{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CARTOframes with Dask\n",
    "\n",
    "This notebook recreate the workflow from <https://jakevdp.github.io/blog/2015/08/14/out-of-core-dataframes-in-python/>, where the author explores [`dask`](http://dask.pydata.org/en/latest/) for splitting up the computations across multiple cores in a machine to complete tasks more quickly. \n",
    "\n",
    "## Basics\n",
    "\n",
    "You'll need the following for this:\n",
    "\n",
    "1. Your CARTO username\n",
    "2. Your API key\n",
    "\n",
    "Paste these values in the quotes (`''`) below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import cartoframes\n",
    "\n",
    "username = ''   # <-- insert your username here\n",
    "api_key = ''    # <-- insert your API key here\n",
    "\n",
    "cc = cartoframes.CartoContext('https://{}.carto.com/'.format(username),\n",
    "                              api_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask import dataframe as dd\n",
    "import pandas as pd\n",
    "columns = [\"name\", \"amenity\", \"Longitude\", \"Latitude\"]\n",
    "data = dd.read_csv('scratch/POIWorld.csv', usecols=columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with_name = data[data.name.notnull()]\n",
    "with_amenity = data[data.amenity.notnull()]\n",
    "\n",
    "is_starbucks = with_name.name.str.contains('[Ss]tarbucks')\n",
    "is_dunkin = with_name.name.str.contains('[Dd]unkin')\n",
    "\n",
    "starbucks = with_name[is_starbucks].compute()\n",
    "dunkin = with_name[is_dunkin].compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>amenity</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6696</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>121.035006</td>\n",
       "      <td>14.547281</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8322</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>120.978371</td>\n",
       "      <td>14.578929</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9505</th>\n",
       "      <td>星巴克咖啡 Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>120.135887</td>\n",
       "      <td>30.271254</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12417</th>\n",
       "      <td>星巴克咖啡 Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>120.158464</td>\n",
       "      <td>30.253061</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12418</th>\n",
       "      <td>星巴克咖啡 Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>120.157341</td>\n",
       "      <td>30.256555</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28564</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-76.934625</td>\n",
       "      <td>40.238707</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33017</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-1.545032</td>\n",
       "      <td>53.797463</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36552</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-79.390940</td>\n",
       "      <td>43.649976</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37719</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-79.389462</td>\n",
       "      <td>43.645361</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40437</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-79.393634</td>\n",
       "      <td>43.670435</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40439</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-79.390089</td>\n",
       "      <td>43.670596</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41495</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>13.388738</td>\n",
       "      <td>52.519403</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41500</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>13.379787</td>\n",
       "      <td>52.516727</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41869</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>13.373732</td>\n",
       "      <td>52.507931</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42941</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>13.376430</td>\n",
       "      <td>52.510587</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43173</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>32.878538</td>\n",
       "      <td>39.895229</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43229</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>16.370443</td>\n",
       "      <td>48.203665</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45342</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>cafe</td>\n",
       "      <td>13.390018</td>\n",
       "      <td>52.511072</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50742</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-79.385434</td>\n",
       "      <td>43.655530</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53643</th>\n",
       "      <td>Starbucks Coffee</td>\n",
       "      <td>cafe</td>\n",
       "      <td>-0.135514</td>\n",
       "      <td>51.498925</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   name amenity   Longitude   Latitude       type\n",
       "6696          Starbucks    cafe  121.035006  14.547281  starbucks\n",
       "8322   Starbucks Coffee    cafe  120.978371  14.578929  starbucks\n",
       "9505    星巴克咖啡 Starbucks    cafe  120.135887  30.271254  starbucks\n",
       "12417   星巴克咖啡 Starbucks    cafe  120.158464  30.253061  starbucks\n",
       "12418   星巴克咖啡 Starbucks    cafe  120.157341  30.256555  starbucks\n",
       "28564         Starbucks    cafe  -76.934625  40.238707  starbucks\n",
       "33017         Starbucks    cafe   -1.545032  53.797463  starbucks\n",
       "36552  Starbucks Coffee    cafe  -79.390940  43.649976  starbucks\n",
       "37719  Starbucks Coffee    cafe  -79.389462  43.645361  starbucks\n",
       "40437  Starbucks Coffee    cafe  -79.393634  43.670435  starbucks\n",
       "40439  Starbucks Coffee    cafe  -79.390089  43.670596  starbucks\n",
       "41495  Starbucks Coffee    cafe   13.388738  52.519403  starbucks\n",
       "41500  Starbucks Coffee    cafe   13.379787  52.516727  starbucks\n",
       "41869  Starbucks Coffee    cafe   13.373732  52.507931  starbucks\n",
       "42941  Starbucks Coffee    cafe   13.376430  52.510587  starbucks\n",
       "43173         Starbucks    cafe   32.878538  39.895229  starbucks\n",
       "43229         Starbucks    cafe   16.370443  48.203665  starbucks\n",
       "45342         Starbucks    cafe   13.390018  52.511072  starbucks\n",
       "50742  Starbucks Coffee    cafe  -79.385434  43.655530  starbucks\n",
       "53643  Starbucks Coffee    cafe   -0.135514  51.498925  starbucks"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "starbucks['type'] = 'starbucks'\n",
    "dunkin['type'] = 'dunkin'\n",
    "coffee_places = pd.concat([starbucks, dunkin])\n",
    "coffee_places.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Write DataFrame to CARTO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The following columns were changed in the CARTO copy of this dataframe:\n",
      "\u001b[1mLongitude\u001b[0m -> \u001b[1mlongitude\u001b[0m\n",
      "\u001b[1mLatitude\u001b[0m -> \u001b[1mlatitude\u001b[0m\n",
      "Table successfully written to CARTO: https://cartoframes.carto.com/dataset/coffee_places\n"
     ]
    }
   ],
   "source": [
    "# specify columns for lng/lat so carto will create a geometry\n",
    "cc.write(coffee_places,\n",
    "         table_name='coffee_places',\n",
    "         lnglat=('longitude', 'latitude'),\n",
    "         overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's visualize this DataFrame\n",
    "\n",
    "Category map on Dunkin' Donuts vs. Starbucks (aka, color by 'type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x160fe00f0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HKEqWCQHk7A0y/rzd5PcPb6fqX6QV1qcPrRTlQkRhebm1eMe0TONLnUNJyVoY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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x153cf9320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from cartoframes import Layer\n",
    "cc.map(layers=Layer('coffee_places', color='type', size=3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fast Food"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "McDonald's        8697\n",
       "Subway            7058\n",
       "Burger King       3226\n",
       "KFC               2881\n",
       "Wendy's           1304\n",
       "Taco Bell         1282\n",
       "Pizza Hut         1014\n",
       "マクドナルド             927\n",
       "Dairy Queen        745\n",
       "Domino's Pizza     724\n",
       "McDonalds          619\n",
       "Arby's             609\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "is_fastfood = with_amenity.amenity.str.contains('fast_food')\n",
    "fastfood = with_amenity[is_fastfood]\n",
    "fastfood.name.value_counts().head(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The following columns were changed in the CARTO copy of this dataframe:\n",
      "\u001b[1mLongitude\u001b[0m -> \u001b[1mlongitude\u001b[0m\n",
      "\u001b[1mLatitude\u001b[0m -> \u001b[1mlatitude\u001b[0m\n",
      "Table successfully written to CARTO: https://cartoframes.carto.com/dataset/fastfood_dask\n",
      "`the_geom` column is being populated from `('longitude', 'latitude')`. Check the status of the operation with:\n",
      "    \u001b[1mBatchJobStatus(CartoContext(), 'd2bc4e92-b1d5-4c7d-a8d7-d5a47eddea0f').status()\u001b[0m\n",
      "or try reading the table from CARTO in a couple of minutes.\n",
      "\u001b[1mNote:\u001b[0m `CartoContext.map` will not work on this table until its geometries are created.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BatchJobStatus(job_id='d2bc4e92-b1d5-4c7d-a8d7-d5a47eddea0f', last_status='pending', created_at='2017-12-05T14:25:06.748Z')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ff = fastfood.compute()\n",
    "cc.write(ff,\n",
    "         table_name='fastfood_dask',\n",
    "         lnglat=('longitude', 'latitude'), overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Number of Fast Food places in this OSM dump"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "152214"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ff)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### OSM Fast Food POIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe srcdoc=\"<!DOCTYPE html>\n",
       "<html>\n",
       "  <head>\n",
       "    <title>Carto</title>\n",
       "    <meta name='viewport' content='initial-scale=1.0, user-scalable=no' />\n",
       "    <meta http-equiv='content-type' content='text/html; charset=UTF-8' />\n",
       "    <link rel='shortcut icon' href='http://cartodb.com/assets/favicon.ico' />\n",
       "\n",
       "    <style>\n",
       "     html, body, #map {\n",
       "       height: 100%;\n",
       "       padding: 0;\n",
       "       margin: 0;\n",
       "     }\n",
       "     #zoom-center {\n",
       "       position: absolute;\n",
       "       right: 0;\n",
       "       top: 0;\n",
       "       background-color: rgba(255, 255, 255, 0.7);\n",
       "       width: 240px;\n",
       "       z-index: 100;\n",
       "       padding: 4px;\n",
       "     }\n",
       "    </style>\n",
       "\n",
       "    <link rel='stylesheet' href='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/themes/css/cartodb.css' />\n",
       "  </head>\n",
       "  <body>\n",
       "    <div id='zoom-center'>\n",
       "      zoom=<span id='zoom'>4</span>,\n",
       "      lng=<span id='lon'>No data</span>, lat=<span id='lat'>No data</span>\n",
       "    </div>\n",
       "    <div id='map'></div>\n",
       "    <script src='https://cartodb-libs.global.ssl.fastly.net/cartodb.js/v3/3.15/cartodb.js'></script>\n",
       "\n",
       "    <script>\n",
       "     const config  = {&quot;user_name&quot;: &quot;cartoframes&quot;, &quot;maps_api_template&quot;: &quot;https://cartoframes.carto.com&quot;, &quot;sql_api_template&quot;: &quot;https://cartoframes.carto.com&quot;, &quot;tiler_protocol&quot;: &quot;https&quot;, &quot;tiler_domain&quot;: &quot;carto.com&quot;, &quot;tiler_port&quot;: &quot;80&quot;, &quot;type&quot;: &quot;namedmap&quot;, &quot;named_map&quot;: {&quot;name&quot;: &quot;cartoframes_ver20170406_layers1_time0_baseid2_labels0_zoom0&quot;, &quot;params&quot;: {&quot;basemap_url&quot;: &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/rastertiles/voyager_labels_under/{z}/{x}/{y}.png&quot;, &quot;cartocss_0&quot;: &quot;#layer[&#92;'mapnik::geometry_type&#92;'=1] {  marker-width: 2; marker-fill: #5D69B1; marker-fill-opacity: 1; marker-allow-overlap: true; marker-line-width: 0.5; marker-line-color: #FFF; marker-line-opacity: 1;} #layer[&#92;'mapnik::geometry_type&#92;'=2] {  line-width: 1.5; line-color: #5D69B1;} #layer[&#92;'mapnik::geometry_type&#92;'=3] {  polygon-fill: #5D69B1; polygon-opacity: 0.9; polygon-gamma: 0.5; line-color: #FFF; line-width: 0.5; line-opacity: 0.25; line-comp-op: hard-light;} &quot;, &quot;sql_0&quot;: &quot;SELECT * FROM fastfood_dask&quot;, &quot;west&quot;: -178.8312024, &quot;south&quot;: -54.8071336, &quot;east&quot;: 178.4835648, &quot;north&quot;: 71.6361881}}};\n",
       "     const bounds  = [[71.6361881, 178.4835648], [-54.8071336, -178.8312024]];\n",
       "     const options = {&quot;filter&quot;: [&quot;mapnik&quot;, &quot;torque&quot;], &quot;https&quot;: true};\n",
       "\n",
       "     const adjustLongitude = (lng) => (\n",
       "       lng - ((Math.ceil((lng + 180) / 360) - 1) * 360)\n",
       "     );\n",
       "     const map = L.map('map', {\n",
       "       zoom: 3,\n",
       "       center: [0, 0],\n",
       "     });\n",
       "\n",
       "     if (L.Browser.retina) {\n",
       "         var basemap = config.named_map.params.basemap_url.replace('.png', '@2x.png');\n",
       "     } else {\n",
       "         var basemap = config.named_map.params.basemap_url;\n",
       "     }\n",
       "     L.tileLayer(basemap, {\n",
       "         attribution: &quot;&copy; <a href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;>OpenStreetMap</a>&quot;\n",
       "     }).addTo(map);\n",
       "     const updateMapInfo = () => {\n",
       "       $('#zoom').text(map.getZoom());\n",
       "       $('#lat').text(map.getCenter().lat.toFixed(4));\n",
       "       $('#lon').text(adjustLongitude(map.getCenter().lng).toFixed(4));\n",
       "     };\n",
       "\n",
       "     cartodb.createLayer(map, config, options)\n",
       "            .addTo(map)\n",
       "            .done((layer) => {\n",
       "              if (bounds.length) {\n",
       "                map.fitBounds(bounds);\n",
       "              }\n",
       "              updateMapInfo();\n",
       "              map.on('move', () => {\n",
       "                updateMapInfo();\n",
       "              });\n",
       "            })\n",
       "            .error((err) => {\n",
       "              console.log('ERROR: ', err);\n",
       "            });\n",
       "    </script>\n",
       "\n",
       "  </body>\n",
       "</html>\n",
       "\" width=800 height=400>  Preview image: <img src=\"https://cartoframes.carto.com/api/v1/map/static/named/cartoframes_ver20170406_layers1_time0_baseid2_labels0_zoom0/800/400.png?config=%7B%22basemap_url%22%3A+%22https%3A%2F%2Fcartodb-basemaps-%7Bs%7D.global.ssl.fastly.net%2Frastertiles%2Fvoyager_labels_under%2F%7Bz%7D%2F%7Bx%7D%2F%7By%7D.png%22%2C+%22cartocss_0%22%3A+%22%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D1%5D+%7B++marker-width%3A+2%3B+marker-fill%3A+%235D69B1%3B+marker-fill-opacity%3A+1%3B+marker-allow-overlap%3A+true%3B+marker-line-width%3A+0.5%3B+marker-line-color%3A+%23FFF%3B+marker-line-opacity%3A+1%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D2%5D+%7B++line-width%3A+1.5%3B+line-color%3A+%235D69B1%3B%7D+%23layer%5B%27mapnik%3A%3Ageometry_type%27%3D3%5D+%7B++polygon-fill%3A+%235D69B1%3B+polygon-opacity%3A+0.9%3B+polygon-gamma%3A+0.5%3B+line-color%3A+%23FFF%3B+line-width%3A+0.5%3B+line-opacity%3A+0.25%3B+line-comp-op%3A+hard-light%3B%7D+%22%2C+%22sql_0%22%3A+%22SELECT+%2A+FROM+fastfood_dask%22%7D&anti_cache=0.44686802321019237&bbox=-178.8312024%2C-54.8071336%2C178.4835648%2C71.6361881\" /></iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from cartoframes import BaseMap\n",
    "cc.map(layers=Layer('fastfood_dask', size=2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding measures from the Data Observatory\n",
    "\n",
    "We can augment our datasets to find out some demographics at the areas of each of the coffee places if you wanted to add features for building a model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>amenity</th>\n",
       "      <th>index</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>median_income_2010_2014</th>\n",
       "      <th>median_income_2011_2015</th>\n",
       "      <th>name</th>\n",
       "      <th>pop_determined_poverty_status_per_sq_km_2010_2014</th>\n",
       "      <th>pop_determined_poverty_status_per_sq_km_2011_2015</th>\n",
       "      <th>the_geom</th>\n",
       "      <th>total_pop_per_sq_km_2010_2014</th>\n",
       "      <th>total_pop_per_sq_km_2011_2015</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cartodb_id</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>cafe</td>\n",
       "      <td>28564</td>\n",
       "      <td>40.238707</td>\n",
       "      <td>-76.934625</td>\n",
       "      <td>62842.0</td>\n",
       "      <td>63415.0</td>\n",
       "      <td>Starbucks</td>\n",
       "      <td>881.868363</td>\n",
       "      <td>873.056479</td>\n",
       "      <td>0101000020E61000007D2079E7D03B53C005EBEEF08D1E...</td>\n",
       "      <td>996.366180</td>\n",
       "      <td>991.577729</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>cafe</td>\n",
       "      <td>65532</td>\n",
       "      <td>35.079845</td>\n",
       "      <td>-106.606866</td>\n",
       "      <td>34140.0</td>\n",
       "      <td>32838.0</td>\n",
       "      <td>Starbucks</td>\n",
       "      <td>869.520635</td>\n",
       "      <td>871.745312</td>\n",
       "      <td>0101000020E61000001CA43BE3D6A65AC0A11EEC5E388A...</td>\n",
       "      <td>929.112813</td>\n",
       "      <td>932.249243</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>cafe</td>\n",
       "      <td>93071</td>\n",
       "      <td>44.039946</td>\n",
       "      <td>-88.541166</td>\n",
       "      <td>39996.0</td>\n",
       "      <td>40665.0</td>\n",
       "      <td>Starbucks</td>\n",
       "      <td>687.264493</td>\n",
       "      <td>686.831843</td>\n",
       "      <td>0101000020E61000004E0E9F74A22256C092CD55F31C05...</td>\n",
       "      <td>854.267385</td>\n",
       "      <td>840.552380</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>cafe</td>\n",
       "      <td>143097</td>\n",
       "      <td>37.367685</td>\n",
       "      <td>-122.036460</td>\n",
       "      <td>122354.0</td>\n",
       "      <td>125488.0</td>\n",
       "      <td>Starbucks</td>\n",
       "      <td>3211.407801</td>\n",
       "      <td>3278.440419</td>\n",
       "      <td>0101000020E6100000CFC7105B55825EC0D45D7E4C10AF...</td>\n",
       "      <td>3238.971520</td>\n",
       "      <td>3308.291340</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>cafe</td>\n",
       "      <td>169680</td>\n",
       "      <td>39.953015</td>\n",
       "      <td>-75.192289</td>\n",
       "      <td>18933.0</td>\n",
       "      <td>20483.0</td>\n",
       "      <td>Starbucks</td>\n",
       "      <td>4855.675567</td>\n",
       "      <td>4977.608287</td>\n",
       "      <td>0101000020E610000067B96C744ECC52C0910E0F61FCF9...</td>\n",
       "      <td>6558.800331</td>\n",
       "      <td>6725.720324</td>\n",
       "      <td>starbucks</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "           amenity   index   latitude   longitude  median_income_2010_2014  \\\n",
       "cartodb_id                                                                   \n",
       "6             cafe   28564  40.238707  -76.934625                  62842.0   \n",
       "26            cafe   65532  35.079845 -106.606866                  34140.0   \n",
       "42            cafe   93071  44.039946  -88.541166                  39996.0   \n",
       "61            cafe  143097  37.367685 -122.036460                 122354.0   \n",
       "69            cafe  169680  39.953015  -75.192289                  18933.0   \n",
       "\n",
       "            median_income_2011_2015       name  \\\n",
       "cartodb_id                                       \n",
       "6                           63415.0  Starbucks   \n",
       "26                          32838.0  Starbucks   \n",
       "42                          40665.0  Starbucks   \n",
       "61                         125488.0  Starbucks   \n",
       "69                          20483.0  Starbucks   \n",
       "\n",
       "            pop_determined_poverty_status_per_sq_km_2010_2014  \\\n",
       "cartodb_id                                                      \n",
       "6                                                  881.868363   \n",
       "26                                                 869.520635   \n",
       "42                                                 687.264493   \n",
       "61                                                3211.407801   \n",
       "69                                                4855.675567   \n",
       "\n",
       "            pop_determined_poverty_status_per_sq_km_2011_2015  \\\n",
       "cartodb_id                                                      \n",
       "6                                                  873.056479   \n",
       "26                                                 871.745312   \n",
       "42                                                 686.831843   \n",
       "61                                                3278.440419   \n",
       "69                                                4977.608287   \n",
       "\n",
       "                                                     the_geom  \\\n",
       "cartodb_id                                                      \n",
       "6           0101000020E61000007D2079E7D03B53C005EBEEF08D1E...   \n",
       "26          0101000020E61000001CA43BE3D6A65AC0A11EEC5E388A...   \n",
       "42          0101000020E61000004E0E9F74A22256C092CD55F31C05...   \n",
       "61          0101000020E6100000CFC7105B55825EC0D45D7E4C10AF...   \n",
       "69          0101000020E610000067B96C744ECC52C0910E0F61FCF9...   \n",
       "\n",
       "            total_pop_per_sq_km_2010_2014  total_pop_per_sq_km_2011_2015  \\\n",
       "cartodb_id                                                                 \n",
       "6                              996.366180                     991.577729   \n",
       "26                             929.112813                     932.249243   \n",
       "42                             854.267385                     840.552380   \n",
       "61                            3238.971520                    3308.291340   \n",
       "69                            6558.800331                    6725.720324   \n",
       "\n",
       "                 type  \n",
       "cartodb_id             \n",
       "6           starbucks  \n",
       "26          starbucks  \n",
       "42          starbucks  \n",
       "61          starbucks  \n",
       "69          starbucks  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# DO measures: Total Population,\n",
    "#              Children under 18 years of age\n",
    "#              Median income\n",
    "\n",
    "data_obs_measures = [{'numer_id': 'us.census.acs.B01003001'},\n",
    "                     {'numer_id': 'us.census.acs.B17001001'},\n",
    "                     {'numer_id': 'us.census.acs.B19013001'}]\n",
    "coffee_augmented = cc.data('coffee_places', data_obs_measures)\n",
    "coffee_augmented.head()"
   ]
  }
 ],
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