A Python library for fast, interactive geospatial vector data visualization in Jupyter.
Building on cutting-edge technologies like GeoArrow and GeoParquet in conjunction with GPU-based map rendering, Lonboard aims to enable visualizing large geospatial datasets interactively through a simple interface.
3 million points rendered from a GeoPandas GeoDataFrame in JupyterLab. Example notebook.
To install Lonboard using pip:
Lonboard is on conda-forge and can be installed using conda, mamba, or pixi. To install Lonboard using conda:
conda install -c conda-forge lonboard
To install from source, refer to the developer documentation.
For the simplest rendering, pass geospatial data into the top-level viz function.
import geopandas as gpd from lonboard import viz gdf = gpd.GeoDataFrame(...) viz(gdf)
Under the hood, this delegates to a ScatterplotLayer, PathLayer, or PolygonLayer. Refer to the documentation and examples for more control over rendering.
Refer to the documentation at developmentseed.org/lonboard.
This is a new binding to the deck.gl geospatial data visualization library. A "deck" is the part of a skateboard you ride on. What's a fast, geospatial skateboard? A lonboard.
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