Introduction to Python for Geographic Data Analysis: A new, open resource for teachers and learners

Digital geoscientific and geospatial datasets are rapidly growing in both number and size. These data present powerful new resources for understanding the evolution of the earth, but working with them requires computational skills are not part of typical geoscience curricula at universities. To leverage the power of these growing geoscientific and geospatial data, students need targeted educational resources that provide basic computational skills.

The new textbook Introduction to Python for Geographic Data Analysis provides a framework for learning to work with (geospatial) datasets of varying size from loading the data to producing interactive visualizations of processed data. Part 1 of the book covers the basics of programming using the Python language, introducing both programming concepts and their Python syntax. It also covers the analysis of tabular data using the pandas Python library and the basics of data visualization. Part 2 introduces working with geospatial data, including fundamental geospatial concepts, working with vector and raster data, geospatial data visualization, and loading data from online sources. Part 3 includes several case studies that build on things presented in the first two parts to demonstrate what can be done with the readers’ new skills. Finally, the appendices provide information about best practices in programing, version control with git and GitHub, and other practical coding tips that promote open, reproducible science.

The book materials are freely available online at https://pythongis.org, and we anticipate that hard copies of the book will be available later in 2026. We hope the book will appeal to a broad range of “geo” scientists, including teachers who provide courses on introductory programming or data analysis for geology and geography students, those interested in learning to interact with and batch process large datasets, and those interested in finding open-source alternatives to commercial GIS software packages.