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        "description": "gmplot\n======\n\nPlotting data on Google Maps, the easy way. A matplotlib-like\ninterface to generate the HTML and javascript to render all the\ndata you'd like on top of Google Maps. Several plotting methods\nmake creating exploratory map views effortless. Here's a crash course:\n\n::\n\n    import gmplot\n\n    gmap = gmplot.GoogleMapPlotter(37.428, -122.145, 16)\n\n    gmap.plot(latitudes, longitudes, 'cornflowerblue', edge_width=10)\n    gmap.scatter(more_lats, more_lngs, '#3B0B39', size=40, marker=False)\n    gmap.scatter(marker_lats, marker_lngs, 'k', marker=True)\n    gmap.heatmap(heat_lats, heat_lngs)\n\n    gmap.draw(\"mymap.html\")\n\n\nGeocoding\n---------\n\n``gmplot`` contains a simple wrapper around Google's geocoding service enabling\nmap initilization to the location of your choice. Rather than providing latitude,\nlongitude, and zoom level during initialization, grab your gmplot instance with\na location:\n\n::\n\n    gmap = gmplot.GoogleMapPlotter.from_geocode(\"San Francisco\")\n\nPlot types\n----------\n\n* Polygons with fills.\n* Drop pins.\n* Scatter points.\n* Grid lines.\n* Heatmaps.\n\n.. image:: http://i.imgur.com/dTNkbZ7.png\n\nMisc.\n-----\n\nCode hosted on `GitHub <https://github.com/vgm64/gmplot>`_\n\nInstall easily with ``pip install gmplot`` from PyPI.\n\nInspired by Yifei Jiang's (jiangyifei@gmail.com) pygmaps_ module.\n\n.. _pygmaps: http://code.google.com/p/pygmaps/\n\n",
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