Folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich …

GeoJSON/TopoJSON overlays # Folium supports both GeoJSON and TopoJSON data in various formats, such as urls, file paths and dictionaries.

The user guide covers different parts of basic usage of Folium. Each page focuses on a single topic and outlines how it is implemented in Folium, with reproducible examples.

[3]: folium.Map( location=(-38.625, -12.875), zoom_control=False, ) [3]: Make this Notebook Trusted to load map: File -> Trust Notebook Limits # You can set limits, so the map won’t scroll outside those …

Map tileset to use. Folium has built-in all tilesets available in the xyzservices package. For example, you can pass any of the following to the “tiles” keyword: ”OpenStreetMap” ”CartoDB Positron” ”CartoDB …

Advanced guide # Using folium with flask Integrating Jenks Natural Break Optimization with choropleth Subplots Using colormaps Scrolling beyond the world edge Panes and CustomPane Geodedetic …

Tiles # Built-in tilesets # [1]: import folium lon, lat = -38.625, -12.875 zoom_start = 8 [2]: folium.Map(location=[lat, lon], tiles="OpenStreetMap", zoom_start=zoom_start) [2]: Make this …

[6]: m = folium.Map([43, -100], zoom_start=4) folium.GeoJson(geo_json_data, zoom_on_click=True).add_to(m) m [6]: Make this Notebook Trusted to load map: File -> Trust …

import pandas state_data = pandas.read_csv( "https://raw.githubusercontent.com/python-visualization/folium-example-data/main/us_unemployment_oct_2012.csv" ) m = folium.Map([43, …

Now, let’s try to add a line at latitude 45°, and add a polyline to verify it’s well rendered. We’ll need to specify origin='lower to inform folium that the first lines of the array are to be plotted at the bottom of …