Geospatial Analysis Notebooks

Jupyter Notebooks for the PhD Course on Python for Geospatial Analysis at Aalborg University Copenhagen, Spring 2020.

Please fork this repo so you have your own copy to work on during the course. We may also post some updates during the course, so forking is a better option than simply downloading it.

The materials provided here assume basic knowledge of Python, so please make sure that you have gone through the following preparation steps before starting with the course:

1. Install the Anaconda Distribution for Python on your computer and work through the Getting started with conda tutorial.

2. Read A Whirlwind Tour of Python up to the end. The examples are also a good opportunity to take your shiny new Python installation for a test-drive, so feel free to play around with them. Alternatively, you can go through the Jupyter notebooks associated with the book available on GitHub.

3. We'll be using GitHub for some parts of this course. If you are new to Git,

   • Read the Git Handbook.
   • Create an account on github.com if you do not have one yet.
   • Install GitHub Desktop on your computer (tutorial).

Optional, but recommended:

1. Read Mastering Markdown if you are new to Markdown.
2. Sign up for the GitHub Student Developer Pack to get free access to some of the paid features on GitHub and some other tools/platforms.

Setting up the course environment

The file geoanalysis.yml contains a specification of a virtual environment with all the Python modules needed for this course. To get up and running:

1. Create a new environment from the file, either by running conda env create -f geoanalysis.yml on the command line, or by importing it in Anaconda Navigator. This is going to take a while, we are now downloading a bunch of modules and all of their dependencies.
2. Activate the environment by typing conda activate geoanalysis, then jupyter notebook. Alternatively, in Anaconda Navigator, click the arrow button next to geoanalysis, then choose Jupyter Notebook.