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Filled Area on Maps in Python

How to make an area on Map in Python with Plotly.


New to Plotly?

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 and Base Map Configuration

To plot on Mapbox maps with Plotly you may need a Mapbox account and a public Mapbox Access Token. See our Mapbox Map Layers documentation for more information.

There are three different ways to show a filled area in a Mapbox map:

  1. Use a Scattermapbox trace and set fill attribute to 'toself'
  2. Use a Mapbox layout (i.e. by minimally using an empty Scattermapbox trace) and add a GeoJSON layer
  3. Use the Choroplethmapbox trace type

Filled Scattermapbox Trace

The following example uses Scattermapbox and sets fill = 'toself'

import plotly.graph_objects as go

fig = go.Figure(go.Scattermapbox(
    fill = "toself",
    lon = [-74, -70, -70, -74], lat = [47, 47, 45, 45],
    marker = { 'size': 10, 'color': "orange" }))

fig.update_layout(
    mapbox = {
        'style': "stamen-terrain",
        'center': {'lon': -73, 'lat': 46 },
        'zoom': 5},
    showlegend = False)

fig.show()

Multiple Filled Areas with a Scattermapbox trace

The following example shows how to use None in your data to draw multiple filled areas. Such gaps in trace data are unconnected by default, but this can be controlled via the connectgaps attribute.

import plotly.graph_objects as go

fig = go.Figure(go.Scattermapbox(
    mode = "lines", fill = "toself",
    lon = [-10, -10, 8, 8, -10, None, 30, 30, 50, 50, 30, None, 100, 100, 80, 80, 100],
    lat = [30, 6, 6, 30, 30,    None, 20, 30, 30, 20, 20, None, 40, 50, 50, 40, 40]))

fig.update_layout(
    mapbox = {'style': "stamen-terrain", 'center': {'lon': 30, 'lat': 30}, 'zoom': 2},
    showlegend = False,
    margin = {'l':0, 'r':0, 'b':0, 't':0})

fig.show()

GeoJSON Layers

In this map we add a GeoJSON layer.

import plotly.graph_objects as go

fig = go.Figure(go.Scattermapbox(
    mode = "markers",
    lon = [-73.605], lat = [45.51],
    marker = {'size': 20, 'color': ["cyan"]}))

fig.update_layout(
    mapbox = {
        'style': "stamen-terrain",
        'center': { 'lon': -73.6, 'lat': 45.5},
        'zoom': 12, 'layers': [{
            'source': {
                'type': "FeatureCollection",
                'features': [{
                    'type': "Feature",
                    'geometry': {
                        'type': "MultiPolygon",
                        'coordinates': [[[
                            [-73.606352888, 45.507489991], [-73.606133883, 45.50687600],
                            [-73.605905904, 45.506773980], [-73.603533905, 45.505698946],
                            [-73.602475870, 45.506856969], [-73.600031904, 45.505696003],
                            [-73.599379992, 45.505389066], [-73.599119902, 45.505632008],
                            [-73.598896977, 45.505514039], [-73.598783894, 45.505617001],
                            [-73.591308727, 45.516246185], [-73.591380782, 45.516280145],
                            [-73.596778656, 45.518690062], [-73.602796770, 45.521348046],
                            [-73.612239983, 45.525564037], [-73.612422919, 45.525642061],
                            [-73.617229085, 45.527751983], [-73.617279234, 45.527774160],
                            [-73.617304713, 45.527741334], [-73.617492052, 45.527498362],
                            [-73.617533258, 45.527512253], [-73.618074188, 45.526759105],
                            [-73.618271651, 45.526500673], [-73.618446320, 45.526287943],
                            [-73.618968507, 45.525698560], [-73.619388002, 45.525216750],
                            [-73.619532966, 45.525064183], [-73.619686662, 45.524889290],
                            [-73.619787038, 45.524770086], [-73.619925742, 45.524584939],
                            [-73.619954486, 45.524557690], [-73.620122362, 45.524377961],
                            [-73.620201713, 45.524298907], [-73.620775593, 45.523650879]
                        ]]]
                    }
                }]
            },
            'type': "fill", 'below': "traces", 'color': "royalblue"}]},
    margin = {'l':0, 'r':0, 'b':0, 't':0})

fig.show()

Reference

See https://plotly.com/python/reference/#scattermapbox for more information about mapbox and their attribute options.

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter