Matplotlib Tools

Matplotlib is a fantastic library for displaying data. It's extremely good for customizing data visualization. I am going to include a handful of example plots on this page but this will not be an exhastive overview.

I would also suggest exploring the matplotlib documentation here. Also matplotlib examples here. I have done my best to annotate heavily as to explain what the code does.

One of my other favorite libraries for plotting data is Seaborn. It looks really crisp and it's rather easy to use.

Some notes on infographics:

Data visualizations—and statistics generally—can be rather dishonest. It's a trap that one can fall into knowingly or not. It's important to be aware of how this can happen. I won't go too deep into it but some of the more common misrepresentations of data visuals can include; withholding data, frivolous artistry, dubious metrics, inconsistent metrics, and axes manipulation.

A personal rule I hold is keep it simple. I'm not really a graphic designer so it's not only easier for me but I find it more beneficial when displaying data. Too much visual 'pop' can take away from what the data is actually showing so I try not to include unnecessary artistry.

I would highly suggest reading Graphics Lies, Misleading Visuals by Alberto Cairo. It's a rather short read but Cairo goes into some good detail on how visual representations of data can be manipulated and misrepresented.

Cited:
Cairo, Alberto. “Graphics Lies, Misleading Visuals.” New Challenges for Data Design, 2014, pp. 103–116.,
https://doi.org/10.1007/978-1-4471-6596-5_5.