GeoPandas extends pandas with support for geospatial data types and operations, enabling spatial analysis and geographic data manipulation in Python. Built on shapely, fiona/pyogrio, and pyproj, GeoPandas provides GeoDataFrame and GeoSeries structures that seamlessly integrate spatial geometries with tabular data. Starting with version 1.0 (June 2024), pyogrio is the default I/O engine and PyGEOS support has been dropped in favour of shapely ≥ 2; version 1.1 (June 2025) added coverage operations, M-coordinate support, and many new shapely-backed methods.
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This topic spans 17 focused tables and 203 indexed concepts, 121 flashcards. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
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Table 1: Installation & Setup
GeoPandas depends on shapely, pyogrio, and pyproj; the cleanest install is via conda, which resolves all GDAL-level binaries automatically. Version 1.1 requires Python ≥ 3.10 and pandas ≥ 2.0; version 1.2 raises this to Python ≥ 3.11 and numpy ≥ 2.0.
| Command | Example | Description | |
|---|---|---|---|
conda install -c conda-forge geopandas | Recommended install — resolves GDAL binaries automatically | ||
pip install geopandas | Installs GeoPandas with core dependencies (shapely, pyogrio, pyproj) | ||
pip install geopandas[all] | Installs with matplotlib, contextily, folium, and pyarrow for mapping | ||
pip install geopandas pyarrow | Adds pyarrow for Arrow-accelerated I/O (required for use_arrow=True) | ||
import geopandas as gpd | Standard import convention for GeoPandas | ||
gpd.__version__ | Returns installed GeoPandas version (1.1.3 is latest stable, May 2026) | ||
pip install geodatasets | Installs sample datasets (replaces removed gpd.datasets module) |