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Add example for making a map directly from a dataframe; addresses map…
…box#4 utilities roadmap
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# Mapboxgl Python Library for location data visualization\n", | ||
"\n", | ||
"https://github.com/mapbox/mapboxgl-jupyter\n", | ||
"\n", | ||
"## Maps using Pandas DataFrame accessors\n", | ||
"requires Pandas > 0.23" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import pandas as pd\n", | ||
"import os\n", | ||
"from mapboxgl.utils import *\n", | ||
"from mapboxgl.viz import *\n", | ||
"\n", | ||
"# Set Mapbox public token, starting with `pk`\n", | ||
"token = os.getenv('MAPBOX_ACCESS_TOKEN')" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"## Define Accessor with `mapbox` namespace" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"@pd.api.extensions.register_dataframe_accessor('mapbox')\n", | ||
"class GeoAccessor(object):\n", | ||
" \"\"\"\n", | ||
" https://pandas.pydata.org/pandas-docs/stable/extending.html\n", | ||
" \"\"\"\n", | ||
" \n", | ||
" def __init__(self, pandas_obj):\n", | ||
" self._obj = pandas_obj\n", | ||
"\n", | ||
" @property\n", | ||
" def center(self):\n", | ||
" # return the geographic center point of this DataFrame\n", | ||
" lat = self._obj.lat\n", | ||
" lon = self._obj.lon\n", | ||
" return (float(lon.mean()), float(lat.mean()))\n", | ||
"\n", | ||
" def draw_map(self, color_property, color_stops):\n", | ||
" \n", | ||
" data = df_to_geojson(df, \n", | ||
" properties=['Avg Medicare Payments', \n", | ||
" 'Avg Covered Charges', \n", | ||
" 'date'], \n", | ||
" lat='lat', \n", | ||
" lon='lon', \n", | ||
" precision=3)\n", | ||
" \n", | ||
" viz = CircleViz(data, \n", | ||
" access_token=token, \n", | ||
" color_property=color_property,\n", | ||
" color_stops=color_stops,\n", | ||
" radius=2, \n", | ||
" center=(-95, 40), \n", | ||
" zoom=3)\n", | ||
" \n", | ||
" viz.show()" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"## Create a visualization from a Pandas dataframe" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# Load data from sample csv\n", | ||
"data_url = 'https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/data/points.csv'\n", | ||
"df = pd.read_csv(data_url).round(3)\n", | ||
"\n", | ||
"# Generate data breaks using numpy quantiles and color stops from colorBrewer\n", | ||
"measure = 'Avg Medicare Payments'\n", | ||
"color_breaks = [round(df[measure].quantile(q=x*0.1), 2) for x in range(1, 9)]\n", | ||
"color_stops = create_color_stops(color_breaks, colors='YlGnBu')\n", | ||
"\n", | ||
"# Make map with dataframe accessor\n", | ||
"df.mapbox.draw_map(measure, color_stops)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [] | ||
} | ||
], | ||
"metadata": { | ||
"anaconda-cloud": { | ||
"attach-environment": true, | ||
"environment": "Root", | ||
"summary": "Mapboxgl Python Data Visualization example" | ||
}, | ||
"kernelspec": { | ||
"display_name": "Python 3", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 3 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython3", | ||
"version": "3.6.1" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 1 | ||
} |