Lines on Mapbox in Python
How to draw a line on Map in Python with Plotly.
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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¶
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="open-street-map", mapbox_zoom=4, mapbox_center_lat = 41,
margin={"r":0,"t":0,"l":0,"b":0})
fig.show()
Lines on Mapbox maps from GeoPandas¶
Given a GeoPandas geo-data frame with linestring
or multilinestring
features, one can extra point data and use px.line_mapbox()
.
import plotly.express as px
import geopandas as gpd
import shapely.geometry
import numpy as np
import wget
# download a zipped shapefile
wget.download("https://plotly.github.io/datasets/ne_50m_rivers_lake_centerlines.zip")
# open a zipped shapefile with the zip:// pseudo-protocol
geo_df = gpd.read_file("zip://ne_50m_rivers_lake_centerlines.zip")
lats = []
lons = []
names = []
for feature, name in zip(geo_df.geometry, geo_df.name):
if isinstance(feature, shapely.geometry.linestring.LineString):
linestrings = [feature]
elif isinstance(feature, shapely.geometry.multilinestring.MultiLineString):
linestrings = feature.geoms
else:
continue
for linestring in linestrings:
x, y = linestring.xy
lats = np.append(lats, y)
lons = np.append(lons, x)
names = np.append(names, [name]*len(y))
lats = np.append(lats, None)
lons = np.append(lons, None)
names = np.append(names, None)
fig = px.line_mapbox(lat=lats, lon=lons, hover_name=names,
mapbox_style="open-street-map", zoom=1)
fig.show()
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': "open-street-map",
'center': {'lon': -20, 'lat': -20},
'zoom': 1})
fig.show()
Reference¶
See function reference for px.(line_mapbox)
or
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( ... )
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