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Filled area on tile maps in Python
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Python > Maps > Filled Area on Tile Maps
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Filled Area on Tile Maps in Python

How to make an area on tile-based maps in Python with Plotly.


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There are three different ways to show a filled area on a tile-based map:

  • Using a Scattermap trace and setting the fill attribute to 'toself'
  • Using a map layout (i.e. by minimally using an empty Scattermap trace) and adding a GeoJSON layer
  • Using the Choroplethmap trace type

Filled Scattermap Trace

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

In [1]:
import plotly.graph_objects as go

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

fig.update_layout(
    map = {
        'style': "open-street-map",
        'center': {'lon': -73, 'lat': 46 },
        'zoom': 5},
    showlegend = False)

fig.show()

Multiple Filled Areas with a Scattermap 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.

In [2]:
import plotly.graph_objects as go

fig = go.Figure(go.Scattermap(
    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(
    map = {'style': "open-street-map", '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.

In [3]:
import plotly.graph_objects as go

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

fig.update_layout(
    map = {
        'style': "open-street-map",
        '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/scattermap/ for available 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( ... )

from dash import Dash, dcc, html

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

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