As the Super Bowl draws near, Facebook took a look at football fandom across the country.

The National Football League is one of the most popular sports in America with some incredibly devoted fans. At Facebook we have about 35 million account holders in the United States who have Liked a page for one of the 32 teams in the league, representing one of the most comprehensive samples of sports fanship ever collected. Put another way, more than 1 in 10 Americans have declared their support for an NFL team on Facebook.

It’s a fairly straightforward geographic breakdown based on the most liked team in each county, as shown above. So you can kind of see where rivalries come from.
Read More

We’ve all seen rain maps for a sliver of time. Screw that. I want to see the total amount of rainfall over a ten-year period. Bill Wheaton did just that in the video above, showing cumulative rainfall between 1960 and 1970. The cool part is that you see mountains appear, but they’re not actually mapped.

The hillshaded terrain (the growing hills and mountains) is based on the rainfall data, not on actual physical topography. In other words, hills and mountains are formed by the rainfall distribution itself and grow as the accumulated precipitation grows. High mountains and sharp edges occur where the distribution of precipitation varies substantially across short distances. Wide, broad plains and low hills are formed when the distribution of rainfall is relatively even across the landscape.

See also Wheaton’s video that shows four years of rain straight up.

Is there more recent data? It could be an interesting complement to the drought maps we saw a few months ago. [Thanks, Bill]

I’m almost certain this relationship is significant. Side note: Is there a meaningless-correlations tumblr yet? [via]

Arthur Buxton plotted the most common colors of Penguin Publishing science fiction colors and arranged them over time. Also available in print.

I wonder if there’s a good way to show connections between the titles or the different covers for each title.

How wealthy are the richest people in the world? How do they compare to each other, and how does their net worth change over time? Bloomberg just put up an interactive tool to answer such questions, and it’s updated daily with new data.
Read More

For the past year, I’ve been working on Data Points: Visualization that Means Something, and you can pre-order it now.

Visualization has grown a lot in the 5-something years I’ve written for FlowingData. It’s not just a tool for analysis anymore. Visualization is a way to express data, and it comes in the form of information graphics, entertainment, everyday interfaces, data art, and yeah, tools, too. Your approach to data and visualization changes based on application.

But even with all these (awesome) new applications, there’s a constant across all of them: the data.

Data Points starts here, and takes you through the process of understanding data, representing it, exploring it, and designing for different applications. Whereas Visualize This was about getting your feet wet with lots of code examples, Data Points is code-independent and is a perfect complement that helps you understand and allow others to understand data better, which is sorta the whole point.

The manuscript is written, the 240 graphics (by me and many of your favorites) are set, and I’m really happy with how it turned out.

It’ll officially be out late March or early April. Crazy, nerve-racking, and exciting all at the same time.

More details to come. Until then: pre-order the book today.

Thanks to Sha Hwang, you can now siltscan videos on YouTube and Vimeo with an easy-to-use bookmarklet. Just go to the video and click. In case you’re unfamiliar with the technique, here’s a description from Golan Levin:

Slitscan imaging techniques are used to create static images of time-based phenomena. In traditional film photography, slit scan images are created by exposing film as it slides past a slit-shaped aperture. In the digital realm, thin slices are extracted from a sequence of video frames, and concatenated into a new image.

Be sure to switch over to HTML5 on YouTube or Vimeo first. The bookmarklet won’t work with Flash.

During a two-week visualization course, Momo Miyazaki, Manas Karambelkar, and Kenneth Aleksander Robertsen imagined what a body of text would be without the the silent letters in silenc.

silenc is based on the concept of the find-and-replace command. This function is applied to a body of text using a database of rules. The silenc database is constructed from hundreds of rules and exceptions composed from known guidelines for “un”pronunciation. Processing code marks up the silent letters and GREP commands format the text.

So nothing too fancy on the analysis side, but the experimental views are kinda interesting to see. [via @alexislloyd]