Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence

by Bonny McClain

In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. This book helps

262 pages, Paperback

Published November 29, 2022

Reviews

[William Dollins · Rating 4 out of 5]

Python is widespread in geospatial and this book covers most of the bases: QGIS, Google Earth Engine, GeoPandas, GDAL/OGR, and ArcGIS. It is a great jumping-off point and, using the information here, you can begin deeper exploration of using Python with any of these platforms. If, like me, you find yourself switching between many of them, this book is a great resource.

This book assumes you already have some understanding of GIS and spatial analysis, which is a reasonable assumption. It does not attempt to teach you GIS in a single book. If you are a Python developer who is new to geospatial or if you are a GIS analyst new to Python development, this book will get you pointed in the right direction. If you choose only one book on working with geospatial Python, make it this one. You'll gain a foundation you can build upon for future work.