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100+ Interesting Data Sets for Data Science

Read full list if you find these examples interesting.

  • How about reading other people’s emails? Ever wanted to do that, but can’t be bothered to train l33t hacking skills (and never mind the legality of it)? (Okay, this one I have thought about.) Well, I’ve got you covered. Check out the Enron corpus. It contains more than half a million emails from about 150 users, mostly senior management of Enron, organized into folders. Wikipedia calls it “unique in that it is one of the only publicly available mass collections of ‘real’ emails easily available for study.” Business idea: figure out what sort of information gets leaked in the emails that will later harm the execs at trial or whatever, then build a software system to automatically mine those out of real email. Either sell it to law enforcement or to corporate executives as the finest cover-your-ass email system.

  • Wondering what the internet really cares about? Well, I don’t know about that, but you could answer an easier question: What does Reddit care about? Someone has scraped the top 2.5 million Reddit posts and then placed them on GitHub. Now you can figure out (with data!) just how much Redditors love cats. Or how about a data backed equivalent of r/circlejerk? (The original use case was determining what domains are the most popular.)

  • Speaking of cats, here are 10,000 annotated images of cats. This ought to come in handy whenever I get around to training a robot to exterminate all non-cat lifeforms. (Or, if you’re Google, you could just train a cat recognition algorithm and then send those users cat-specific advertising.)

  • If you’re interested in building financial algorithms or, really, just predicting arbitrage opportunities for one of America’s largest cash crops, check out this data set, which tracks the price of marijuana from September 2nd, 2010 until about the present.

  • Who’s using what drugs and how often?

  • The earliest recorded chess match dates back to the 10th century, played between a historian from Baghdad and a student. Since then, it’s become a tradition for moves to be recorded – especially if a game has some significance, like a showdown between two strong players. As a consequence, today, students of the game benefit from one of the richest data sets of any game or sport. Perhaps the best freely available data set of games is known as the “Million Base,” boasting some 2.2 million matches. You can download it here. I can imagine an app that calculates your chess fingerprint, letting you know what grandmaster your play is most similar to, or an analysis of how play style has changed over time.

  • On the topic of games, for soccer fans, I recently came across thisfreely available data set of soccer games, players, teams, goals, a.... If that’s not enough, you can grab even more data via this Soccermetrics API python wrapper. I imagine that this could come in handy for coaches attempting to get an edge over opponent teams and, more generally, for that cross-section between geeks and gamblers attempting to build analytic models to make better bets.

  • Google has put made all their Google Books n-gram data freely available. An n-gram is an n word phrase, and the data set includes 1-grams through 5-grams. The data set is “based originally on 5.2 million books published between 1500 and 2008.” I can imagine using it to determine the most overused, cliche phrases, and those phrases that are in danger of becoming cliched. (Quick! Someone register the domain clichealert.com!)

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