A Beginner’s Guide to Creating a Corona Dashboard (Part 2; for real now!)

In my last article I promised the reader that I’ll create a dashboard to track the spread of the corona virus in my homeland as well as for other European countries. The result was a R script that gathers data from the European Center for Disease Control and Prevention to create some static ggplot2 outputs.

While these graphs helped me to answer the questions I had, they don’t really constitute to something that deserves to be called“dashboard. Furthermore, since they are static, they might answer my question but not yours, for example if you’re interested in a different time period. The natural next step was to create a real interactive dashboard which can be published on the internet so that users can chose what exactly the graphs should show.

This article will be exactly about that. At the end you’ll find a link to the Shiny app as well as the source code, so you can build it yourself, improve it, customize it, or do whatever you want with it. Be creative! It helps fighting against the boredom and loneliness, at least it did for me.

Disclaimer: I’m not a scientist and don’t pretend to be one. Please view this article more as a technical guide and don’t try to infer anything from the graphs created. Stick to the expert opinions, e.g. from Johns Hopkins or for Germany…