Linux & macOS   Build Status
Windows   Build status

This course is best followed if you can reproduce the examples and tutorials provided with it. To do so, you will need to install in your machine a series of software packages. These are all open-source and available for free to download.

There are two main pathways to install required Python libraries on your own machine. A minimalist one is less stable and will only provide Python resources, while a more comprehensive one will install not only a Python stack but also several useful R libraries.

This is the recommended approach if you meet the following requirements:

  1. You have admin rights over your machine
  2. You are running either Windows 10 Pro, macOS, or Linux

In that case, Docker is the preferred alternative. It provides a stable platform to run complex software setups like that required in this context. Docker is a containerisation technology that allows to run pre-packaged (containerised) software under controlled environments. Relying on Docker, the gds_env project provides a containerised platform for Geographic Data Science.

The steps to install this (given you meet the requirements above) include:

2) A minimalist approach: conda

If you just want a more minimalist installation that only includes the barebones of what’s needed in this context, and/or you are not running Windows 10 Pro, macOS or Linux, the recommended approach is to do a conda installation. This route will install natively a Python distribution with the libraries we will need. Please note that no interactive extensions or R packages are installed in this case, and also be aware the installation is less stable as it relies on the specific versions for your OS and latest releases (in most cases it should be fine, and this particular stack is regularly tested, but some failures nevertheless happen sometimes).

To install Python and required libraries through this approach, please follow these steps: