The opening page of We Feel Fine: An Almanac of Human Emotion reads a quote from “a woman in Maine.” It sets the stage for the rest of the book.

I have a problem I’m sure many other bloggers face: I am perfectly comfortable sharing intimate details about my emotions with complete strangers I meet online but shy away from expressing my true feelings to anyone I know in real life.

For those unfamiliar, We Feel Fine is a project from Jonathan Harris and Sep Kamvar that’s been online since 2006. At its core, the goal is to show the emotions of the authors behind millions of blog posts on the Web by looking for sentences that start with “I feel” or “I am feeling.” It’s an interactive artwork “authored by everyone.”
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In a follow up to his McDonald’s map, Stephen Von Worley of Weather Sealed maps the dominating burger chains across the United States. McDonald’s obviously has a stronghold in a lot of areas but not all of them. Most noticeable is Sonic Drive-in with over 900 restaurants in Texas alone. Personally, I’m rooting for Carl’s Jr. and In-n-Out.

[via We Love Datavis]

EPCOR, the water utility company that runs the fountains up in Edmonton, Canada released this graph yesterday. It’s water consumption during the Olympic gold medal hockey game, overlaying consumption of the previous day. How much do Canadians love their hockey? A lot.

The first period ends. Time to pee. The second period ends. Time to pee. The third period ends. Time to pee. Consumption goes way down when Canada wins and during the medal ceremony.

Finally, when it’s all said and done, the rest of the country can relieve itself, figuratively and literally.

[via contrarian | thanks, @statpumpkin]

In an effort to put transit data from the Toronto Transit Committee to better use, MyTTC provides a trip planner to help you find the best route from point A to point B. This video, compete with smart arses sitting on a couch, provides a peek into how the underlying algorithm works.

[Thanks, Canna]

Big news for all you Edward Tufte fanboys and girls. He will be joining the Recovery Independent Advisory Panel who will advise The Recovery Accountability and Transparency Board. The Board’s purpose is to track and explain how the $787 billion in stimulus funds is being put to use.

I’m doing this because I like accountability and transparency, and I believe in public service. And it is the complete opposite of everything else I do. Maybe I’ll learn something. The practical consequence is that I will probably go to Washington several days each month, in addition to whatever homework and phone meetings are necessary.

Whether Tufte will have a direct impact on graphs like these, I’m not so sure, but it certainly won’t hurt. I mean the man does know a thing or two about dispersing information.

[Thanks, Yuri and @tbeauchamp]

Footprints – Every building footprint, and nothing else, in Montgomery County, Ohio. It’s interesting how buildings can define an area.

Data, data everywhere – The Economist reports on the explosion of big data and the challenges that come with it.

Q&A With Shawn Allen of Stamen Design – Always interesting to hear from these guys [thx, tim].

The Case For An Older Woman – Another thoughtful analysis from the okcupid group on why men should be more open-minded to dating older women.

There’s this article on CNN, from The Frisky, that has this little theory about who is most likely to win the Oscar for best actor:

[T]he Oscar generally goes to the dude who has the most best actor and best supporting nominations under his belt already.

That seemed like a curious statement. Didn’t Forest Whitaker, Philip Seymour Hoffman, and Jaimie Foxx recently win on their first nominations for the coveted award? Okay, so Hoffman was actually up against a bunch of other newbies, but what about the rest?

Only 10 out of the past 29 winners, or just over a third, had the most nominations their year. Take a look at the data since 1980. Is the theory valid? You decide.
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It was a good month for FlowingData. We passed the 30k-reader mark, and I think this past month was an all-time high for pageviews. Thanks again. everyone for reading and sharing FlowingData.

I also managed to switch servers (semi-) successfully while updating the FD homepage in the process. Make sure you check that out if you haven’t already, and let me know what you think in the comments.

In case you missed them, here are the most popular posts from last month ranked by a combination of views, comments, and trackbacks. I especially enjoyed a lot of the thoughtful discussion that came out of these posts.

1. Track Mouse Activity On Your Computer
2. How a Giant Shark Took Down an Airplane
3. Data Underload #9 – Big Graphic Blueprint
4. Where Bars Trump Grocery Stores
5. Excessively Labeled Airplane Tells You Where the Big Cheese Sits
6. Think like a statistician – without the math
7. Road to Recovery – Is the Recovery Act working?
8. Data Underload #8 – Unsolicited
9. An Easy Way to Make a Treemap
10. Challenge: make this graph easier to read

From the Forums

There was also some good stuff going on in the forums with a couple of job postings and some data goodies.

Data Visualization Guru – Energy group EnergyHub is looking for someone who can help visualize their data.

Interactive Data Visualization help needed – So is FrogDesign, but for a smaller project.

Visual Architects Contest – Do you have what it takes to win?

WinterOlympicMedals – The Olympics are over, but that doesn’t mean you have to stop playing with several decades of medal data [thanks, annie]

Simple yet effective. Any questions? [via 9gag | Thanks, Barry]

Frederik Seiffert provides this nifty tool, LastHistory, to visualize your Last.fm listening history. Mouse over songs and find repeated track sequences. The visualization itself isn’t all that useful, but it gets interesting when you hook your calendar and photos in with music. LastHistory lets you replay songs synched with your photos, and your slideshow suddenly gains a new dimension.
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FloatingSheep, a fun geography blog, looks at the beer belly of America. One maps shows total number of bars, but the interesting map is the one above. Red dots represent locations where there are more bars than grocery stores, based on results from the Google Maps API. The Midwest takes their drinking seriously.

Of course there are plenty of possible explanations for the distribution. Maybe people get all their food from superstores like Walmart in the red dot areas, so there are fewer gigantic stores than there are small local bars.

Then again, the FloatingSheep guys did their homework and found, according to Census, that the number of drinking places in those red dots are really skewed compare to the average. So it’s also possible that area of the country just likes to drink a lot.

Anyone who lives in the area care to confirm? I expect your comment to be filled with typos and make very little sense. And maybe smell like garbage.

[Thanks, Michael]

From JESS3 is this video on the state of the internet. It’s essentially a barrage of numbers, but it’s fun nevertheless and it’s got some interesting morsels in there.

Like everyone, I’ve been watching the Olympics, and it continues to amaze me how hundredths of a second can make up the difference between a gold medal and nothing at all. Amanda Cox of The New York Times visualizes and audiolizes(?) these tiny differences. She got creative with this one.

Each row is an event and going from left to right, the first dot is the gold medal winner. The amount of space between the first dot and the dots that follow is how many seconds athletes finished after the winner.

Visually, this only sort of works, but click on play to hear how these differences sound, and it puts everything in perspective.

See the rest of NYT interactive Olympic coverage here. You know, just in case NBC coverage doesn’t cut it for you.

Snake oil? Scientific evidence for health supplements – Some work as advertised. Others are just a waste of money.

Cell phones show human movement predictable 93% of the time – Is this really all that surprising? Work, school, home. Rinse and repeat.

America’s Wealthiest Religions – A Good Magazine transparency. Probably didn’t need to be circular.

Measuring Tweets – Twitter is now handling 50 million tweets per day i.e. 600 tweets per second.

All news is connected in some way or another. News Dots from Slate shows just that.

News Dots scans all articles from major publications—about 500 stories a day—and submits them to Calais, a service from Thompson Reuters that automatically “tags” content with all the important keywords: people, places, companies, topics, and so forth. Slate’s tool registers any tag that appears at least twice in a story.

Bubbles are sized by how much the corresponding topic is written about, and connections are made when topics are mentioned in the same article. Click on a topic to see the matching articles in the sidebar.

How everything is placed I’m not exactly sure. I’m guessing distance represents some abstract measurement of relatedness. You guys have any better guesses?

Every Olympics since 1936 has had a series of pictograms (i.e. icons that look like restroom signs) that represents the events. Here are pictograms for the Vancouver games, and here they are for the Beijing Olympics. Some series are distinct while others clearly sucked it up. Designer Steven Heller discusses the evolution of these Olympic pictograms in this video for The New York Times. Which set do you like best?
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The Economist discusses the return of big government and includes this graph showing total government spending as a percentage of Gross Domestic Product. We see a dip in 2000 and a big jump this past year.

The trouble is that the country labels are cluttered. If you read them left to right, you get mixed up initially. Keep your eyes left and move top to bottom, and you might be okay.

The Challenge

Can you think of a way to make this graph easier to read? Is there a better way to represent the time series?

One catch: you have to work within the size limitation of 290 pixels wide and 300 pixels tall. It’s an easy fix with unlimited space. But what can you do when space is scarce? Leave your thoughts in the comments below.

P.S. I was looking for the data this graph uses but got tired of using the OECD stat browser, so we’ll just have to use our imagination for this one.

[Thanks, Justin]

Update: Here’s GDP (sans spending) by country from 1995 to 2008 if anyone would like to take a wack [thanks, Kim].