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Lines on Mapbox in Python

How to draw a line 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.

To draw a line on your map, you either can use px.line_mapbox() in Plotly Express, or Scattermapbox traces. Below we show you how to draw a line on Mapbox using Plotly Express.

Lines on Mapbox maps using Plotly Express

In [1]:
import pandas as pd

us_cities = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/us-cities-top-1k.csv")
us_cities = us_cities.query("State in ['New York', 'Ohio']")

import plotly.express as px

fig = px.line_mapbox(us_cities, lat="lat", lon="lon", color="State", zoom=3, height=300)

fig.update_layout(mapbox_style="stamen-terrain", mapbox_zoom=4, mapbox_center_lat = 41,
    margin={"r":0,"t":0,"l":0,"b":0})

fig.show()

Lines on Mapbox maps using Scattermapbox traces

This example uses go.Scattermapbox and sets the mode attribute to a combination of markers and line.

In [2]:
import plotly.graph_objects as go

fig = go.Figure(go.Scattermapbox(
    mode = "markers+lines",
    lon = [10, 20, 30],
    lat = [10, 20,30],
    marker = {'size': 10}))

fig.add_trace(go.Scattermapbox(
    mode = "markers+lines",
    lon = [-50, -60,40],
    lat = [30, 10, -20],
    marker = {'size': 10}))

fig.update_layout(
    margin ={'l':0,'t':0,'b':0,'r':0},
    mapbox = {
        'center': {'lon': 10, 'lat': 10},
        'style': "stamen-terrain",
        'center': {'lon': -20, 'lat': -20},
        'zoom': 1})

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