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 (jiangyifei@gmail.com) pygmaps module.