geopandas
Geographic pandas extensions
Decision gist · record as of 2026-08-14
Yes. GeoPandas is a mature, actively maintained library (Production/Stable status, 5223 stars) with low install friction and no known vulnerabilities. Its permissive BSD-3-Clause license poses no restrictions. Install it if you work with geographic data in Python and want to avoid setting up a spatial database or learning a separate GIS tool.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; pyogrio (a runtime dependency) may require system libraries on some platforms.
- Low install friction with a pure-Python wheel distribution.
- Active maintenance with recent releases; repository shows 5223 stars and last commit on 2026-08-12.
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause permissive license allows commercial use, modification, and distribution with minimal restrictions—suitable for most projects.
last release 2026-06-26 (49 days) · last repo commit 2026-08-12 · 5,223 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 24,795,060 downloads/mo, #912 on PyPI
Alternatives
Verify before relying
pip install geopandas
import geopandas as gpd
from shapely.geometry import Point
gdf = gpd.GeoDataFrame(
{'name': ['A', 'B']},
geometry=[Point(0, 0), Point(1, 1)]
)- Whether pyogrio's system-level dependencies (e.g., GDAL) are commonly pre-installed or require additional setup on typical developer machines.
- Performance characteristics when working with very large geographic datasets.
- Specific spatial database operations that GeoPandas can replicate versus those requiring PostGIS or similar tools.
What it is and what it does
GeoPandas is a Python library that brings geospatial capabilities to the pandas ecosystem. It wraps shapely geometries inside pandas DataFrames, letting you apply familiar pandas operations (filtering, grouping, merging) to geographic data while also providing spatial operations like intersection, union, and distance calculations. This eliminates the need to move data to a spatial database like PostGIS for many common GIS tasks.
The library is built on six core runtime dependencies: numpy for numerical operations, pandas for tabular data, shapely for geometric primitives, pyproj for coordinate system transformations, pyogrio for reading and writing geographic file formats, and packaging for version handling. It targets Python 3.10+ and is actively maintained, making it suitable for production geospatial analysis workflows in Python.
Use it for
- Load shapefiles or GeoJSON data and filter geographic features by attributes or spatial relationships without a database.
- Perform spatial joins to combine datasets based on geographic proximity or overlap.
- Calculate distances, areas, and centroids for geographic features in a familiar pandas-like workflow.
- Transform coordinate systems across multiple geographic datasets in bulk.
- Visualize geographic data by plotting GeoDataFrames directly or exporting to web mapping libraries.
- Combine census, climate, or survey data with geographic boundaries for regional analysis.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
GeoPandas is a mature, actively maintained library (Production/Stable status, 5223 stars) with low install friction and no known vulnerabilities. Its permissive BSD-3-Clause license poses no restrictions. Install it if you work with geographic data in Python and want to avoid setting up a spatial database or learning a separate GIS tool.
Install
geopandas on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Active maintenance with recent releases; repository shows 5223 stars and last commit on 2026-08-12. Requires Python 3.10 or later.
Requires Python 3.10 or later; pyogrio (a runtime dependency) may require system libraries on some platforms.
License in practice
BSD-3-Clause permissive license allows commercial use, modification, and distribution with minimal restrictions—suitable for most projects.
Quickstart
pip install geopandas
import geopandas as gpd
from shapely.geometry import Point
gdf = gpd.GeoDataFrame(
{'name': ['A', 'B']},
geometry=[Point(0, 0), Point(1, 1)]
)Verify before relying
- Whether pyogrio's system-level dependencies (e.g., GDAL) are commonly pre-installed or require additional setup on typical developer machines.
- Performance characteristics when working with very large geographic datasets.
- Specific spatial database operations that GeoPandas can replicate versus those requiring PostGIS or similar tools.
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesnumpypyogriopackagingpandaspyprojshapely |
| Maintenance | Actively maintained 49 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 24,795,060 / month, #912 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: Science/ResearchOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyTopic :: Scientific/Engineering :: GIS |
Evidence: geopandas-1.1.4-py3-none-any.whl
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More GIS packages
Shapely provides Python tools for creating, manipulating, and analyzing 2D geometric objects (points, lines, polygons) using the GEOS library, with both scalar and vectorized NumPy-based operations.
pyproj provides a Python interface to PROJ, enabling cartographic projections and coordinate system transformations for geospatial applications.
geopy is a Python client for geocoding and distance calculation that converts addresses to coordinates and vice versa using multiple web-based geocoding services, and computes geodesic and great-circle distances between geographic points.
Install it if you need geocoding or distance calculations in your application.
Pyogrio provides fast, bulk-oriented read and write access to vector spatial data formats (Shapefile, GeoPackage, GeoJSON, etc.) via GDAL/OGR bindings, typically for use with GeoPandas GeoDataFrames.
h3 provides Python bindings to Uber's H3 geospatial indexing library, converting geographic coordinates into hierarchical hexagonal grid cells and performing spatial operations on them.
Fiona reads and writes vector GIS data (Shapefile, GeoPackage, etc.) via a Python API and command-line interface, wrapping GDAL with a focus on readable, productive code.
See also dask-geopandas · geodatasets · reproj · tobler · antimeridian · pandas · apache-sedona · arcgis · pygeos