Agent skill · research science · aiskillstore
geopandas
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
Why this skill is useful
Provides specific commands and patterns for geospatial data analysis that the AI wouldn't reliably generate on its own.
What it needs
Requires cartopy, contextily, folium, geoalchemy2, geopandas, mapclassify, psycopg2, pyarrow installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
GeoPandas GeoPandas extends pandas to enable spatial operations on geometric types. It combines the capabilities of pandas and shapely for geospatial data analysis. Installation Optional Dependencies Quick Start Core Concepts Data Structures GeoSeries: Vector of geometries with spatial operations GeoDataFrame: Tabular data structure with geometry column See data-structures.md for details. Reading and Writing Data GeoPandas reads/writes multiple formats: Shapefile, GeoJSON, GeoPackage, PostGIS, Parquet. See data-io.md for comprehensive I/O operations. Coordinate Reference Systems Always check and manage CRS for accurate spatial operations: See crs-management.md for CRS operations. Common Operations Geometric Operations Buffer, simplify, centroid, convex hull, affine transformations: See geometric-operations.md for all operations. Spatial Analysis Spatial joins, overlay operations, dissolve: See spatial-analysis.md for analysis operations. Visualization Create static and interactive maps: See visualization.md for mapping techniques. Detailed Documentation Data Structures - GeoSeries and GeoDataFrame fundamentals Data I/O - Reading/writing files, PostGIS, Parquet Geometric Operations - Buffer, simplify, affine transforms Spatial Analysis - Joins, overlay, dissolve, clipping Visualization - Plotting, choropleth maps, interactive maps CRS Management - Coordinate reference systems and projections Common Workflows Load, Transform, Analyze, Export Spatial Join and Aggregate Multi-Source Data Integration Performance Tips 1. Use spatial indexing: GeoPandas creates spatial indexes automatically for most operations 2. Filter during read: Use bbox, mask, or where parameters to load only needed data 3. Use Arrow for I/O: Add usearrow=True for 2-4x faster reading/writing 4. Simplify geometries: Use .simplify() to reduce complexity when precision isn't critical 5. Batch operations: Vectorized operations are much faster than iterating rows 6. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/geopandas