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Applied Geospatial Data Science with Python

You're reading from   Applied Geospatial Data Science with Python Leverage geospatial data analysis and modeling to find unique solutions to environmental problems

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781803238128
Length 308 pages
Edition 1st Edition
Languages
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Author (1):
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David S. Jordan David S. Jordan
Author Profile Icon David S. Jordan
David S. Jordan
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Table of Contents (17) Chapters Close

Preface 1. Part 1:The Essentials of Geospatial Data Science
2. Chapter 1: Introducing Geographic Information Systems and Geospatial Data Science FREE CHAPTER 3. Chapter 2: What Is Geospatial Data and Where Can I Find It? 4. Chapter 3: Working with Geographic and Projected Coordinate Systems 5. Chapter 4: Exploring Geospatial Data Science Packages 6. Part 2: Exploratory Spatial Data Analysis
7. Chapter 5: Exploratory Data Visualization 8. Chapter 6: Hypothesis Testing and Spatial Randomness 9. Chapter 7: Spatial Feature Engineering 10. Part 3: Geospatial Modeling Case Studies
11. Chapter 8: Spatial Clustering and Regionalization 12. Chapter 9: Developing Spatial Regression Models 13. Chapter 10: Developing Solutions for Spatial Optimization Problems 14. Chapter 11: Advanced Topics in Spatial Data Science 15. Index 16. Other Books You May Enjoy

Exploring Geospatial Data Science Packages

Toward the end of Chapter 3, Working with Geographic and Projected Coordinate Systems, we introduced you to the Python packages: PyProj, GeoPandas, and Matplotlib. You may recall that we used GeoPandas to read in a shapefile of state capitals, plotted them using Matplotlib, and then projected the capitals using PyProj. Reading in geospatial data, projecting the data, and then plotting it are common steps in numerous geospatial data science initiatives. However, we’ve just started to scratch the surface in terms of introducing you to the entire universe of geospatial data science packages and the powerful solutions that are just a few keystrokes away.

In this chapter, we’ll provide you with a deeper understanding of what PyProj, GeoPandas, and Matplotlib are capable of. We’ll also introduce you to a wide array of other geospatial data science packages that you’ll rely upon during your work. Some of these packages...

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