As a cure for unpalatable side effects when seeing a crappy graph I reshape them in something better. Sometimes there are those who shamelessly deceive, with or without intention. Swindling with axes, mixing correlation with causation, skewed means etc.. And sometimes people use charts, maps or graphics to make a point without thinking about how these visualisations represent the underlying data.
But most of the time I’m just baffled about what’s happening in a visualisation that’s designed badly. It can sometimes take ages to finally grasp the information. The obvious point I want to make here is that data visualisations are there for us to make things easier, not harder!
In the first section of my homepage I’ll archive all improved visualisations (newest on top). With always the original and the improved version together. Follow me on twitter to receive a new one as an image on your twitter feed.
Rule of thumb is that the language of the original graph is the language I use in the visualisations. Sometimes the graph is clearly intended for a Dutch Audience. I’ll always add a short English intro.
I hope you learn some things 😊.
This is an introduction of the series: Data Visualisation Redesigned for the Better.
For redesigns and other data journalism/visualisation related articles, go to my blog:
Do you stumble upon a crappy graph? Please let me know! Cheers 🙂