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description display_as language layout name order page_type permalink thumbnail
How to draw lines, great circles, and contours on maps in Python.
maps
python
base
Lines on Maps
6
u-guide
python/lines-on-maps/
thumbnail/flight-paths.jpg

Below we show how to create geographical line plots using either Plotly Express with px.line_geo function or the lower-level go.Scattergeo object.

Base Map Configuration

Plotly figures made with Plotly Express px.scatter_geo, px.line_geo or px.choropleth functions or containing go.Choropleth or go.Scattergeo graph objects have a go.layout.Geo object which can be used to control the appearance of the base map onto which data is plotted.

Lines on Maps 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.

import plotly.express as px
df = px.data.gapminder().query("year == 2007")
fig = px.line_geo(df, locations="iso_alpha",
                  color="continent", # "continent" is one of the columns of gapminder
                  projection="orthographic")
fig.show()

Lines on Maps with plotly.graph_objects

US Flight Paths Map

import plotly.graph_objects as go
import pandas as pd

df_airports = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv')
df_airports.head()

df_flight_paths = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_aa_flight_paths.csv')
df_flight_paths.head()

fig = go.Figure()

fig.add_trace(go.Scattergeo(
    locationmode = 'USA-states',
    lon = df_airports['long'],
    lat = df_airports['lat'],
    hoverinfo = 'text',
    text = df_airports['airport'],
    mode = 'markers',
    marker = dict(
        size = 2,
        color = 'rgb(255, 0, 0)',
        line = dict(
            width = 3,
            color = 'rgba(68, 68, 68, 0)'
        )
    )))

flight_paths = []
for i in range(len(df_flight_paths)):
    fig.add_trace(
        go.Scattergeo(
            locationmode = 'USA-states',
            lon = [df_flight_paths['start_lon'][i], df_flight_paths['end_lon'][i]],
            lat = [df_flight_paths['start_lat'][i], df_flight_paths['end_lat'][i]],
            mode = 'lines',
            line = dict(width = 1,color = 'red'),
            opacity = float(df_flight_paths['cnt'][i]) / float(df_flight_paths['cnt'].max()),
        )
    )

fig.update_layout(
    title_text = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
    showlegend = False,
    geo = dict(
        scope = 'north america',
        projection_type = 'azimuthal equal area',
        showland = True,
        landcolor = 'rgb(243, 243, 243)',
        countrycolor = 'rgb(204, 204, 204)',
    ),
)

fig.show()

Performance improvement: put many lines in the same trace

For very large amounts (>1000) of lines, performance may become critcal. If you can relinquish setting individual line styles (e.g. opacity), you can put multiple paths into one trace. This makes the map render faster and reduces the script execution time and memory consumption.

Use None between path coordinates to create a break in the otherwise connected paths.

import plotly.graph_objects as go
import pandas as pd

df_airports = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv')
df_airports.head()

df_flight_paths = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_aa_flight_paths.csv')
df_flight_paths.head()

fig = go.Figure()

fig.add_trace(go.Scattergeo(
    locationmode = 'USA-states',
    lon = df_airports['long'],
    lat = df_airports['lat'],
    hoverinfo = 'text',
    text = df_airports['airport'],
    mode = 'markers',
    marker = dict(
        size = 2,
        color = 'rgb(255, 0, 0)',
        line = dict(
            width = 3,
            color = 'rgba(68, 68, 68, 0)'
        )
    )))

lons = []
lats = []
import numpy as np
lons = np.empty(3 * len(df_flight_paths))
lons[::3] = df_flight_paths['start_lon']
lons[1::3] = df_flight_paths['end_lon']
lons[2::3] = None
lats = np.empty(3 * len(df_flight_paths))
lats[::3] = df_flight_paths['start_lat']
lats[1::3] = df_flight_paths['end_lat']
lats[2::3] = None

fig.add_trace(
    go.Scattergeo(
        locationmode = 'USA-states',
        lon = lons,
        lat = lats,
        mode = 'lines',
        line = dict(width = 1,color = 'red'),
        opacity = 0.5
    )
)

fig.update_layout(
    title_text = 'Feb. 2011 American Airline flight paths<br>(Hover for airport names)',
    showlegend = False,
    geo = go.layout.Geo(
        scope = 'north america',
        projection_type = 'azimuthal equal area',
        showland = True,
        landcolor = 'rgb(243, 243, 243)',
        countrycolor = 'rgb(204, 204, 204)',
    ),
    height=700,
)

fig.show()

London to NYC Great Circle

import plotly.graph_objects as go

fig = go.Figure(data=go.Scattergeo(
    lat = [40.7127, 51.5072],
    lon = [-74.0059, 0.1275],
    mode = 'lines',
    line = dict(width = 2, color = 'blue'),
))

fig.update_layout(
    title_text = 'London to NYC Great Circle',
    showlegend = False,
    geo = dict(
        resolution = 50,
        showland = True,
        showlakes = True,
        landcolor = 'rgb(204, 204, 204)',
        countrycolor = 'rgb(204, 204, 204)',
        lakecolor = 'rgb(255, 255, 255)',
        projection_type = "equirectangular",
        coastlinewidth = 2,
        lataxis = dict(
            range = [20, 60],
            showgrid = True,
            dtick = 10
        ),
        lonaxis = dict(
            range = [-100, 20],
            showgrid = True,
            dtick = 20
        ),
    )
)

fig.show()

Contour lines on globe

import plotly.graph_objects as go
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/globe_contours.csv')
df.head()


scl = ['rgb(213,62,79)', 'rgb(244,109,67)', 'rgb(253,174,97)', \
    'rgb(254,224,139)', 'rgb(255,255,191)', 'rgb(230,245,152)', \
    'rgb(171,221,164)', 'rgb(102,194,165)', 'rgb(50,136,189)'
]
n_colors = len(scl)

fig = go.Figure()

for i, (lat, lon) in enumerate(zip(df.columns[::2], df.columns[1::2])):
    fig.add_trace(go.Scattergeo(
        lon = df[lon],
        lat = df[lat],
        mode = 'lines',
        line = dict(width = 2, color = scl[i % n_colors]
        )))

fig.update_layout(
    title_text = 'Contour lines over globe<br>(Click and drag to rotate)',
    showlegend = False,
    geo = dict(
        showland = True,
        showcountries = True,
        showocean = True,
        countrywidth = 0.5,
        landcolor = 'rgb(230, 145, 56)',
        lakecolor = 'rgb(0, 255, 255)',
        oceancolor = 'rgb(0, 255, 255)',
        projection = dict(
            type = 'orthographic',
            rotation = dict(
                lon = -100,
                lat = 40,
                roll = 0
            )
        ),
        lonaxis = dict(
            showgrid = True,
            gridcolor = 'rgb(102, 102, 102)',
            gridwidth = 0.5
        ),
        lataxis = dict(
            showgrid = True,
            gridcolor = 'rgb(102, 102, 102)',
            gridwidth = 0.5
        )
    )
)

fig.show()

Reference

See https://plotly.com/python/reference/scattergeo/ for more information and chart attribute options!