A fun interactive piece that shows a few quirks of how we experience time. 2020 definitely feels a decade long so far.
An explorable on the mechanics of gears and how simple machines work.
Somehow, I made it through a BS in engineering without learning the math behind Fourier transforms. This visualization explains them really well, and shows how you can use them to decompose very complex shapes.
This is one of the first infinite scrolling visualizations I’ve run into, although the genre has become more popular since. Worth checking out.
Lying with data is easy without going to these lengths. I don’t even understand what they were trying to highlight with this odd transformation.
You’ve heard of it before - an army of monkeys hitting keys at random for a long enough amount of time will almost surely type out your favorite masterpiece. Here’s the proof, as a live experiment of increasing complexity.
A cool data visualization that tries to explain how travel infrastructure distorts our perceptions of geography. I thought about this a lot after getting my bicycle in San Francisco, and considerably expanding my effective radius.
A really simple visualization that says a lot. The author combed through 741,576 section front headlines since 1900, looking for which country got the most mentions in any given month. It’s pretty amazing how much attention Britain was given early on, and how much reporting about wars takes up the front page. Germany and then the Axis take over during the world wars, then there’s Russia during the cold war, followed Vietnam and Iraq. The fact that China takes up so much of the last ten years is also telling. This is a great project, I just wish the articles were linked, too.
An awesome data visualization of land use across the US. Breaking up the country into quarter million acre squares lets us say a lot about how the US really works, and what people value here.
Using Airbnb ratings to visualize a visitor’s experience of a city is an interesting idea. Understanding neighborhoods, and social problems (just look at the Tenderloin in the SF visualization!)
Urban development is super interesting, and thinking of how cities work by looking at their layouts is a good exercise. I wish I had worked more with geographic data while I was in the Apple Maps team. This seems like a neat library, and the fact that it is based on networkx makes me even more curious. There might be a side project brewing here.
Facts don’t need to be alternative to make you arrive at the wrong conclusions.
A very cool project. Can’t go wrong with mapping + Python + 3D Printing.
Unsurprisingly, its Tyrion.