Book review: Python for ArcGIS Pro
As GIS has evolved to become a web based platform, Python is now an essential tool for many GIS practitioners to be successful with GIS. Silas Toms and Bill Parker’s book Python for ArcGIS Pro from Packt Publishing provides a hands-on, engaging way to gain these core Python skills in a GIS context. Indeed, as Rene Rubalcava states in the foreword for this book, if you need to perform analysis, there’s a Python library available for it. The book provides ways for the new as well as the experienced programmer to start engaging with these tools right away, through a wide variety of tools including ArcPy, the ArcGIS API for Python, and Notebooks. I have long had great respect for the GIS books from Packt, and this book upheld my high regard for this publisher. The book’s two authors have a combined 30+ years of GIS experience behind them, and this experience shows through their attention to detail. They are knowledgeable and they make good instructors, which is a wonderful combination.
As a GIS instructor, I appreciate the fine line that GIS book authors need to take in terms of the amount of detail and guidance they provide in instruction. The book’s authors provide the right amount of detail for each activity, not too much minutae but just enough to keep the reader on task without getting lost. The screen shots are in black and white but are in sharp detail, are very helpful, and again, are provided in just the right amount. The data for the book including code files are stored on GitHub and are easily accessed. The book is available in digital and in print form.
The book’s organization makes its content wonderfully digestible: Part I’s introduction includes describing what Python for GIS is and why it is an important set of tools, and the basics of programming, including data structures, data types, and conditionals. ArcPy basics and the ArcGIS API for Python are also covered in Part I. Part II focuses on applying Python through modules, including publishing to ArcGIS Online and automated map production. My favorite part of Part II is where the authors explain how to turn scripts into tools. These tools become a custom toolbox which can be run like any ArcGIS tool and which also can be shared—very powerful! Part III digs into geospatial data analysis, an introduction to Pandas, vector and raster data structures, and NumPy for geospatial data processing. Part IV’s case studies are varied and interesting, covering such topics as crop yields and other themes at a variety of scales.
This book can be used by people new to coding and new to GIS, as well as by seasoned GIS professionals who seek to keep learning. It can be used in its entirety or by selecting specific tools and activities that the reader is seeking to learn more about. I found the book to be extremely valuable (my review on Amazon is here) in my own journey forward, and I trust you will as well.
