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Mastering Geospatial Analysis with Python

You're reading from Mastering Geospatial Analysis with Python

Product type Book

Published in Apr 2018

Publisher Packt

ISBN-13 9781788293334

Pages 440 pages

Edition 1st Edition

Languages

Concepts

Geospatial Analysis

Authors (3):

Silas Toms

Paul Crickard

Eric van Rees

View More author details

Table of Contents (23) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. Package Installation and Management

2. Introduction to Geospatial Code Libraries

3. Introduction to Geospatial Databases

4. Data Types, Storage, and Conversion

5. Vector Data Analysis

6. Raster Data Processing

7. Geoprocessing with Geodatabases

8. Automating QGIS Analysis

9. ArcGIS API for Python and ArcGIS Online

10. Geoprocessing with a GPU Database

11. Flask and GeoAlchemy2

12. GeoDjango

13. Geospatial REST API

14. Cloud Geodatabase Analysis and Visualization

15. Automating Cloud Cartography

16. Python Geoprocessing with Hadoop

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Index

GeoPandas

GeoPandas has been introduced in the GeoPandas section of Chapter 2, Introduction to Geospatial Code Libraries, where its data structures and methods have also been covered.

Geospatial analysis with GeoPandas

GeoPandas was created to offer data to scientists who want to work with spatial data similar to pandas, and this means giving access to geospatial attribute data through data structures not available through pandas. Combine this with a set of geometric operations, data overlay capabilities, geocoding and plotting capabilities and you have an idea of this library's capabilities. In the examples mentioned as we proceed, we'll cover GeoPandas' plotting methods, explain how to access and subset spatial data, and provide a typical workflow for doing geospatial analysis with GeoPandas, where data processing is an important condition for being able to analyze and interpret the data correctly.

Let's have a look at a few code examples of GeoPandas.

Selecting and plotting geometry data...

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Authors (3)

Silas Toms

Silas Toms is a long-time geospatial professional and author who has previously published ArcPy and ArcGIS and Mastering Geospatial Analysis with Python. His career highlights include developing the real-time common operational picture used at Super Bowl 50, building geospatial software for autonomous cars, designing computer vision for next-gen insurance, and developing mapping systems for Zillow. He now works at Volta Charging, predicting the future of electric vehicle adoption and electric charging infrastructure.

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Paul Crickard

Paul Crickard authored a book on the Leaflet JavaScript module. He has been programming for over 15 years and has focused on GIS and geospatial programming for 7 years. He spent 3 years working as a planner at an architecture firm, where he combined GIS with Building Information Modeling (BIM) and CAD. Currently, he is the CIO at the 2nd Judicial District Attorney's Office in New Mexico.

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Eric van Rees

Eric van Rees was first introduced to Geographical Information Systems (GIS) when studying Human Geography in the Netherlands. For 9 years, he was the editor-in-chief of GeoInformatics, an international GIS, surveying, and mapping publication and a contributing editor of GIS Magazine. During that tenure, he visited many geospatial user conferences, trade fairs, and industry meetings. He focuses on producing technical content, such as software tutorials, tech blogs, and innovative new use cases in the mapping industry.

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