Scatter Plots on Tile Maps in Python

How to make scatter plots on tile maps in Python.

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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.

Basic example with Plotly Express¶

Here we show the Plotly Express function px.scatter_map for a scatter plot on a tile map.

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.

In [1]:

import plotly.express as px
df = px.data.carshare()
fig = px.scatter_map(df, lat="centroid_lat", lon="centroid_lon",     color="peak_hour", size="car_hours",
                  color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=10)
fig.show()

Basic Example with GeoPandas¶

px.scatter_map can work well with GeoPandas dataframes whose geometry is of type Point.

In [2]:

import plotly.express as px
import geopandas as gpd

geo_df = gpd.read_file(gpd.datasets.get_path('naturalearth_cities'))

fig = px.scatter_map(geo_df,
                        lat=geo_df.geometry.y,
                        lon=geo_df.geometry.x,
                        hover_name="name",
                        zoom=1)
fig.show()

Basic Example¶

In [3]:

import plotly.graph_objects as go

fig = go.Figure(go.Scattermap(
        lat=['45.5017'],
        lon=['-73.5673'],
        mode='markers',
        marker=go.scattermap.Marker(
            size=14
        ),
        text=['Montreal'],
    ))

fig.update_layout(
    hovermode='closest',
    map=dict(
        bearing=0,
        center=go.layout.map.Center(
            lat=45,
            lon=-73
        ),
        pitch=0,
        zoom=5
    )
)

fig.show()

Multiple Markers¶

In [4]:

import plotly.graph_objects as go

fig = go.Figure(go.Scattermap(
        lat=['38.91427','38.91538','38.91458',
             '38.92239','38.93222','38.90842',
             '38.91931','38.93260','38.91368',
             '38.88516','38.921894','38.93206',
             '38.91275'],
        lon=['-77.02827','-77.02013','-77.03155',
             '-77.04227','-77.02854','-77.02419',
             '-77.02518','-77.03304','-77.04509',
             '-76.99656','-77.042438','-77.02821',
             '-77.01239'],
        mode='markers',
        marker=go.scattermap.Marker(
            size=9
        ),
        text=["The coffee bar","Bistro Bohem","Black Cat",
             "Snap","Columbia Heights Coffee","Azi's Cafe",
             "Blind Dog Cafe","Le Caprice","Filter",
             "Peregrine","Tryst","The Coupe",
             "Big Bear Cafe"],
    ))

fig.update_layout(
    autosize=True,
    hovermode='closest',
    map=dict(
        bearing=0,
        center=dict(
            lat=38.92,
            lon=-77.07
        ),
        pitch=0,
        zoom=10
    ),
)

fig.show()

Nuclear Waste Sites on Campuses¶

In [5]:

import plotly.graph_objects as go
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/Nuclear%20Waste%20Sites%20on%20American%20Campuses.csv')
site_lat = df.lat
site_lon = df.lon
locations_name = df.text

fig = go.Figure()

fig.add_trace(go.Scattermap(
        lat=site_lat,
        lon=site_lon,
        mode='markers',
        marker=go.scattermap.Marker(
            size=17,
            color='rgb(255, 0, 0)',
            opacity=0.7
        ),
        text=locations_name,
        hoverinfo='text'
    ))

fig.add_trace(go.Scattermap(
        lat=site_lat,
        lon=site_lon,
        mode='markers',
        marker=go.scattermap.Marker(
            size=8,
            color='rgb(242, 177, 172)',
            opacity=0.7
        ),
        hoverinfo='none'
    ))

fig.update_layout(
    title=dict(text='Nuclear Waste Sites on Campus'),
    autosize=True,
    hovermode='closest',
    showlegend=False,
    map=dict(
        bearing=0,
        center=dict(
            lat=38,
            lon=-94
        ),
        pitch=0,
        zoom=3,
        style='light'
    ),
)

fig.show()

Set Marker Symbols¶

You can define the symbol on your map by setting symbol attribute.

basic
streets
outdoors
light
dark
satellite
satellite-streets

In [6]:

import plotly.graph_objects as go

fig = go.Figure(go.Scattermap(
    mode = "markers+text+lines",
    lon = [-75, -80, -50], lat = [45, 20, -20],
    marker = {'size': 20, 'symbol': ["bus", "harbor", "airport"]},
    text = ["Bus", "Harbor", "airport"],textposition = "bottom right"))

fig.update_layout(
    map = {
        'style': "outdoors", 'zoom': 0.7},
    showlegend = False)

fig.show()

Add Clusters¶

New in 5.11

Display clusters of data points by setting cluster. Here, we enable clusters with enabled=True. You can also enable clusters by setting other cluster properties. Other available properties include color (for setting the color of the clusters), size (for setting the size of a cluster step), and step (for configuring how many points it takes to create a cluster or advance to the next cluster step).

In [7]:

import plotly.express as px
import pandas as pd

df = pd.read_csv(
    "https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv"
)
fig = px.scatter_map(df, lat="lat", lon="long", size="cnt", zoom=3)
fig.update_traces(cluster=dict(enabled=True))
fig.show()

Font Customization¶

You can customize the font on go.Scattermap traces with textfont. For example, you can set the font family.

In [8]:

import plotly.graph_objects as go

fig = go.Figure(go.Scattermap(
    mode = "markers+text+lines",
    lon = [-75, -80, -50], lat = [45, 20, -20],
    marker = {'size': 20, 'symbol': ["bus", "harbor", "airport"]},
    text = ["Bus", "Harbor", "airport"], textposition = "bottom right",
    textfont = dict(size=18, color="black", family="Open Sans Bold")
    ))

fig.update_layout(
    map = {
        'style': "outdoors", 'zoom': 0.7},
    showlegend = False,)

fig.show()

go.Scattermap supports the following values for textfont.family:

'Metropolis Black Italic', 'Metropolis Black', 'Metropolis Bold Italic', 'Metropolis Bold', 'Metropolis Extra Bold Italic', 'Metropolis Extra Bold', 'Metropolis Extra Light Italic', 'Metropolis Extra Light', 'Metropolis Light Italic', 'Metropolis Light', 'Metropolis Medium Italic', 'Metropolis Medium', 'Metropolis Regular Italic', 'Metropolis Regular', 'Metropolis Semi Bold Italic', 'Metropolis Semi Bold', 'Metropolis Thin Italic', 'Metropolis Thin', 'Open Sans Bold Italic', 'Open Sans Bold', 'Open Sans Extrabold Italic', 'Open Sans Extrabold', 'Open Sans Italic', 'Open Sans Light Italic', 'Open Sans Light', 'Open Sans Regular', 'Open Sans Semibold Italic', 'Open Sans Semibold', 'Klokantech Noto Sans Bold', 'Klokantech Noto Sans CJK Bold', 'Klokantech Noto Sans CJK Regular', 'Klokantech Noto Sans Italic', and 'Klokantech Noto Sans Regular'.

Font Weight¶

New in 5.23

You can specify a numeric font weight on go.Scattermap with textfont.weight.

In [9]:

import plotly.graph_objects as go

fig = go.Figure(go.Scattermap(
    mode = "markers+text+lines",
    lon = [-75, -80, -50], lat = [45, 20, -20],
    marker = dict(size=20, symbol=["bus", "harbor", "airport"]),
    text = ["Bus", "Harbor", "airport"], textposition = "bottom right",
    textfont = dict(size=18, color="black", weight=900)
    ))

fig.update_layout(
    map = dict(
        style="outdoors", zoom=0.7),
    showlegend = False,)

fig.show()

Mapbox Maps¶

Mapbox traces are deprecated and may be removed in a future version of Plotly.py.

The earlier examples using px.scatter_map and go.Scattermap use Maplibre for rendering. These traces were introduced in Plotly.py 5.24 and are now the recommended way to create scatter plots on tile-based maps. There are also traces that use Mapbox: px.scatter_mapbox and go.Scattermapbox

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.

Here's the first example rewritten to use px.scatter_mapbox.

In [10]:

import plotly.express as px
px.set_mapbox_access_token(open(".mapbox_token").read())
df = px.data.carshare()
fig = px.scatter_mapbox(df, lat="centroid_lat", lon="centroid_lon",     color="peak_hour", size="car_hours",
                  color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=10)
fig.show()

And here's an example using Graph Objects:

In [11]:

import plotly.graph_objects as go

mapbox_access_token = open(".mapbox_token").read()

fig = go.Figure(go.Scattermapbox(
        lat=['45.5017'],
        lon=['-73.5673'],
        mode='markers',
        marker=go.scattermapbox.Marker(
            size=14
        ),
        text=['Montreal'],
    ))

fig.update_layout(
    hovermode='closest',
    mapbox=dict(
        accesstoken=mapbox_access_token,
        bearing=0,
        center=go.layout.mapbox.Center(
            lat=45,
            lon=-73
        ),
        pitch=0,
        zoom=5
    )
)

fig.show()

Reference¶

See function reference for px.scatter_map or https://plotly.com/python/reference/scattermap/ for more information about the attributes available.

For Mapbox-based tile maps, see function reference for px.scatter_mapbox or https://plotly.com/python/reference/scattermapbox/.

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_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter