To use the analysis provided here, some Python knowledge is required, ideally additional experience (or willingness to learn) about the Pandas data science library and the Jupyter Notebook.
All the computational steps and code are available here.
Ways to use and execute the source code
If you know your way around Github, you can fork the repository.
All of the plots and tables can be recomputed using the Binder service (link in each webpage with plots and data, or use go here and select the relevant notebook yourself.
This will provide a fully functional computing environment, that can be used from your browser. (But you need to download your notebook at the end of the session if you want to archive it or want to continue working on it later.)