geopandas-geospatial
Geospatial vector analysis extending pandas. Read/write spatial formats (Shapefile, GeoJSON, GeoPackage, Parquet, PostGIS), CRS handling, geometric ops (buffer, simplify, centroid, affine), spatial analysis (joins, overlays, dissolve, clipping, distance), visualization (choropleth, interactive maps, basemaps). Use for spatial joins, overlays, CRS transforms, area/distance, maps.
npx skills add BioTender-max/awesome-bio-agent-skills --skill geopandas-geospatial --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# GeoPandas Geospatial Analysis ## Overview GeoPandas extends pandas with spatial operations on geometric types, combining pandas DataFrames with Shapely geometries and Fiona for file I/O. It enables reading, writing, manipulating, and visualizing geospatial vector data (points, lines, polygons) with a familiar pandas-like API. ## When to Use - Reading and writing spatial file formats (Shapefile, GeoJSON, GeoPackage, Parquet) - Performing spatial joins between geographic datasets (points in polygons, nearest neighbors) - Running overlay operations (intersection, union, difference, clipping) - Computing geometric properties (area, distance, buffer, centroid) - Creating choropleth maps and interactive web maps - Reprojecting data between coordinate reference systems - Aggregating spatial features by attribute (dissolve) - For raster data analysis, use rasterio/xarray instead - For large-scale distributed geospatial, consider Dask-GeoPandas or Apache Sedona ## Prerequisites ```bash pip install geopandas matplotlib # Optional: # pip install folium — interactive maps # pip install mapclassify — classification schemes for choropleth # pip install contextily — basemaps # pip install pyarr
- Overview
- When to Use
- Prerequisites
- Quick Start
- Core API
- 1. Data I/O
- 2. CRS Management
- 3. Geometric Operations
- 4. Spatial Analysis
- 5. Visualization
- Key Concepts
- Data Structures
- CRS Rules for Spatial Operations
- Spatial Indexing
pip install geopandas matplotlib pip install folium — interactive maps pip install mapclassify — classification schemes for choropleth pip install contextily — basemaps pip install pyarrow — faster I/O (2-4x speedup) pip install psycopg2 geoalchemy2 — PostGIS support
What does the geopandas-geospatial skill do?
Geospatial vector analysis extending pandas. Read/write spatial formats (Shapefile, GeoJSON, GeoPackage, Parquet, PostGIS), CRS handling, geometric ops (buffer, simplify, centroid, affine), spatial analysis (joins, overlays, dissolve, clipping, distance), visualization (choropleth, interactive maps, basemaps). Use for spatial joins, overlays, CRS transforms, area/distance, maps.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill geopandas-geospatial --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.