Understanding COVID-19 with REPL-driven visualizations

To better understand COVID-19, I visualized open data with Vega and a Clojure REPL. I wrote a blog post about it: COVID19 data in the REPL Here’s a small, static version of the Germany map:


The big reason I took the time to write this up rather than continue privately making my own visualizations was the recent SciCloj data science meetup in Berlin, before ClojureD. A common sentiment was that we should all share how we compose libraries and architecture these kinds of projects. My coronavirus exploration is a very small project, but I thought it could help towards that goal. I shared (a cleaned-up subset of) the code I used to visualize the data in this repo. I figure it may help two kinds of folks: those who could use example Clojure code for charts and maps, and those who want to see how a certain lispy, functional approach to data manipulation is done.


Just gotta say – this is super cool. In my research work I need to dig in to what you did here.

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I just tried this. Works right out of the box. Such a great work!

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Don’t miss namenu’s fork, which added Korea. (But if comparing with other countries, take note of recent changes in the Johns Hopkins source data: they switched from “South Korea” to “Republic of Korea”.)

Tooltip-less image of Namenu’s visualization:

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