Charting all the Pokemon

Jul 18, 2016

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.

Favorites

Visualizing the Uncertainty in Data

Data is an abstraction, and it’s impossible to encapsulate everything it represents in real life. So there is uncertainty. Here are ways to visualize the uncertainty.

Graphical perception – learn the fundamentals first

Before you dive into the advanced stuff – like just about everything in your life – you have to learn the fundamentals before you know when you can break the rules.

Divorce and Occupation

Some jobs tend towards higher divorce rates. Some towards lower. Salary also probably plays a role.

How You Will Die

So far we’ve seen when you will die and how other people tend to die. Now let’s put the two together to see how and when you will die, given your sex, race, and age.