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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
Authors (3):
Silas Toms Silas Toms
Profile icon Silas Toms
Paul Crickard Paul Crickard
Profile icon Paul Crickard
Eric van Rees Eric van Rees
Profile icon 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 1. Other Books You May Enjoy Index

Summary


In this chapter, we learned how to use the MapboxGL—Jupyter and Mapbox Python SDK to create data visualizations and to upload data into the Mapbox account. We created point data visualizations, choropleth maps, heat maps, and graduated circle visualizations. We learned how to style a custom basemap, how to add it to an HTML map, and how to add custom tilesets to the basemap. We learned how to use GeoPandas to convert Polygon data into point data, and how to visualize the result. 

In the next chapter, we will explore the use of Python modules and Hadoop to perform geospatial analysis.

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