Lines on Tile Maps in Python
How to draw a line on tile-based maps in Python with Plotly.
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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.
Lines on tile maps using Plotly Express¶
To draw a line on a map, you either can use px.line_map
in Plotly Express, or go.Scattermap
in Plotly Graph Objects. Here's an example of drawing a line on a tile-based map 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_map(us_cities, lat="lat", lon="lon", color="State", zoom=3, height=300)
fig.update_layout(map_style="open-street-map", map_zoom=4, map_center_lat = 41,
margin={"r":0,"t":0,"l":0,"b":0})
fig.show()
Lines on maps from GeoPandas¶
Given a GeoPandas geo-data frame with linestring
or multilinestring
features, one can extra point data and use px.line_map
.
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_map(lat=lats, lon=lons, hover_name=names,
map_style="open-street-map", zoom=1)
fig.show()
import plotly.graph_objects as go
fig = go.Figure(go.Scattermap(
mode = "markers+lines",
lon = [10, 20, 30],
lat = [10, 20,30],
marker = {'size': 10}))
fig.add_trace(go.Scattermap(
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},
map = {
'center': {'lon': 10, 'lat': 10},
'style': "open-street-map",
'center': {'lon': -20, 'lat': -20},
'zoom': 1})
fig.show()
Mapbox Maps¶
Mapbox traces are deprecated and may be removed in a future version of Plotly.py.
The earlier examples using px.line_map
and go.Scattermap
use Maplibre for rendering. These traces were introduced in Plotly.py 5.24 and are now the recommended way to draw lines on tile-based maps. There are also traces that use Mapbox: px.line_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.
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.
Here's an example of using Scattermapbox
.
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_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.line_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