN  \n",
       "3                                       NaN        NaN    NaN  \n",
       "4                                       NaN        NaN    NaN  \n",
       "...                          ...        ...        ...    ...  \n",
       "3819  Currently on the Final NPL  38.926389 -82.076389  54053  \n",
       "3820  Currently on the Final NPL   37.97651   -81.1265  54019  \n",
       "3821  Currently on the Final NPL  39.325167 -81.548778  54107  \n",
       "3822  Currently on the Final NPL  39.297053 -80.357433  54033  \n",
       "3823  Currently on the Final NPL  38.951667 -81.761667  54035  \n",
       "\n",
       "[3824 rows x 9 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_facility"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84349d9c",
   "metadata": {},
   "source": [
    "## Downloading Cancer Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "274b1cfa",
   "metadata": {},
   "source": [
    "Cancer statistics are queries from https://www.statecancerprofiles.cancer.gov/   \n",
    "To query cancer statistics, you first need to define `scp_cancer_data` with *state_fips* arguments.   \n",
    "*state_fips* can be single state fips code in string format or a list of state fips code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d303aca9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIFTools import scp_cancer_data\n",
    "cancer = scp_cancer_data(['01','02'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "862b8602",
   "metadata": {},
   "source": [
    "Then you can query data and retrieve it from `cancer_data` attribute, which is in a dictionary format with each value is a pandas DataFrame for incidence or mortality data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1e21da6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>Type</th>\n",
       "      <th>Site</th>\n",
       "      <th>AAR</th>\n",
       "      <th>AAC</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01000</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>All Site</td>\n",
       "      <td>451.7</td>\n",
       "      <td>27407.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01000</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Bladder</td>\n",
       "      <td>17.7</td>\n",
       "      <td>1092.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01000</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Brain &amp; ONS</td>\n",
       "      <td>6.4</td>\n",
       "      <td>360.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01000</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Cervix</td>\n",
       "      <td>9.5</td>\n",
       "      <td>241.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01000</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Colon &amp; Rectum</td>\n",
       "      <td>42.4</td>\n",
       "      <td>2533.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1355</th>\n",
       "      <td>01133</td>\n",
       "      <td>Winston County</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Ovary</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1356</th>\n",
       "      <td>01133</td>\n",
       "      <td>Winston County</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Pancreas</td>\n",
       "      <td>15.3</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1357</th>\n",
       "      <td>01133</td>\n",
       "      <td>Winston County</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Prostate</td>\n",
       "      <td>104.7</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1358</th>\n",
       "      <td>01133</td>\n",
       "      <td>Winston County</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Stomach</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>01133</td>\n",
       "      <td>Winston County</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Incidence</td>\n",
       "      <td>Thyroid</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1360 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       FIPS          County    State       Type            Site    AAR  \\\n",
       "0     01000         Alabama  Alabama  Incidence        All Site  451.7   \n",
       "1     01000         Alabama  Alabama  Incidence         Bladder   17.7   \n",
       "2     01000         Alabama  Alabama  Incidence     Brain & ONS    6.4   \n",
       "3     01000         Alabama  Alabama  Incidence          Cervix    9.5   \n",
       "4     01000         Alabama  Alabama  Incidence  Colon & Rectum   42.4   \n",
       "...     ...             ...      ...        ...             ...    ...   \n",
       "1355  01133  Winston County  Alabama  Incidence           Ovary    NaN   \n",
       "1356  01133  Winston County  Alabama  Incidence        Pancreas   15.3   \n",
       "1357  01133  Winston County  Alabama  Incidence        Prostate  104.7   \n",
       "1358  01133  Winston County  Alabama  Incidence         Stomach    NaN   \n",
       "1359  01133  Winston County  Alabama  Incidence         Thyroid    NaN   \n",
       "\n",
       "          AAC  \n",
       "0     27407.0  \n",
       "1      1092.0  \n",
       "2       360.0  \n",
       "3       241.0  \n",
       "4      2533.0  \n",
       "...       ...  \n",
       "1355      NaN  \n",
       "1356      6.0  \n",
       "1357     20.0  \n",
       "1358      NaN  \n",
       "1359      NaN  \n",
       "\n",
       "[1360 rows x 7 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cancer.cancer_data['incidence']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c6f6865",
   "metadata": {},
   "source": [
    "## Risk Behavior and Screening Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0973eb4",
   "metadata": {},
   "source": [
    "CDC risk behavior and screening data is querried using Socrata API.   \n",
    "You then need the followings:\n",
    "* domain : str =  \"chronicdata.cdc.gov\"\n",
    "* app_token : str = \"nx4zQ2205wpLwaaaZeZp9zAOs\"\n",
    "* user_name : str\n",
    "* password : str   \n",
    "\n",
    "Then first define a SocrataConfig config object with the arguments above.   \n",
    "It is okay to not have *user_name* and *password*, but it may cause a slow download of datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6e27ed18",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIF_Config import SocrataConfig\n",
    "\n",
    "kwargs = {\"domain\": \"chronicdata.cdc.gov\",\n",
    "      \"app_token\": \"nx4zQ2205wpLwaaaZeZp9zAOs\"}\n",
    "\n",
    "cfg = SocrataConfig(**kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b322a57",
   "metadata": {},
   "source": [
    "Then we provide the config object as well as state_fips (str or List\\[str\\]) to `places_data`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2de8f055",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIFTools import places_data\n",
    "cdc = places_data(['21','22'], cfg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e46fb10",
   "metadata": {},
   "source": [
    "Then you can retrieve county-level and tract-level data from the `places_data` attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "27fd968d",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'county':       FIPS         County      State Cancer_Prevalence Met_Cervical_Screen  \\\n",
       " 0    21085        Grayson   Kentucky               7.5                78.3   \n",
       " 1    21061       Edmonson   Kentucky               7.8                79.3   \n",
       " 2    21223        Trimble   Kentucky               7.6                80.1   \n",
       " 3    21075         Fulton   Kentucky               7.7                79.0   \n",
       " 4    21179         Nelson   Kentucky               7.1                82.3   \n",
       " ..     ...            ...        ...               ...                 ...   \n",
       " 179  22117     Washington  Louisiana               7.2                79.8   \n",
       " 180  22103    St. Tammany  Louisiana               7.4                83.8   \n",
       " 181  22031        De Soto  Louisiana               7.1                81.1   \n",
       " 182  22077  Pointe Coupee  Louisiana               7.7                80.1   \n",
       " 183  22013      Bienville  Louisiana               7.7                79.9   \n",
       " \n",
       "     Met_Colon_Screen Currently_Smoke Met_Breast_Screen BMI_Obese  \n",
       " 0               70.9            27.1              64.3      41.5  \n",
       " 1               72.0            25.5              64.7      40.7  \n",
       " 2               71.3            23.6              67.3      38.7  \n",
       " 3               72.3            26.4              67.8      42.3  \n",
       " 4               75.3            19.5              70.0      37.9  \n",
       " ..               ...             ...               ...       ...  \n",
       " 179             69.7            24.3              73.6      43.8  \n",
       " 180             75.7            16.7              78.9      31.3  \n",
       " 181             71.1            22.6              74.9      42.6  \n",
       " 182             70.5            21.5              73.1      40.6  \n",
       " 183             68.6            24.6              75.1      43.9  \n",
       " \n",
       " [184 rows x 9 columns],\n",
       " 'tract':      State            County  FIPS5         FIPS Cancer_Prevalence  \\\n",
       " 0       KY             Clark  21049  21049020500               7.3   \n",
       " 1       KY         Henderson  21101  21101020500               6.7   \n",
       " 2       KY        Montgomery  21173  21173920100               6.3   \n",
       " 3       KY         Jefferson  21111  21111011106               6.3   \n",
       " 4       KY            Warren  21227  21227011002               3.4   \n",
       " ...    ...               ...    ...          ...               ...   \n",
       " 2225    LA        St. Landry  22097  22097960400               6.8   \n",
       " 2226    LA         Jefferson  22051  22051020512               8.1   \n",
       " 2227    LA           Orleans  22071  22071001701               7.4   \n",
       " 2228    LA  West Baton Rouge  22121  22121020402               5.4   \n",
       " 2229    LA            Iberia  22045  22045030100               6.2   \n",
       " \n",
       "      Met_Colon_Screen Currently_Smoke Met_Breast_Screen BMI_Obese  \n",
       " 0                76.1            18.1              76.2      33.3  \n",
       " 1                70.5            24.2              73.2      42.1  \n",
       " 2                72.8            22.3              72.5      37.5  \n",
       " 3                74.1            19.6              75.4      35.7  \n",
       " 4                67.8            24.0              76.1      38.8  \n",
       " ...               ...             ...               ...       ...  \n",
       " 2225             64.0            29.6              75.0      35.3  \n",
       " 2226             71.5            12.8              82.8      32.8  \n",
       " 2227             72.1            17.7              84.7      36.6  \n",
       " 2228             73.1            16.8              78.6      33.3  \n",
       " 2229             69.9            23.2              80.2      38.5  \n",
       " \n",
       " [2230 rows x 9 columns]}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdc.places_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d643765",
   "metadata": {},
   "source": [
    "## Downloading Food Desert Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33a8706a",
   "metadata": {},
   "source": [
    "The food desert data is downloaded from the FDA: https://www.ers.usda.gov/data-products/food-access-research-atlas/download-the-data/   \n",
    "Similar to `scp_cancer_data`, you first need to provide `food_desert` a state fips code or a list of state fips code if you have more than one state of interest.   \n",
    "Another argument that `food_desert` requires is *var_name*. As default, the variable used in **Cancer InFocus** is **LILATracts_Vehicle** but if you have a different variable of your interest, you can provide the variable name. You can find variables from the link provided in the beginning. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ecc5c257",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIFTools import food_desert\n",
    "fd = food_desert(['21','22'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75612f0c",
   "metadata": {},
   "source": [
    "You can query and view the food desert data from the `food_desert_data` attribute. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cae9dbad",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "downloading food desert data file: 100%|██| 81.8M/81.8M [00:02<00:00, 35.8MiB/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'Tract':               FIPS  LILATracts_Vehicle\n",
       " 0       1001020100                   0\n",
       " 1       1001020200                   0\n",
       " 2       1001020300                   0\n",
       " 3       1001020400                   0\n",
       " 4       1001020500                   0\n",
       " ...            ...                 ...\n",
       " 62432  56043000200                   0\n",
       " 62433  56043000301                   0\n",
       " 62434  56043000302                   0\n",
       " 62435  56045951100                   0\n",
       " 62436  56045951300                   0\n",
       " \n",
       " [62437 rows x 2 columns],\n",
       " 'County':        FIPS  LILATracts_Vehicle\n",
       " 0     10001            0.164720\n",
       " 1     10003            0.129582\n",
       " 2     10005            0.042145\n",
       " 3     10010            0.064586\n",
       " 4     10030            0.114731\n",
       " ...     ...                 ...\n",
       " 3010  56037            0.137542\n",
       " 3011  56039            0.000000\n",
       " 3012  56041            0.343245\n",
       " 3013  56043            0.000000\n",
       " 3014  56045            0.000000\n",
       " \n",
       " [3015 rows x 2 columns]}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd.food_desert_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3caa3a54",
   "metadata": {},
   "source": [
    "## Downloading Water Violation Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf232590",
   "metadata": {},
   "source": [
    "`water_violation` class variable can provide you accumulate number of water violations in a given county between `start_year` and `end_year`. When `end_year` is **None**, which is a default value for the argument, it gives the total accumulate number of violations for the given county since the `start_year`. The default for `start_year` is 2016. If you want to retrieve information for a single year, make sure `start_year` == `end_year`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a47e2ad6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIFTools import water_violation\n",
    "\n",
    "wv = water_violation(['21','22'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "04c44afc",
   "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>County</th>\n",
       "      <th>State</th>\n",
       "      <th>Counts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adair County</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Allen County</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Anderson County</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ballard County</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Barren County</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>Webster Parish County</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>West Baton Rouge Parish County</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>West Carroll Parish County</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>West Feliciana Parish County</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>Winn Parish County</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>184 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             County      State  Counts\n",
       "0                      Adair County   Kentucky     0.0\n",
       "1                      Allen County   Kentucky     2.0\n",
       "2                   Anderson County   Kentucky     2.0\n",
       "3                    Ballard County   Kentucky     0.0\n",
       "4                     Barren County   Kentucky     0.0\n",
       "..                              ...        ...     ...\n",
       "179           Webster Parish County  Louisiana    14.0\n",
       "180  West Baton Rouge Parish County  Louisiana     0.0\n",
       "181      West Carroll Parish County  Louisiana    11.0\n",
       "182    West Feliciana Parish County  Louisiana     0.0\n",
       "183              Winn Parish County  Louisiana    48.0\n",
       "\n",
       "[184 rows x 3 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wv.water_violation_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfedade4",
   "metadata": {},
   "source": [
    "## Downloading BLS Employment Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5622ee3",
   "metadata": {},
   "source": [
    "While ACS5 provides 5 years estimates of unemployment rate, the BLS provides most recent county-wise unemployment numbers.    \n",
    "`BLS` with a state_fips code(s) provides the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cf89e08b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from CIFTools import BLS\n",
    "bls = BLS(['21','22'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cf386c5e",
   "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>FIPS</th>\n",
       "      <th>Unemployment Rate</th>\n",
       "      <th>Period</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21001</td>\n",
       "      <td>4.7</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21003</td>\n",
       "      <td>3.7</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21005</td>\n",
       "      <td>3.1</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21007</td>\n",
       "      <td>4.4</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21009</td>\n",
       "      <td>4.1</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>22119</td>\n",
       "      <td>3.4</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>22121</td>\n",
       "      <td>2.6</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>22123</td>\n",
       "      <td>4.2</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>22125</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>22127</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Nov-22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>184 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      FIPS  Unemployment Rate  Period\n",
       "0    21001                4.7  Nov-22\n",
       "1    21003                3.7  Nov-22\n",
       "2    21005                3.1  Nov-22\n",
       "3    21007                4.4  Nov-22\n",
       "4    21009                4.1  Nov-22\n",
       "..     ...                ...     ...\n",
       "179  22119                3.4  Nov-22\n",
       "180  22121                2.6  Nov-22\n",
       "181  22123                4.2  Nov-22\n",
       "182  22125                2.0  Nov-22\n",
       "183  22127                3.2  Nov-22\n",
       "\n",
       "[184 rows x 3 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bls.bls_data"
   ]
  }
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