021 - source_us-census-bureau-api_population_2019_walkthrough.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# US Census Bureau API - Population Walkthrough\n",
    "\n",
    "## Overview\n",
    "| Detail Tag            | Information                                                                                        |\n",
    "|-----------------------|----------------------------------------------------------------------------------------------------|\n",
    "| Originally Created By | Ariel Herrera arielherrera@analyticsariel.com                                                      |\n",
    "| External References   | <a href=\"https://www.census.gov/data/developers/data-sets/popest-popproj/popest.html\" target=\"_blank\">(1) US Census API - Population</a>|\n",
    "| Input Datasets        | API key, Address params                                                                                    |\n",
    "| Output Datasets       | Table with population                                              |\n",
    "| Input Data Source     | API                                                                                                |\n",
    "| Output Data Source    | Dataframe                                                                                                   |\n",
    "\n",
    "## History\n",
    "| Date         | Developed By  | Reason                                                |\n",
    "|--------------|---------------|-------------------------------------------------------|\n",
    "| 25th Jan 2021 | Ariel Herrera | Notebook created to get population data from Census API. |\n",
    "\n",
    "## Other Details\n",
    "This Notebook is a prototype."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"blue\">Imports</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests # request http, api\n",
    "import pandas as pd # tabluar data\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"blue\">Local and Constant Variables</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.max_columns = None # show all columns in display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read api keys file and assign variables\n",
    "df = pd.read_csv('../data/input/api_keys.csv')\n",
    "census_api_key = df.loc[df['API'] == 'census']['KEY'].iloc[0]\n",
    "rapid_api_key = df.loc[df['API'] == 'rapid']['KEY'].iloc[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"blue\">Functions</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def json_to_dataframe(response):\n",
    "    \"\"\"\n",
    "    Convert response to dataframe\n",
    "    \"\"\"\n",
    "    return pd.DataFrame(response.json()[1:], columns=response.json()[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=\"blue\">Data</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=\"purple\">Population Estimates: Estimates by Age, Sex, Race, and Hispanic Origin</font>\n",
    "https://api.census.gov/data/2019/pep/population/examples.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# population united states\n",
    "url = \"https://api.census.gov/data/2019/pep/charage?get=NAME,POP&for=us:*&key={0}\"\\\n",
    "    .format(census_api_key)\n",
    "\n",
    "response = requests.request(\"GET\", url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[[\"NAME\",\"POP\",\"HISP\",\"DATE_CODE\",\"DATE_DESC\",\"state\"],\\n[\"New York\",\"16010245\",\"1\",\"7\",\"7/1/2014 Population Estimate\",\"36\"],\\n[\"New York\",\"3640804\",\"2\",\"7\",\"7/1/2014 Population Estimate\",\"36\"],\\n[\"New York\",\"15977166\",\"1\",\"8\",\"7/1/2015 Population Estimate\",\"36\"],\\n[\"New York\",\"3677500\",\"2\",\"8\",\"7/1/2015 Population Estimate\",\"36\"],\\n[\"New York\",\"15925768\",\"1\",\"9\",\"7/1/2016 Population Estimate\",\"36\"],\\n[\"New York\",\"3707660\",\"2\",\"9\",\"7/1/2016 Population Estimate\",\"36\"],\\n[\"New York\",\"15864453\",\"1\",\"10\",\"7/1/2017 Population Estimate\",\"36\"],\\n[\"New York\",\"3725119\",\"2\",\"10\",\"7/1/2017 Population Estimate\",\"36\"],\\n[\"New York\",\"15786810\",\"1\",\"11\",\"7/1/2018 Population Estimate\",\"36\"],\\n[\"New York\",\"3743541\",\"2\",\"11\",\"7/1/2018 Population Estimate\",\"36\"],\\n[\"New York\",\"15702503\",\"1\",\"12\",\"7/1/2019 Population Estimate\",\"36\"],\\n[\"New York\",\"3751058\",\"2\",\"12\",\"7/1/2019 Population Estimate\",\"36\"]]'"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>POP</th>\n",
       "      <th>us</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>328239523</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            NAME        POP us\n",
       "0  United States  328239523  1"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_to_dataframe(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# population united states by year (last 5 on record)\n",
    "url = \"https://api.census.gov/data/2019/pep/charage?get=NAME,POP&DATE_CODE=8,9,10,11,12&DATE_DESC&for=us:*&key={0}\"\\\n",
    "    .format(census_api_key)\n",
    "\n",
    "response = requests.request(\"GET\", url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>POP</th>\n",
       "      <th>DATE_CODE</th>\n",
       "      <th>DATE_DESC</th>\n",
       "      <th>us</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>320635163</td>\n",
       "      <td>8</td>\n",
       "      <td>7/1/2015 Population Estimate</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>United States</td>\n",
       "      <td>322941311</td>\n",
       "      <td>9</td>\n",
       "      <td>7/1/2016 Population Estimate</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United States</td>\n",
       "      <td>324985539</td>\n",
       "      <td>10</td>\n",
       "      <td>7/1/2017 Population Estimate</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>United States</td>\n",
       "      <td>326687501</td>\n",
       "      <td>11</td>\n",
       "      <td>7/1/2018 Population Estimate</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>United States</td>\n",
       "      <td>328239523</td>\n",
       "      <td>12</td>\n",
       "      <td>7/1/2019 Population Estimate</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            NAME        POP DATE_CODE                     DATE_DESC us\n",
       "0  United States  320635163         8  7/1/2015 Population Estimate  1\n",
       "1  United States  322941311         9  7/1/2016 Population Estimate  1\n",
       "2  United States  324985539        10  7/1/2017 Population Estimate  1\n",
       "3  United States  326687501        11  7/1/2018 Population Estimate  1\n",
       "4  United States  328239523        12  7/1/2019 Population Estimate  1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_to_dataframe(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# population united states by state\n",
    "url = \"https://api.census.gov/data/2019/pep/charage?get=NAME,POP&for=state:*&key={0}\"\\\n",
    "    .format(census_api_key)\n",
    "\n",
    "response = requests.request(\"GET\", url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 5 states with largest population estimates:\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "    }\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>POP</th>\n",
       "      <th>HISP</th>\n",
       "      <th>DATE_CODE</th>\n",
       "      <th>DATE_DESC</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>New York</td>\n",
       "      <td>16010245</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>7/1/2014 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>New York</td>\n",
       "      <td>15977166</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>7/1/2015 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>New York</td>\n",
       "      <td>15925768</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>7/1/2016 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>New York</td>\n",
       "      <td>15864453</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>7/1/2017 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>New York</td>\n",
       "      <td>15786810</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>7/1/2018 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       NAME       POP HISP DATE_CODE                     DATE_DESC state\n",
       "0  New York  16010245    1         7  7/1/2014 Population Estimate    36\n",
       "2  New York  15977166    1         8  7/1/2015 Population Estimate    36\n",
       "4  New York  15925768    1         9  7/1/2016 Population Estimate    36\n",
       "6  New York  15864453    1        10  7/1/2017 Population Estimate    36\n",
       "8  New York  15786810    1        11  7/1/2018 Population Estimate    36"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pop_by_state = json_to_dataframe(response)\n",
    "\n",
    "# convert population to integer\n",
    "df_pop_by_state['POP'] = df_pop_by_state['POP'].astype(int)\n",
    "\n",
    "# top 5 states with largest population\n",
    "df_pop_by_state_sort = df_pop_by_state\\\n",
    "    .sort_values(by=['POP'], ascending=False)\\\n",
    "    .head(5) \n",
    "print('Top 5 states with largest population estimates:')\n",
    "df_pop_by_state_sort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "list of top 5 states: ['06', '48', '12', '36', '42']\n",
      "list of states as one string: 06,48,12,36,42\n"
     ]
    }
   ],
   "source": [
    "top_5_state_list = df_pop_by_state_sort['state'].tolist()\n",
    "print('list of top 5 states:', top_5_state_list)\n",
    "\n",
    "state_str = ','.join(top_5_state_list)\n",
    "print('list of states as one string:', state_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "# population top 5 states for age 16\n",
    "url = \"https://api.census.gov/data/2019/pep/charage?get=NAME,POP&AGE=16&for=state:{0}&key={1}\"\\\n",
    "    .format(state_str,census_api_key)\n",
    "\n",
    "response = requests.request(\"GET\", url)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>POP</th>\n",
       "      <th>AGE</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>New York</td>\n",
       "      <td>227902</td>\n",
       "      <td>16</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>154083</td>\n",
       "      <td>16</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Texas</td>\n",
       "      <td>414872</td>\n",
       "      <td>16</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>California</td>\n",
       "      <td>501846</td>\n",
       "      <td>16</td>\n",
       "      <td>06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Florida</td>\n",
       "      <td>234530</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           NAME     POP AGE state\n",
       "0      New York  227902  16    36\n",
       "1  Pennsylvania  154083  16    42\n",
       "2         Texas  414872  16    48\n",
       "3    California  501846  16    06\n",
       "4       Florida  234530  16    12"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_to_dataframe(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# population NY year over year split by hisp\n",
    "url = \"https://api.census.gov/data/2019/pep/charage?get=NAME,POP&HISP=1,2&DATE_CODE=7,8,9,10,11,12&DATE_DESC&for=state:36&key={0}\"\\\n",
    "    .format(census_api_key)\n",
    "\n",
    "response = requests.request(\"GET\", url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>POP</th>\n",
       "      <th>HISP</th>\n",
       "      <th>DATE_CODE</th>\n",
       "      <th>DATE_DESC</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>New York</td>\n",
       "      <td>16010245</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>7/1/2014 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>New York</td>\n",
       "      <td>3640804</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7/1/2014 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>New York</td>\n",
       "      <td>15977166</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>7/1/2015 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>New York</td>\n",
       "      <td>3677500</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>7/1/2015 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>New York</td>\n",
       "      <td>15925768</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>7/1/2016 Population Estimate</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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       "       NAME       POP HISP DATE_CODE                     DATE_DESC state\n",
       "0  New York  16010245    1         7  7/1/2014 Population Estimate    36\n",
       "1  New York   3640804    2         7  7/1/2014 Population Estimate    36\n",
       "2  New York  15977166    1         8  7/1/2015 Population Estimate    36\n",
       "3  New York   3677500    2         8  7/1/2015 Population Estimate    36\n",
       "4  New York  15925768    1         9  7/1/2016 Population Estimate    36"
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   "source": [
    "fig = px.line(df_hisp_by_year, x=\"DATE_DESC\", y=\"POP\", color=\"HISP\", \n",
    "              title='New York Hispanic Population Estimates Year over Year')\n",
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  {
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   "source": [
    "## Looking for an <font color=\"green\">EASIER</font> way to access the <B>CENSUS DATA</B>? Checkout AnalyticsAriel wrapper API on RAPID API - https://rapidapi.com/arielherrera/api/us-census-bureau/endpoints\n",
    "\n",
    "Tutorial videos on YouTube Channel - AnalyticsAriel"
   ]
  },
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    "# End Notebook"
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