Python beyond the workshop

Some people find the course interesting and would like to find out more about how python can be used for data analysis and how to continue learning about Python for (Geographic) Data Science. This section collects a few references to point you in that direction.


Two excellent (free) books are:

There are two popular books that are good introductions to using Python for Data Science:

Note these are introductions to Data Science but there is very limited, if any, coverage of spatial data and spatial analysis.

Package references

Several of the core packages for data science written in Python have prepared impressive resources as part of their documentation. In some cases, these references are a fantastic summary not only of the functionality of the library, but also of the methods behind them. Here is a short list with some of the most relevant ones:


There are several online resources to learn Python, to a point that it becomes too hard to know where to start. One of the most useful ones is the recordings of the SciPy conference for scientific computing in Python, which takes place every July in Austin (TX). The conference includes both short presentations of new packages and projects and 4h workshops that delve into the details of the main functionality in the scientific Python stack. The playlist of the 2018 edition is available at:

And, in the context of Geographic Data Science, the following two workshops are of particular interest:

Online Courses

In addition to disconnected resources, there are starting to appear full bodied courses on the use of Python for (Geographic) Data Science. Here are a couple of interest: