Book Image

Applied Geospatial Data Science with Python

By : David S. Jordan
3 (1)
Book Image

Applied Geospatial Data Science with Python

3 (1)
By: David S. Jordan

Overview of this book

Data scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python. Throughout this book, you’ll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You’ll learn how to read, process, and manipulate spatial data effectively. With data in hand, you’ll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you’ll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries. By the end of the book, you’ll be able to tackle random data, find meaningful correlations, and make geospatial data models.
Table of Contents (17 chapters)
Part 1:The Essentials of Geospatial Data Science
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Chapter 1: Introducing Geographic Information Systems and Geospatial Data Science
Part 2: Exploratory Spatial Data Analysis
Part 3: Geospatial Modeling Case Studies

Working with GCS and PCS in Python

While we have not yet taken a deep dive into setting up a geospatial data science environment in Python, as that is coming up in Chapter 4, Exploring Geospatial Data Science Packages, it is of relevance for us to walk you through how to work with geographic and projected coordinate systems within Python at this time.

There are two notable packages that we’ll reference in this section: PyProj and geopandas. While we won’t spend the time in this chapter diving too deep into the weeds of either of these packages, as we’ll save that for the next chapter, it is relevant for you to know that both of these packages are useful for working with spatial data and projections.


PyProj is a Python package used to transform geospatial coordinates from one coordinate reference system into another. The PyProj package is useful when working with cartographic projections and geodetic transformations. As of the time of writing this...