Geographic Data Science with Python

"The geospatial Python ecosystem is evolving rapidly, and until now there has been no one-stop reference for the geospatial programmer on data I/O, spatial analysis, and geovisualization. I will use this book in my teaching and will also recommend it to students as a book to keep on the shelf and use as a supplement to other courses, for independent projects, and for their future careers. I don't think there is anything quite like it in the market."
-Professor Lee Hachadoorian, Temple University

"Geographic Data Science with Python is an essential resource for data scientists looking to extend their skills into the geographic domain and for geographers looking to add data science skills. The book's approach achieves a highly effective balance between introducing theoretical concepts and applying them to practical examples. The book also serves as a guide to the modern open source spatial Python stack. The accompanying interactive Jupyter notebooks are great resources for running what-if scenarios to extend the concepts introduced in the book and for getting started with new projects. If you want to understand the unique properties of spatial data and how to apply them in creative ways using Python, this book is a must have."
- David C. Folch, Associate Professor, Northern Arizona University

"Three things will stand out after taking a close look at this book. First, the authors present a timely book that is like an encyclopedia of the emerging field of geographic data science. This book will aspire geographers with what data science can do in helping them answer questions with spatial data, and data scientists in providing critical spatial and methodological contexts of the data. For this reason, this book provides what the seemingly countless tutorials out there in the digital cloud cannot do: a wholistic view of the landscape that may often be daunting to grasp by both communities. Second, the core of this book comes from years of intensive software development of the authors. Their experience (and hard work) has made reading this book a treasure hunt -- not necessarily the challenging sort because you can find good stuff everywhere you turn. Lastly, this is an "open" book because of the Jupyter notebooks associated with this book that are ready to use and, more importantly, to extend to new problems and applications. Because of these features, this book transcends a traditional GIS textbook or how-to tech book and is highly recommended for anyone wishing to understand geographic data."
- Ningchuan Xiao, Professor, The Ohio State University