Television actors can make boat loads of money. Some more than others. Hugh Laurie makes $400,000 per episode while Ashley Tisdale makes $30,000. TV Guide compiled a list of TV’s top earners a while back, so luckily we can take a look by the numbers. Here’s your chance to visualize the data.

You can download the data in CSV format or in Excel. There are four columns: actor name, show, pay per episode, and show type (comedy or drama). I entered this data by hand to get it in a manageable format, so keep an eye out for typos (just like in real life!).

The challenge here will be that there’s quite a few names on the list, so it’s a bit too much to show every value at once. You’ll have to decide what you want to show and what story you want to tell. Do actors in drama or comedies make more? What kind of distribution do you see? How do top actor salaries compare to that of the average actor?

One more time, here’s the link to the CSV and Excel files. Leave links to your graphs in the comments below.

Deadline: February 22, 2011

It’s that time of year again. Obama recently released his 2012 budget proposal for how to allocate $3.7 trillion. It’s complicated no doubt, but Shan Carter and Amanda Cox of the New York Times make it easier to understand with their interactive treemap. Rectangles are sized by proposed spending and colors indicate percent change from previous year. Darker red rectangles represent bigger drops from the 2011 budget and darker green greater increases. Zoom in and pan as you please.
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Tonight on Jeopardy, the first day of the IBM Watson challenge, Ken Jennings and Brad Rutter will go up against IBM’s super computer in the historic match of man versus machine. In place of a person, a computer screen with an animated graphic will stand representing Watson, but it’s not just some random icon.

The avatar is actually a work of generative art designed by Joshua Davis and implemented by Automata Studios. The avatar changes based on a number of factors such as confidence in an answer and question type for a total of 27 states. For example, when Watson enters an answer correctly, the swarm around the sphere flows to the top and turns green. When Watson answers incorrectly, the swarm turns orange and flows to the bottom.

Get the full description and a sense of the process in the video below.
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Pedro Cruz puts a twist on the traditional map approach to visualize traffic in Lisbon as blood vessels:

In this work the traffic of Lisbon is portrayed exploring metaphors of living organisms with circulatory problems. Rather than being an aesthetic essay or a set of decorative artifacts, my approach focuses on synthesizing and conveying meaning through data portrayal.

Vessels swell and wiggle as traffic picks up during the rush hour and then relax and shrink as traffic goes down. More useful than an actual map? Probably not. Fun and engaging? Yes. Catch the short animation below.
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I got a chuckle out of this one. By Brandon Schaefer. Check out the full-sized version here.

As we all know, the iPad has changed how many people interact with online content as well as provided interaction designers with a new vehicle to mess around in. Your hands aren’t glued to mouse and keyboard anymore. They’re all over the place, depending on what application you’re using or game you’re playing. George Kokkinidis, of Design Language News, has a brief look at these differences through his fingerprints:

My method involved cleaning the iPad’s surface with a microfiber cloth, using an app for a short amount of time, then turning the screen off. Next, I photographed the iPad, positioning a light source and some black matte board to limit distracting reflections. I then brought the photographs into Adobe Illustrator, and created vectors of the iPad and the fingerprints to emphasize the data.

The method is so simple but super effective. I’m sure just about everyone recognizes that pattern on the bottom left.

[Design Language News via Waxy]

As you might expect, people who play sports video games tend to play with teams when those teams are winning in real life. Anyone who plays online via their Playstation or Xbox can tell you this. I play NBA 2K11 sometimes, and it can get pretty boring playing the Lakers over and over again. Kevin Quealy for the New York Times investigates the phenomenon with data from Madden NFL, the most popular football video game of all time, and small multiples. I sense R and ggplot.

A team loses, and there’s a dip in gameplay. A team wins or gets a new star player, there’s a spike.

OkCupid continues their analysis on the mysteries of the dating world, this time on the best questions to ask on a first date, or rather, the best questions to ask when you actually want to find out something else. Will your date have sex on the first date? Ask your date if he or she likes the taste of beer, because:

Among all our casual topics, whether someone likes the taste of beer is the single best predictor of if he or she has sex on the first date.

Well, okay, not entirely correct. The question is if they would consider sex, not if they’d actually do it. I’ve considered buying just about every Apple product, but all I have is the one Macbook. Still interesting though.

I’m still waiting for LinkedIn to start doing this sort of analysis. I mean it’s more or less the same thing, except you’re trying to find a company to work for rather than a partner to, uh, have beer with. Who’s with me?

Jer Thorp, who has a knack for creating stuff that’s both useful and beautiful, continues his string of impressive work with this visualization for Boing Boing (video below). It shows possibly habitable planets, according to Kepler data. For those unfamiliar, the Kepler mission is to find possible habitable planets, or more precisely:

The challenge now is to find terrestrial planets (i.e., those one half to twice the size of the Earth), especially those in the habitable zone of their stars where liquid water and possibly life might exist.

The visualization imagines if all the exoplanets were orbiting a single star, which is physically impossible, but allows for comparisons for size, temperature, and path. There are a few views, starting with the exoplanets orbiting and then the animation transitions to something that sort of looks like an exoplanet mountain and then into a bubble plot.
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The sold out O’Reilly Strata conference was a success down in Santa Clara, California, with the next one already scheduled for 2011 in New York. There were lots of interesting talks and lots of interesting people to talk to. I was only there for one day and didn’t nearly get to meet everyone I wanted to, but it was great seeing so many people who are excited about data packed into one place.
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People are getting fatter everywhere. You know this. But there’s nothing like the numbers to actually show how we’re growing outwards and by how much. With this interactive, Wilson Andrews and Todd Lindeman, for the Washington Post, report:

With a few exceptions, the average body mass index in most countries has risen since 1980, according to a project that tracked risk factors for heart disease and stroke in 199 countries over 28 years.

Each circle represents a country, plotted by men’s BMI on the horizontal axis and women’s BMI on the vertical. Countries above the diagonal are countries where women have a higher BMI than the men, and vice versa for dots below the diagonal. Press play, and watch how BMI has changed from 1980 to 2008.
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Designer Gregor Aisch has a look at energy usage in Europe. Click on a number of topics on the bottom to see how each country compares, or mouse over a specific country to get its details. Bubbles are color-coded according to relatively high or low levels (I think) and sized by population (I think). There isn’t a whole lot of explanation of what you’re actually seeing, but it has some interesting interactions in there. Maybe our European readers can add some context. Don’t forget to take it fullscreen and put it on autoplay.

[publicdata.eu via @moritz_stefaner]

I think we’ve all grown accustomed to this by now. Designer Nicholas Felton, known for his quantified annual reports on his life for the past year, just put up his Report for 2010. This one though isn’t for Nicholas. It’s for his late father. It’s breakdowns for where he lived and traveled, postcards sent, and people he spent time with.
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Statisticians everywhere are squealing in delight over this story on fellow statistician Mohan Srivastava, who used his know-how to crack the code of a tic-tac-toe scatcher lottery game. After winning three dollars on a scratcher ticket that was given to him as a gag gift, Srivastava got to wondering about the process of how tickets were made. As a geological consultant who figures out if areas are worth mining for gold, he wondered if he could do the same with this scatcher.
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Here are some links for you to accompany your bag of chips, bowl of chili, and plate of wings as you wate for the Super Bowl to start.

Super Bowl FanMap — Who are people picking to win the big game in your area? ESRI is taking votes and mapping them. Packers are far ahead, leading 64 percent to 36. [via]

Where the Streets Have Your Name — See where there are streets named after you. Yeah, you.

d8taplex — A super alpha version of something that looks like a data search engine with graphs.

Top-spending cities for personal care — Active north and sedentary south?

Designer Ibraheem Youssef iconifies the most viewed YouTube videos of all time. Do you recognize what each icon represents? I’m embarrassed to say that I probably know one too many of them.
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Fortune Magazine recently published their annual list of top companies to work for, with SAS, Boston Consulting, and Wegman’s taking the one, two, and three spots, respectively. To accompany the piece, this interactive, produced by Tommy McCall, shows what the employees have to say about their companies.
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Apparently moods on Twitter can be used to predict the ups and downs of the stock market, according to work from Johan Bollen and Huina Mao of Indiana University-Bloomington: “Measuring how calm the Twitterverse is on a given day can foretell the direction of changes to the Dow Jones Industrial Average three days later with an accuracy of 86.7 percent.”

I can’t wait until Twitter is used to predict when I want to eat and sleep, and my robot can cook me gourmet meals and provide turn down service accordingly. And it better be accurate to the minute. Anything less is failure.

Christopher Beam for Slate explains research being done at UCLA in collaboration with the LAPD on predictive policing:

Predictive policing is based on the idea that some crime is random—but a lot isn’t. For example, home burglaries are relatively predictable. When a house gets robbed, the likelihood of that house or houses near it getting robbed again spikes in the following days. Most people expect the exact opposite, figuring that if lightning strike once, it won’t strike again. “This type of lightning does strike more than once,” says Brantingham. Other crimes, like murder or rape, are harder to predict. They’re more rare, for one thing, and the crime scene isn’t always stationary, like a house. But they do tend to follow the same general pattern. If one gang member shoots another, for example, the likelihood of reprisal goes up.

This happened in my neighborhood when I was in fifth grade. We lived in a pretty quiet neighborhood, but one morning a window was open. Someone had come into our house while we were sleeping and stole whatever was in immediate reach. They also stole my dad’s brand new bicycle from the garage. Same thing happened to my neighbor two days later.

[Slate via @amstatnews]