{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mapboxgl Python Library for location data visualization\n",
    "\n",
    "https://github.com/mapbox/mapboxgl-jupyter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from mapboxgl.viz import *\n",
    "from mapboxgl.utils import *\n",
    "\n",
    "# Must be a public token, starting with `pk`\n",
    "token = os.getenv('MAPBOX_ACCESS_TOKEN')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Choropleths with interpolated color assignment from GeoJSON source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# create choropleth from polygon features stored as GeoJSON\n",
    "viz = ChoroplethViz('https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/data/us-states.geojson', \n",
    "                    access_token=token,\n",
    "                    color_property='density',\n",
    "                    color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n",
    "                    color_function_type='interpolate',\n",
    "                    line_stroke='--',\n",
    "                    line_color='rgb(128,0,38)',\n",
    "                    line_width=1,\n",
    "                    line_opacity=0.9,\n",
    "                    opacity=0.8,\n",
    "                    center=(-96, 37.8),\n",
    "                    zoom=3,\n",
    "                    below_layer='waterway-label',\n",
    "                    legend_layout='horizontal',\n",
    "                    legend_key_shape='bar',\n",
    "                    legend_key_borders_on=False)\n",
    "viz.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add 3-D Extrusion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# adjust view angle\n",
    "viz.bearing = -15\n",
    "viz.pitch = 45\n",
    "\n",
    "# add extrusion to viz using interpolation keyed on density in GeoJSON features\n",
    "viz.height_property = 'density'\n",
    "viz.height_stops = create_numeric_stops([0, 50, 100, 500, 1500, 5000], 0, 500000)\n",
    "viz.height_function_type = 'interpolate'\n",
    "\n",
    "# render again\n",
    "viz.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Choropleths with match-type color scheme from GeoJSON source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "match_color_stops = [['Massachusetts', 'rgb(46,204,113)'],\n",
    "                     ['Utah', 'rgb(231,76,60)'],\n",
    "                     ['California', 'rgb(142,68,173)']]\n",
    "\n",
    "viz = ChoroplethViz('https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/data/us-states.geojson', \n",
    "                    access_token=token,\n",
    "                    color_property='name', \n",
    "                    color_stops=match_color_stops, \n",
    "                    color_function_type='match', \n",
    "                    color_default='rgba(52,73,94,0.5)', \n",
    "                    opacity=0.8, \n",
    "                    center=(-96, 37.8), \n",
    "                    zoom=3, \n",
    "                    below_layer='waterway-label')\n",
    "viz.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Vector polygon source with data-join technique\n",
    "\n",
    "In this configuration, properties in JSON data are used to calculate colors to style polygons from the vector source."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# must be JSON object (need to extend to use referenced JSON file)\n",
    "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n",
    "\n",
    "# create choropleth map with vector source styling use data in JSON object\n",
    "viz = ChoroplethViz(data, \n",
    "                    access_token=token,\n",
    "                    vector_url='mapbox://mapbox.us_census_states_2015',\n",
    "                    vector_layer_name='states',\n",
    "                    vector_join_property='STATE_ID',\n",
    "                    data_join_property='id',\n",
    "                    color_property='density',\n",
    "                    color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n",
    "                    line_stroke='dashed',\n",
    "                    line_color='rgb(128,0,38)',\n",
    "                    opacity=0.8,\n",
    "                    center=(-96, 37.8),\n",
    "                    zoom=3,\n",
    "                    below_layer='waterway-label',\n",
    "                    legend_layout='horizontal',\n",
    "                    legend_key_shape='bar',\n",
    "                    legend_key_borders_on=False)\n",
    "viz.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Vector polygon source with data-join technique, categorical color scheme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# must be JSON object (need to extend to use referenced JSON file)\n",
    "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n",
    "\n",
    "match_color_stops = [['Massachusetts', 'rgb(46,204,113)'],\n",
    "                     ['Utah', 'rgb(231,76,60)'],\n",
    "                     ['California', 'rgb(142,68,173)']]\n",
    "\n",
    "# create choropleth map with vector source styling use data in JSON object\n",
    "viz = ChoroplethViz(data, \n",
    "                    access_token=token,\n",
    "                    vector_url='mapbox://mapbox.us_census_states_2015',\n",
    "                    vector_layer_name='states',\n",
    "                    vector_join_property='STATE_ID',\n",
    "                    data_join_property='id',\n",
    "                    color_property='name',\n",
    "                    color_stops=match_color_stops,\n",
    "                    color_default = 'rgba(52,73,94,0.5)', \n",
    "                    opacity=0.8,\n",
    "                    center=(-96, 37.8),\n",
    "                    zoom=3,\n",
    "                    below_layer='waterway-label')\n",
    "viz.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add 3-D Extrusion to Vector Choropleth Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# adjust view angle\n",
    "viz.bearing = -15\n",
    "viz.pitch = 45\n",
    "\n",
    "# add extrusion to viz using interpolation keyed on density in GeoJSON features\n",
    "viz.height_property = 'density'\n",
    "viz.height_stops = create_numeric_stops([0, 50, 100, 500, 1500, 5000], 0, 500000)\n",
    "viz.height_function_type = 'interpolate'\n",
    "\n",
    "# render again\n",
    "viz.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Vector polygon source joined to data in a local Pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data from sample csv\n",
    "import pandas as pd\n",
    "data_url = 'https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/data/2010_us_population_by_postcode.csv'\n",
    "df = pd.read_csv(data_url).round(3)\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Group pandas dataframe by a value\n",
    "measure = '2010 Census Population'\n",
    "dimension = 'Zip Code ZCTA'\n",
    "\n",
    "data = df[[dimension, measure]].groupby(dimension, as_index=False).mean()\n",
    "color_breaks = [round(data[measure].quantile(q=x*0.1), 2) for x in range(2,11)]\n",
    "color_stops = create_color_stops(color_breaks, colors='PuRd')\n",
    "data = json.loads(data.to_json(orient='records'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the viz\n",
    "viz = ChoroplethViz(data, \n",
    "                    access_token=token,\n",
    "                    vector_url='mapbox://rsbaumann.bv2k1pl2',\n",
    "                    vector_layer_name='2016_us_census_postcode',\n",
    "                    vector_join_property='postcode',\n",
    "                    data_join_property=dimension,\n",
    "                    color_property=measure,\n",
    "                    color_stops=color_stops,\n",
    "                    line_color = 'rgba(0,0,0,0.05)',\n",
    "                    line_width = 0.5,\n",
    "                    opacity=0.7,\n",
    "                    center=(-95, 45),\n",
    "                    zoom=2,\n",
    "                    below_layer='waterway-label',\n",
    "                    legend_key_shape='contiguous-bar')\n",
    "viz.show()"
   ]
  }
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