GeoPandas Geospatial Analysis

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

pip install geopandas matplotlib
# Optional:
# 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

Quick Start

import geopandas as gpd

# Read spatial data
gdf = gpd.read_file("data.geojson")
print(f"Shape: {gdf.shape}, CRS: {gdf.crs}")
print(f"Geometry types: {gdf.geometry.geom_type.unique()}")