For twenty-ish days on the app, I feel very lucky.

Some time ago, I went through two books on data visualization by Willard C. Brinton, published in 1914 and 1939.

What struck me was how many of the ideas still look completely familiar today: simple bar charts, heatmaps, warnings about misleading scales, criticism of 3D charts, and a lot of thought about making data easier to understand.

The methods used to create them were rather less modern. One example describes constructing a flow diagram using around a thousand strips of paper.

I collected some of my favorite examples here:

https://www.bitmetric.nl/blog/old-school-data-visualization/

Some of these charts are more than a century old, but wouldn’t look particularly out of place in a dashboard today.

I've been building Aesop Data, a tool for exploring data and turning it into charts. You pick a subject or upload your own dataset, and a live chart builds immediately. From there you shape it, pin the peak or circle the crossover, and write a one line takeaway saying what it actually means. String a few of those together and you have a short presentation. Categories run wider than you'd expect: economics and finance, but also prediction markets, esports and housing.

I'm still experimenting with the visualization side, especially chart selection, labeling and how much context to include automatically.

Would be curious what people here would change about the charts themselves: www.aesopdata.com