Geographic Data Science with Python By Sergio Rey, Dani Arribas-Bel, and Levi John Wolf is an English-language textbook focused on geographic data science. This book covers the combination of geographic data and data science, offering practical insights for professionals and students at higher education levels.
The book introduces a systematic approach to geographic data analysis, applying geographic and computational methods within the Python environment. It covers essential concepts such as spatial data, mapping, and spatial statistics, and highlights clusters and outliers from a geographic perspective.
Geographic Data Science with Python provides concrete examples and methods that are directly applicable for data scientists, GIScientists, and geographers. It helps readers replicate, adapt, and extend analyses using Python, unlocking new insights into geographic data.
The content aligns with topics such as geographic information systems, remote sensing, web programming, and technology within engineering, specifically in the fields of remote sensing and GIS.
Series: Chapman & Hall/CRC Texts in Statistical Science