Ipyleaflet

12. Ipyleaflet#

Open In Colab

12.1. Introduction#

ipyleaflet is a Python library that brings the power of Leaflet.js to Jupyter Notebooks. It allows interactive mapping, geospatial visualization, and dynamic map customization with widgets.

12.1.1. Learning Objectives#

By the end of this lecture, you will:

  • Understand what ipyleaflet is and how it differs from Folium.

  • Learn to create basic maps and add markers.

  • Explore how to use geospatial layers and data.

  • Customize maps with widgets and interactivity.

12.2. 1. Installing and Importing ipyleaflet#

To install ipyleaflet, run the following command:

pip install ipyleaflet

Then, import it in Python:

from ipyleaflet import Map, Marker

12.3. 2. Creating a Basic Map#

A simple ipyleaflet map can be created as follows:

m = Map(center=(37.7749, -122.4194), zoom=10)
m

12.3.1. Map Parameters#

  • center: The latitude and longitude of the map center.

  • zoom: The initial zoom level.

12.4. 3. Adding Markers#

Markers help highlight specific locations on the map.

marker = Marker(location=(37.7749, -122.4194))
m.add_layer(marker)
m

12.5. 4. Adding Tile Layers#

Different tile layers can be used to change the appearance of the map.

from ipyleaflet import TileLayer

m.add_layer(TileLayer(url="https://{s}.tile.opentopomap.org/{z}/{x}/{y}.png"))
m

Common tile providers:

  • OpenStreetMap

  • Stamen Terrain

  • CartoDB DarkMatter

12.6. 5. Adding GeoJSON Layers#

GeoJSON files allow visualization of geospatial boundaries.

from ipyleaflet import GeoJSON
import json

data = {
    "type": "FeatureCollection",
    "features": [
        {
            "type": "Feature",
            "geometry": {"type": "Point", "coordinates": [-122.4194, 37.7749]},
            "properties": {"name": "San Francisco"},
        }
    ],
}

gj = GeoJSON(data=data)
m.add_layer(gj)
m

12.7. 6. Adding a Choropleth Layer#

Choropleth maps visualize geographic data distributions.

from ipyleaflet import Choropleth
import pandas as pd

# Example data
geojson_url = (
    "https://raw.githubusercontent.com/johan/world.geo.json/master/countries.geo.json"
)
data = {"USA": 100, "CAN": 50, "MEX": 75}

choro = Choropleth(geo_data=geojson_url, choro_data=data, key_on="id")
m.add_layer(choro)
m

12.8. 7. Adding Layer Controls#

To toggle layers dynamically:

from ipyleaflet import LayersControl

m.add_control(LayersControl())
m

12.9. 8. Adding Interactive Widgets#

Widgets enable real-time interaction with the map.

from ipywidgets import FloatSlider

zoom_slider = FloatSlider(description="Zoom Level", min=1, max=20, value=m.zoom)


def zoom_change(change):
    m.zoom = change["new"]


zoom_slider.observe(zoom_change, "value")
zoom_slider

12.10. Summary#

  • ipyleaflet enables interactive mapping in Jupyter Notebooks.

  • Supports markers, tile layers, GeoJSON, and choropleth maps.

  • Interactive widgets enhance user experience.

  • Suitable for real-time geospatial data visualization.

12.11. Further Reading#

Contents