Hands-on Exercises using PySAL Map Classify
Author(s): Su Yeon Han
In this notebook, you will learn how to create choropleth maps using different classification methods available in the mapclassify package of the Python Spatial Analysis Library (PySAL).
The examples in this notebook are adapted from the electronic book "Geographic Data Science with Python" by Sergio Rey, Dani Arribas-Bel, and Levi Wolf, which can be found at https://geographicdata.science/book/intro.html. Specifically, we will focus on the section titled "Choropleth Mapping" under "PART II - Spatial Data Analysis."
Our goal is to explore regional income data for the 32 Mexican states used in the paper by [RSastreGutierrez10]. The variable we will be analyzing is per capita gross domestic product for 1940 (PCGDP1940).
By the end of this notebook, you should have a better understanding of how to create choropleth maps using different classification methods and be able to apply this knowledge to your own spatial data analyses.
Keywords: Mapping, Choropleth Map, Pysal