Getting Started with Kepler.gl in Jupyter Notebook: Installation, Basic Usage, and Export

Kepler.gl is an open‑source geospatial data visualization tool from Uber that can be used directly in Jupyter notebooks.

Installation – install via pip and, for notebook versions ≥5.3 on macOS, optionally run the nbextension commands.

pip install keplergl

jupyter nbextension install --py --sys-prefix keplergl
jupyter nbextension enable --py --sys-prefix keplergl

Simple example – creating a KeplerGl object and displaying an empty map.

from keplergl import KeplerGl
map_1 = KeplerGl(height=500)
map_1

Adding data – Kepler.gl accepts CSV, GeoJSON, or DataFrame. Example loads a CSV with pandas and adds it to the map.

import pandas as pd
df = pd.read_csv('rocket_launch_site_elevation_2019-10-27.csv')
map_2 = KeplerGl(height=600)
map_2.add_data(name='rocket', data=df)
map_2

Customizing charts – most visual settings are handled through the UI, unlike libraries such as pyecharts or matplotlib.

Getting configuration – the current map configuration can be retrieved with .config and reused.

config = map_2.config

Exporting the map – use .save_to_html() to export the map to an HTML file, optionally setting the file name and read‑only flag.

map_3.save_to_html(file_name='kepler_example.html')

Overall, Kepler.gl provides an easy‑to‑use, UI‑driven way to create attractive geospatial visualizations without writing extensive configuration code.