GMaps

Custom Python plots on a Google Maps background. A flexible matplotlib like interface to generate many types of plots on top of Google Maps.

Setup

You'll need to have a Google Static Maps API key, go to https://console.developers.google.com, create a project, enable Google Static Maps API, get your server key and paste it in google_static_maps_api.py.

Examples

Marker Plots

Simply plotting markers on a map. Consider a pandas DataFrame df defined as follows:

|   | latitude | longitude |  color |  size | label |
|---|----------|-----------|--------|-------|-------|
| 0 |  48.8770 |  2.30698  |  blue  |  tiny |       |
| 1 |  48.8708 |  2.30523  |   red  | small |       |
| 2 |  48.8733 |  2.32403  | orange |  mid  |   A   |
| 3 |  48.8728 |  2.30491  |  black |  mid  |   Z   |
| 4 |  48.8644 |  2.33160  | purple |  mid  |   0   |

Simply use

import gmaps

gmaps.plot_markers(df)

will produce

Density Plots

The only thing you need is a pandas DataFrame df containing a 'latitude' and a 'longitude' columns, describing locations.

import gmaps

gmaps.density_plot(df['latitude'], df['longitude'])

Heat Maps

This time your pandas DataFrame df will need an extra 'value' column, describing the metric you want to plot (you may have to normalize it properly for a good rendering).

import gmaps

gmaps.heatmap(df['latitude'], df['longitude'], df['value'])

Scatter Plots

Let's assume your pandas DataFrame df has a numerical 'cluster' column, describing clusters of geographical points. You can produce plots like the following:

import gmaps

gmaps.scatter(df['latitude'], df['longitude'], colors=df['cluster'])

Polygon Plots

Still with the same DataFrame df and its 'cluster' column, plotting clusters and their convex hull.

import gmaps

gmaps.polygons(df['latitude'], df['longitude'], df['cluster'])

More to come!

Requirements

pandas >= 0.13.1
numpy >= 1.8.2
scipy >= 0.13.3
matplotlib >= 1.3.1
requests >= 2.7.0

earthat / gmaps