Geospatial Data Science Essentials: 101 Practical Python Tips and Tricks

Geospatial Data Science Essentials is a hands-on guide to geospatial analytics with Python. It distills 101 core concepts — from theory to implementation — into practical, reproducible examples that reflect how geospatial data science is actually used today.Written for data scientists, GIS professionals, and technically inclined newcomers to spatial data, the book focuses on real-world workflows rather than abstract theory. Across ten thematic chapters and 101 short sections, you will work with compact code examples covering spatial data structures, vector and raster processing, visualization, map projections, spatial indexing, OpenStreetMap data, spatial networks, and geospatial statistics and machine learning.This second edition reflects updates in the geospatial Python ecosystem, including library updates, bug fixes, and new examples aligned with recent versions of tools such as GeoPandas and OSMnx. Whether you are building analytical pipelines, exploring spatial patterns, or extending your existing Python skill set into the geospatial domain, this book provides a practical foundation for working confidently with spatial data. Read more