Book Image

Mastering Geospatial Analysis with Python

By : Silas Toms, Paul Crickard, Eric van Rees
Book Image

Mastering Geospatial Analysis with Python

By: Silas Toms, Paul Crickard, Eric van Rees

Overview of this book

Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell
Geoprocessing with Geodatabases

How to install CARTOframes

The CARTOframes library can be best installed by starting Anaconda Navigator and creating a new environment. From there, you can open a terminal and use pip install, which will install the library for you. This is currently the only way to install it (there's no conda support yet). Use the following command:

>>pip install cartoframes

Additional resources

CARTOframes documentation can be found, at:

The current version of CARTOframes is 0.5.5. The PyPi repository for CARTOframes can be accessed here:

There's also a GitHub repository with additional information, as one of the many CARTO GitHub repositories: 

Jupyter Notebooks

It is recommended to use CARTOframes in Jupyter Notebooks. In the example scripts later in this chapter, we'll be using the CARTOframes package with other geospatial packages, so you might want to install it in a virtual...