Early on during what has since become the first global pandemic of my career, I started to comes across some really good looking charts plotting the spread of coronavirus from its origins in Wuhan, China, to almost every other country in the world. Having recently started using Jupyter Notebooks myself, it seemed like a good opportunity to increase my familiarity with Jupyter by seeing what I could do with the wealth of data that this pandemic has produced.

I have previously done most of my plotting with Matplotlib, but I have since stumbled across Plotly and I noticed that it seems to have very good support for map-based charts out of the box. As such, Plotly seemed to be the go-to library for the charts that I wanted to produce.

Detailed below is the process of taking the raw time-series data from the widely used John Hopkins repo, processing it and then using Plotly to graphically show the spread of worldwide spread of coronavirus over time.

You can find my original Github repo here.

(Word of warning: whilst the maps render nicely on larger screens, mobile users' mileage may vary.)