Bringing Data To Life - DIY

Source code and documentation to COVIDBlooms, my COVID-19 data visualisation.

Bringing Data To Life - DIY

Last week I presented and described the why behind a recent COVID-19 data visualisation exercise I undertook recently.

The primary purpose of that exercise was of course, to enable detailed data analysis on a relevant and prominent topic. But there was an ulterior motive too - these exercises never fail to teach things along the way. Staying current and fluent in data science tools is important to me, because being a numerate, critical thinker with tools that help make sense of data is never not my job, regardless of my job.

But let's be honest, me being adept at any of these tools is only possible because of the collective heavy lifting others have done to package and document the building blocks.

So now I get to make my contribution. Below is the complete source code, with interspersed documentation and oh-so-essential references that got me there, that I wrote to generate the data visualisation. To download a copy and use it for any purpose of your own, grab it from my GitHub account here.


COVIDBlooms