Pokemon is everywhere these days. I think it’s just something the world really needs right now. I know very little about the universe, but I do like it when people analyze fictional worlds and characters. Joshua Kunst grabbed a data dump about all the Pokemon (seriously, I don’t even know if I’m referring to them/it/thing correctly) and clustered them algorithmically. The t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm to be specific.
Charting all the Pokemon
Projects by FlowingData See All →
Years You Have Left to Live, Probably
The individual data points of life are much less predictable than the average. Here’s a simulation that shows you how much time is left on the clock.
Peak Non-Creepy Dating Pool
Based on the “half-your-age-plus-seven” rule, the range of people you can date expands with age. Combine that with population counts and demographics, and you can find when your non-creepy dating pool peaks.
Top Brewery Road Trip, Routed Algorithmically
There are a lot of great craft breweries in the United States, but there is only so much time. This is the computed best way to get to the top rated breweries and how to maximize the beer tasting experience. Every journey begins with a single sip.