The Wall Street Journal visualized major political contributions, according to the Federal Election Commission, in a piece they call Political Moneyball.

Based on the money sent between the players (and other characteristics like party and home state), our presentation pulls players toward similar players and pushes apart those that have nothing in common. The players who are most interconnected (like industry PACs who try to make alliances with everyone) end up close to the center. Those who are less connected (like a donor who only gives money to Ron Paul) are pushed away from the center.

Analysis was powered by CartoDB, and the network by Tulip.

The challenge with these network graphs that have lots of nodes and edges is narrowing down what’s useful. With yesterday’s Internet map it’s easy to relate, because you just search for the sites of interest, and the large ones such as Facebook and Twitter provide context.

However, with Political Moneyball it’s tougher, because there are so many entities you’ve never heard of. My suggestion: Start with the examples section (such as who the National Rifle Association supports) in the sidebar, and go from there. It’ll be much easier to get into it.

Peter Nitsch created Ascii Street View, converting Google Street View to colored letters. Search for a location and experience the retro goodness. [via Waxy]

Using a new kind of MRI scanner, scientists at the National Institutes of Health mapped the connections in the human brain, revealing an intricate, grid-like structure.

“Before, we had just driving directions. Now, we have a map showing how all the highways and byways are interconnected,” says Van Wedeen, a member of the Human Connectome Project. “Brain wiring is not like the wiring in your basement, where it just needs to connect the right endpoints. Rather, the grid is the language of the brain and wiring and re-wiring work by modifying it.”

[via Matt Mullenweg]

Ruslan Enikeev created a searchable Internet map of links and bubbles, showing over 350,000 sites and two million links from 196 countries. Similar sites are closer together.
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From the Guardian US, a simple site that tells you if a record was broken today, and if so, what records. It was pieced together with Google Docs and github, and uses the New York Times Olympics API. [via]

No doubt there is going to be a lot of tweeting about the Olympics during the next couple of weeks, but sometimes it’s hard to get a sense of what people are talking about because of the high volume. Emoto, a team effort by Drew Hemment, Moritz Stefaner, and Studio NAND, is a Twitter tracker that aggregates sentiment around topics.
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A lot of Olympic events are over and done with in a few minutes (or seconds), so the difference between winning and losing can be something really tiny. As the games in London get started, The New York Times put together a great series on the tiny details that athletes try to hone in on as they jump over hurdles, twist over the vault, and hand off the baton.

The feature was surprisingly sort of buried in a lot of other Olympic coverage, but hopefully they put together more of them. The combination of graphics and insight from athletes is uber interesting.

Update: The butterfly was just added, and cycling is up next.

Lee Drutman, a Senior Fellow at the Sunlight Foundation, compared the tax returns of previous presidents against that of Mitt Romney.

This scatter plot highlights two things: First, the two highest income years we observe are Romney 2011 ($21.6 million) and Romney 2010 ($20.9 million). Nobody else comes close. The next closest are Obama 2009 ($5.5 million) and Obama 2007 ($4.1 million).

Second, the two lowest effective tax rates we observe also belong to Romney. The 2012 Republican candidate paid an effective tax rate of 13.9% in 2010 and 15.4% in 2011. Next lowest is George H.W. Bush, who paid a 15.5% rate in 1991. By contrast, in Obama’s two highest earning years, he paid a rate of 32.6% (2009) and 33.7% (2007).

Of course the difference is there because most of Romney’s income comes from investments, but wow, what a contrast.

[Thanks, Chris]

The Washington Post has a fine graphic on swimming world records and the changing swimsuit, from speedo to full rubber body suit.
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Carnegie Mellon statistics professor Cosma Shalizi considers the differences and similarities between statistics and data science.

If people want to call those who do such jobs “data scientists” rather than “statisticians” because it sounds more dignified, or gets them more money, or makes them easier to hire, then more power to them. If they want to avoid the suggestion that you need a statistics degree to do this work, they have a point but it seems a clumsy way to make it. If, however, the name “statistician” is avoided because that connotes not a powerful discipline which transforms profound ideas about learning from experience into practical tools, but rather, a meaningless conglomeration of rituals better conducted with twenty-sided dice, then we as a profession have failed ourselves and, more importantly, the public, and the blame lies with us. Since what we have to offer is really quite wonderful, we should not let that happen.

Some time during the past couple of years, statistics became data science’s older, more boring sibling that always plays by the rules. There are a lot of statisticians who now call themselves data scientists. I still call myself a statistician.

But I think we’re getting closer to that part in the movie when the older, more stuffy character learns from the young whipper snapper that loosening up could be a good thing, and when the young one realizes that some elbow grease and tradition can go a long way.