geodatasets
Spatial data examples
Decision gist · record as of 2026-08-14
Yes. Geodatasets is actively maintained, has no security vulnerabilities, installs with minimal friction, and solves a real problem for anyone teaching or learning GIS—reliable access to example spatial data. The permissive BSD license poses no restrictions. Install it if you're building tutorials, examples, or educational materials that need geospatial datasets.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction with a single runtime dependency (pooch).
- The package is actively maintained with recent releases and no known vulnerabilities.
License · maintenance · safety
BSD 3-Clause (permissive) — BSD 3-Clause is a permissive license allowing commercial and private use with minimal restrictions, making this package safe to use in most projects.
last release 2026-05-18 (88 days) · last repo commit 2026-05-18 · 76 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 181,536 downloads/mo, #10,123 on PyPI
Alternatives
Verify before relying
pip install geodatasets
import geodatasets
# Get URL for a dataset
url = geodatasets.get_url('geoda airbnb')
# Download and cache, then get local path
path = geodatasets.get_path('geoda airbnb')- Whether the cached datasets persist across Python sessions or require re-download
- Cache size limits or cleanup strategies for long-term use
- Whether all datasets remain accessible or if URLs are subject to change
What it is and what it does
Geodatasets is a lightweight package that manages a curated registry of geospatial datasets hosted externally. It wraps a JSON metadata store describing datasets from sources like GeoDA, Natural Earth, and EEA, providing a simple Python API to query dataset information, retrieve download URLs, or fetch and cache files locally. The package uses pooch for download and caching, so you can reference datasets by name and get either a direct URL or a local file path—downloading only if the file isn't already cached.
It's designed for data scientists, educators, and GIS practitioners who need reliable sample datasets for tutorials, examples, or quick analysis without manually managing downloads. The registry includes dozens of datasets covering topics like urban crime, health indicators, economic data, and natural features, each with metadata about geometry type, dimensions, and attribution.
Use it for
- Load example datasets in Jupyter notebooks for GIS tutorials or demonstrations without manual downloads
- Provide consistent sample data across educational materials or training courses
- Quickly prototype spatial analysis workflows with known, well-documented datasets
- Build reproducible examples in documentation or blog posts using cached geospatial data
- Access pre-vetted datasets with proper attribution and license information for research
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Geodatasets is actively maintained, has no security vulnerabilities, installs with minimal friction, and solves a real problem for anyone teaching or learning GIS—reliable access to example spatial data. The permissive BSD license poses no restrictions. Install it if you're building tutorials, examples, or educational materials that need geospatial datasets.
Install
geodatasets on PyPI
Before you install
Low install friction with a single runtime dependency (pooch). The package is actively maintained with recent releases and no known vulnerabilities.
License in practice
BSD 3-Clause is a permissive license allowing commercial and private use with minimal restrictions, making this package safe to use in most projects.
Quickstart
pip install geodatasets
import geodatasets
# Get URL for a dataset
url = geodatasets.get_url('geoda airbnb')
# Download and cache, then get local path
path = geodatasets.get_path('geoda airbnb')Verify before relying
- Whether the cached datasets persist across Python sessions or require re-download
- Cache size limits or cleanup strategies for long-term use
- Whether all datasets remain accessible or if URLs are subject to change
Package facts
| License | BSD 3-Clause permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepooch |
| Maintenance | Actively maintained 88 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 181,536 / month, #10,123 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Topic :: Scientific/Engineering :: GIS |
Evidence: geodatasets-2026.5.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “geospatial example datasets”
- geodatasetsGeodatasets provides a curated database of geospatial example…
- libpysallibpysal provides core spatial analysis building blocks—computational…
- torchgeoTorchGeo provides PyTorch datasets, samplers, transforms, and…
Give your agent the search over MCP, or paste the wish link into any chat.
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.
GeoPandas extends pandas DataFrames to handle geographic data, combining pandas operations with shapely geometry and spatial analysis capabilities that would otherwise require a spatial database.
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.
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.
See also dask-geopandas · arcgis · access · GeoAlchemy2 · overturemaps · odc-loader · spatial-access · open-radar-data · tensorflow-datasets