Plotting data on Google Maps, the easy way. A matplotlib-like interface to generate the HTML and javascript to render all the data you'd like on top of Google Maps. Several plotting methods make creating exploratory map views effortless. Here's a crash course:
from gmplot import gmplot # Place map gmap = gmplot.GoogleMapPlotter(37.766956, -122.438481, 13) # Polygon golden_gate_park_lats, golden_gate_park_lons = zip(*[ (37.771269, -122.511015), (37.773495, -122.464830), (37.774797, -122.454538), (37.771988, -122.454018), (37.773646, -122.440979), (37.772742, -122.440797), (37.771096, -122.453889), (37.768669, -122.453518), (37.766227, -122.460213), (37.764028, -122.510347), (37.771269, -122.511015) ]) gmap.plot(golden_gate_park_lats, golden_gate_park_lons, 'cornflowerblue', edge_width=10) # Scatter points top_attraction_lats, top_attraction_lons = zip(*[ (37.769901, -122.498331), (37.768645, -122.475328), (37.771478, -122.468677), (37.769867, -122.466102), (37.767187, -122.467496), (37.770104, -122.470436) ]) gmap.scatter(top_attraction_lats, top_attraction_lons, '#3B0B39', size=40, marker=False) # Marker hidden_gem_lat, hidden_gem_lon = 37.770776, -122.461689 gmap.marker(hidden_gem_lat, hidden_gem_lon, 'cornflowerblue') # Draw gmap.draw("my_map.html")
gmplot
contains a simple wrapper around Google's geocoding service enabling
map initilization to the location of your choice. Rather than providing latitude,
longitude, and zoom level during initialization, grab your gmplot instance with
a location:
gmap = gmplot.GoogleMapPlotter.from_geocode("San Francisco")
- Polygons with fills -
plot
- Drop pins. -
marker
- Scatter points. -
scatter
- Grid lines. -
grid
- Heatmaps. -
heatmap
Code hosted on GitHub
Install easily with pip install gmplot
from PyPI.
Inspired by Yifei Jiang's ([email protected]) pygmaps module.