Mapbox Density Heatmap in Python

How to make a Mapbox Density Heatmap in Python with Plotly.


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Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Mapbox Access Token

To plot on Mapbox maps with Plotly, you may need a Mapbox account and token or a Stadia Maps account and token, depending on base map (mapbox_style) you use. On this page, we show how to use the "open-street-map" base map, which doesn't require a token, and a "stamen" base map, which requires a Stadia Maps token. See our Mapbox Map Layers documentation for more examples.

OpenStreetMap base map (no token needed): density mapbox with plotly.express

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

With px.density_mapbox, each row of the DataFrame is represented as a point smoothed with a given radius of influence.

In [1]:
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/earthquakes-23k.csv')

import plotly.express as px
fig = px.density_mapbox(df, lat='Latitude', lon='Longitude', z='Magnitude', radius=10,
                        center=dict(lat=0, lon=180), zoom=0,
                        mapbox_style="open-street-map")
fig.show()

Stamen Terrain base map (Stadia Maps token needed): density mapbox with plotly.express

Some base maps require a token. To use "stamen" base maps, you'll need a Stadia Maps token, which you can provide to the mapbox_accesstoken parameter on fig.update_layout. Here, we have the token saved in a file called .mapbox_token, load it in to the variable token, and then pass it to mapbox_accesstoken.

import plotly.express as px
import pandas as pd

token = open(".mapbox_token").read() # you will need your own token

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/earthquakes-23k.csv')

fig = px.density_mapbox(df, lat='Latitude', lon='Longitude', z='Magnitude', radius=10,
                        center=dict(lat=0, lon=180), zoom=0,
                        mapbox_style="stamen-terrain")
fig.update_layout(mapbox_accesstoken=token)
fig.show()

OpenStreetMap base map (no token needed): density mapbox with plotly.graph_objects

If Plotly Express does not provide a good starting point, it is also possible to use the more generic go.Densitymapbox class from plotly.graph_objects.

In [2]:
import pandas as pd
quakes = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/earthquakes-23k.csv')

import plotly.graph_objects as go
fig = go.Figure(go.Densitymapbox(lat=quakes.Latitude, lon=quakes.Longitude, z=quakes.Magnitude,
                                 radius=10))
fig.update_layout(mapbox_style="open-street-map", mapbox_center_lon=180)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()