Chart design

This is an educational data project to see how data visualisations can mislead or suggest false conclusions. It's also a journey of learnings where I want to discover what can and will be done wrong when presenting data to readers. I fell into this rabbit hole by naivly asking a question on misleading charts on Mastodon.

Basically I bought a few books and looked intensively how professionals do it, what they warn about and what implications one should care about when visualising data - I realised this is so educational for me, let's write a bit to enforce the learning process and maybe it helps others too. Further I think being informed how you can trick readers into false conclusions is an important skill in times of AI slob and a growing spread of misinformation.

Disclaimer: Not all mistakes are automatically misleading or created with evil in mind. Often people are trapped in mindsets or just gaze over imporant aspects. It will likely happen to me too.

So in general I'd like to say thanks for visiting the site and when you got feedback, reach me on Mastodon or Bluesky. Additionally I included data pipelines, visualisation code and the web deployment code in a Git repository

Why should I even bother?

The project is all about visual literacy (graphicacy). Everyone of us can decide to just take what they get and leave it there. For me at least, I think we all should educate ourselves to build our own picture and find mechanisms or short cuts to see where data representations want to lead us with a healthy amount of critical thinking.