Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Geospatial Analysis with Python

You're reading from   Mastering Geospatial Analysis with Python Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter

Arrow left icon
Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788293334
Length 440 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Silas Toms Silas Toms
Author Profile Icon Silas Toms
Silas Toms
Paul Crickard Paul Crickard
Author Profile Icon Paul Crickard
Paul Crickard
Eric van Rees Eric van Rees
Author Profile Icon Eric van Rees
Eric van Rees
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Package Installation and Management 2. Introduction to Geospatial Code Libraries FREE CHAPTER 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 17. Other Books You May Enjoy

Package Installation and Management

This book focuses on important code libraries for geospatial data management and analysis for Python 3. The reason for this is simple—as Python 2 is near the end of its life cycle, it is quickly being replaced by Python 3. This new Python version comes with key differences in organization and syntax, meaning that developers need to adjust their legacy code and apply new syntax in their code. Fields such as machine learning, data science, and big data have changed the way geospatial data is managed, analyzed, and presented today. In all these areas, Python 3 has quickly become the new standard, which is another reason for the geospatial community to start using Python 3.

The geospatial community has been relying on Python 2 for a long time, as many dependencies weren't available for Python 3 or not working correctly. But now that Python 3 is mature and stable, the geospatial community has taken advantage of its capabilities, resulting in many new libraries and tools. This book aims to help developers understand open source and commercial modules for geospatial programs written in Python 3, offering a selection of major geospatial libraries and tools for doing geospatial data management and data analysis.

This chapter will explain how to install and manage the code libraries that will be used in this book. It will cover the following topics:

  • Installing Anaconda
  • Managing Python packages using Anaconda Navigator, Anaconda Cloud, conda, and pip
  • Managing virtual environments using Anaconda, conda, and virtualenv
  • Running a Jupyter Notebook
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
Banner background image