Steal Like a Data Visualiser
How I recreated a particle orbit in Clojure and improved my animation skills in the process
Improving your data visualisation skills through theft may sound vicious at first, but it is a very effective learning method and hopefully a great tribute to the original creator.
Why did I steal?
I was born in Germany, but my parents immigrated from Poland. In Germany there’s a stereotype that Eastern Europeans, and especially people from Poland, tend to steal a lot. But confirming this stereotype was not my main motivation … I was inspired by the book Steal Like an Artist by Austin Kleon. This book is full of great advice. It shows how stealing can help you become a better artist — here’s one of my favourite quotes from the book:
If we’re free from the burden of trying to be completely original, we can stop trying to make something out of nothing, and we can embrace influence instead of running away from it.
So I thought, if that works for art, then it can work for data visualisation as well. I checked my list of favourite data visualisations and decided to steal one. This article is about how I stole a viz from ‘The Unlikely Odds Of Making It Big’ by The Pudding.
Note: I’m not actually encouraging you to steal someone else’s work. This article explains how useful recreating other people’s ideas can be, to practise and enhance your own skills.
What did I steal?
The Unlikely Odds Of Making It Big shows the trajectory of 3000 small bands who tried to make it big in New York City from 2013–2016. Most headlined at a small venue with a capacity of less than 700 people. Only 400 successfully headlined a show with a capacity of over 700 people and, of those, 21 bands had made it big by 2016, i.e. they had headlined a show with an audience capacity of 3000+. This was one of the visualisations that inspired me to learn as much as possible about dataviz. My plan is to skill up so that one day I can create my own stories like this.
The visualisation is split into three parts: a particle orbit introducing all bands, a bubble chart about the bands who made it big and a filterable list with information about all…