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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

Packages for working with geospatial data

There are many packages that enable you to work with geospatial data in Python. In this section, we’ll discuss some of the most common packages that you’ll interact with during the course of common geospatial data science workflows.

GeoPandas

As we mentioned in the prior chapter, GeoPandas is an extension of pandas, which adds support for additional data types necessary for working with spatial data. It also includes additional methods not found in pandas, which enable you to perform spatial operations and produce spatial data visualizations. We’ll discuss pandas later on in this chapter in the Reviewing foundational data science packages section. pandas is a foundational package required for most general data science workflows.

The core functionality of GeoPandas includes the following:

  • Reading and writing spatial data
  • Spatial data structures
  • Projection management
  • Spatial data visualization...
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