Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781803238128
Length 308 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
David S. Jordan David S. Jordan
Author Profile Icon David S. Jordan
David S. Jordan
Arrow right icon
View More author details
Toc

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

Summary

In this chapter, we’ve introduced you to a number of Python packages that you’ll frequently leverage in your day-to-day work as a geospatial data scientist. In this chapter, you learned about a variety of packages, such as GeoPandas and Rasterio, for easily reading, manipulating, and writing geospatial vector and raster data structures. In the second part of the chapter, you learned about PySAL and its ecosystem of packages for exploring, modeling, and visualizing geospatial data. The last section of this chapter introduced you to five geospatial packages that enable you to produce production-quality static and interactive geospatial data visualizations.

With these packages, you can now interact with geospatial data and their underlying geometries. Interacting with data is one of the first steps in any data science pipeline. You also now have the skills to produce a variety of geospatial data visualizations, which will be important as you tell the story of...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime