Geocomputation with Python

This resource is the online home of Geocomputation with Python, a book on reproducible geographic data analysis with open source software created by the authors: Michael Dorman, Anita Graser, Jakub Nowosad, and Robin Lovelace.

Geocomputation with Python (geocompy) is motivated by the need for an introductory, yet rigorous and up-to-date, resource geographic data with the most popular programming language in the world.
A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve.
We aim to minimize surprises, with each section and chapter building on the previous.
If you’re just starting out with Python for working with geographic data, this book is an excellent place to start.

There are many resources on Python on ‘GeoPython’ but none that fill this need for an introductory resource that provides strong foundations for future work.
We want to avoid reinventing the wheel and provide something that fills an ‘ecological niche’ in the wider free and open source software for geospatial (FOSS4G) ecosystem. Key features include:

• Doing basic operations
• Integration of vector and raster datasets and operations
• Clear explanation of each line of code in the book to minimize surprises
• Excercises at the end of each chapter with reproducible and open solutions
• Provision of lucid example datasets and meaningful operations to illustrate the applied nature of geographic research