Kevin Wu made a straightforward interactive that lets you see IMDB television ratings over time, per episode and by season.
Kevin Wu made a straightforward interactive that lets you see IMDB television ratings over time, per episode and by season.
Because you get more pizza to eat, and if you don't finish it, you'll have breakfast tomorrow. Other than that fine reason, well, it's geometrically the better deal. Planet Money explains with an interactive that shows the price per square inch for 3,678 pizza places across the United States, based on data from Grubhub.
The math of why bigger pizzas are such a good deal is simple: A pizza is a circle, and the area of a circle increases with the square of the radius.
More pizza more problems
So, for example, a 16-inch pizza is actually four times as big as an 8-inch pizza.
And when you look at thousands of pizza prices from around the U.S., you see that you almost always get a much, much better deal when you buy a bigger pizza.
You get more pizza, and the business gets more money with minimal extra pizza-making effort. Win-win. Although, keep going on the horizontal axis and I bet that curve starts to curl up. Where can I get a ten-foot pizza?
Two bars, one blue and one red, represent two events that can happen together or independently of the other. When a ball hits a bar the corresponding event occurs. What is the probability that one event occurs given that the other does and vice versa? If the probability of both events increases and decreases, how does that change the separate probabilities? Sliders and options let you experiment, and the visual and counters change to help you learn.
A fun one to tinker with.
You can make static maps in R relatively well, if you know what packages to use and what to look for, but there isn't much direct interaction with your graphics. rMaps is a package that helps you create maps that you can mouse over and zoom in to.
Last year, WNYC made an interactive map that shows transit times in New York, based on where you clicked. Geography graduate student Andrew Hardin expanded on the idea for San Francisco, Seattle, Boulder, and Denver, with additional options and more granular simulations.
Two Google research groups, Big Picture and Music Intelligence, got together and made a music timeline baby.
The Music Timeline shows genres of music waxing and waning, based on how many Google Play Music users have an artist or album in their music library, and other data (such as album release dates). Each stripe on the graph represents a genre; the thickness of the stripe tells you roughly the popularity of music released in a given year in that genre. (For example, the "jazz" stripe is thick in the 1950s since many users' libraries contain jazz albums released in the '50s.) Click on the stripes to zoom into more specialized genres.
As you'd expect, the initial view is a stacked area chart that represents the popularity of genres over time, which feels fairly familiar, but then you interact with the stacks and it gets more interesting and almost surprisingly fast. The best part is the pointers to specific albums as you mouse over.
When you watch sports, it can sometimes feel like the stat guy pulls random numbers for the talking heads to ponder, and you can't help but wonder who significant the numbers actually are. Benjamin Schmidt shows all the possibilities for a common statement during baseball games, and it turns out there are a lot of statements to pick from.
Statements of the form "Jack Morris won more games in the 1980s than anyone else" are fascinating. Although they're true, they rest on cherry-picked years that may or may not illustrate a deeper truth in context. (And we see them all the time: see my college degrees cherry-picker for another area.) For baseball, there are thousands of statements just like the ones here that you can make about any single cumulative stat over the game's history--10,296, to be exact. Printed out, all the statements you could make with the data here would take about 15,000 pages: this visualization lets you hone in on the patches of interest.
Andrew Filer mapped the reach of public radio stations in the United Stations, based on data from Wikipedia and the station search from the Federal Communications Commission. Each circle represents a station and its coverage, and colors represent media outlets. For example, Capital Public Radio in Northern California is available across several stations in Sacramento, Modesto, Tahoe City, and others.
So now you know where to go the next time you grow tired of the usual Billboard top 20.
You're on the freeway, traffic is moving along, and for no apparent reason everyone slows down. And eventually, for no apparent reason, traffic starts back up again. What the what? Lewis Lehe and Matthew Green explain why these waves occur with a couple of interactives.
The simplest explanation for why traffic waves happen is that drivers have relatively slow reaction times: if the car in front of you suddenly slows down, it’ll likely take you a second or so to hit the brakes. The slower your reaction time, the harder you have to brake to compensate and keep a safe distance. The same goes for the car behind you, which has to brake even harder than you did in order to slow down faster. And so on down the road, in a domino-like effect.
Hit the brakes in the simulation, and you'll see what happens. Naturally this is a simplified version of traffic conditions and assumes some things about how people drive and react, but you'll get the idea.
It might remind you of this real world experiment a few years ago.
You've probably heard of the six degrees of Kevin Bacon. The idea is that you can name any actor and trace back to Kevin Bacon through actors who have worked together. Ben Blatt for Slate applied this idea to sports and put together an interactive that finds the number degrees between athletes. The fun part is that you can enter two athletes from different professional sports: basketball, football, and baseball.
What's even more remarkable is that it's possible to connect players who didn't even play the same sport. Cross-sport athletes like Deion Sanders and Bo Jackson are exceedingly rare, and some combinations of sports are hardly seen at all. Of these 18 athletes, all but one—Bud Grant—played baseball as one of his two pro careers, proving either that the stars of the diamond are athletic enough to master other sports or that anyone athletic enough to play basketball or football can also handle baseball. Hockey is the opposite, as there has never been a pro hockey player who also played top-level basketball, football, or baseball. As a result, hockey is a closed system. But once you get off the ice, it's possible to link every pro baseball, basketball, and football star.
I like how it only takes 18 players (well, actually probably fewer) to pull double-time to make this possible. To link Yao Ming (basketball) and Joe Montana (football), it only took six hops, with Mark Hendrickson as a link between basketball and baseball and Deion Sanders as the link between baseball and football.
Surprising? Kind of, but then again, in 2011, almost all pairs of people on Facebook could be linked with just six hops, too. The barebones interactive is still a lot of fun to play with though if you follow sports.
It can be difficult to imagine the scale of planets and moons, because (1) they're really big and (2) they're far away. From where we are, the stars look pretty small, but in reality, they shiny objects might be several times larger than our own planet. In this straightforward interactive, Brian Lukis shows how planet and moon sizes compare. Simply select between the apparent view and the absolute to see how perspective seemingly changes size.
When you focus on all the small events and decisions that happen throughout a single day, those 24 hours can seem like an eternity. Graphic designer Luke Twyman turned that around in Here is Today. It's a straightforward interactive that places one day in the context of all days ever.
You start at today, and as you move forward, the days before this one appear, until today is reduced to a one-pixel sliver on the screen and doesn't seem like much at all.
For the past few months, Stamen Design has been working with 3-D data from Nokia's Here. Something pretty came out of the experiment.
For your viewing, embedding, linking, and otherwise internet-ing pleasure: http://here.stamen.com/ is live today. It uses 3D data from HERE for San Francisco, New York, London, and Berlin to create city-wide 3D browsable maps, and it does this in the browser (though you'll need a WebGL-enabled browser to see it). As in many of our other mapping projects, the urls change dynamically depending on location and other factors, and the data conforms, more or less, to the Tile Map Service specification. What this means, among other things, is that it's not only possible to link to and embed these maps at specific locations and zoom levels, but that it's easy—and as we've seen with Citytracking, easy is good.
There are a bunch of views to play with, and you should try all of them. My favorites though are the city-planning look in Pinstripe and the glowing aesthetic of the height view.
If you listen to the radio long enough, you've probably noticed that many songs sound similar or remind of you of a song you've heard before. Hooktheory shows you just how similar some songs are via chord progressions in over 1,300 songs. The small group analyzed the data last year and presented some static charts, but this interactive version takes it a step further.
Simply start by selecting a chord in the network diagram. Songs that use that chord appear on the right. Then select another chord in the network diagram to find songs that use the chord progression from the original to the new. Keep selecting chords to filter further.
So in the end, there are two main things you can do: (1) Find songs that use the same chord progression and (2) see the most likely chord given the current selection.
My musical knowledge from middle school jazz band is long gone, but it's fun to explore, and you'll likely find relationships to songs that you didn't expect. [Thanks, Dave]
Shan Carter, Amanda Cox, and Mike Bostock for The New York Times, analyzed movie trailers for five best picture nominees. The horizontal axis represents time elapsed during a trailer, and the vertical axis represents when that clip occurred during the movie. The above is for Silver Linings Playbook:
"Silver Linings Playbook" follows the standard model for trailers, according to Bill Woolery, a trailer specialist in Los Angeles who once worked on trailers for movies like "The Usual Suspects" and "E.T. the Extra-Terrestrial." While introducing the movie’s story and its characters, the trailer largely follows the order of the film itself.
Because the order of the trailer is pretty much the order of the movie, you see a straight line with a downward slope most of the way. On the other hand, the Lincoln trailer jumps around showing a zig-zag pattern.
In addition to the charts, the healthy dose of annotation provides interesting tidbits on the reasoning behind pace and scene choice.
With the State of the Union address tonight, The Guardian plotted the Flesh-Kincaid grade levels for past addresses. Each circle represents a state of the union and is sized by the number of words used. Color is used to provide separation between presidents. For example, Obama's state of the union last year was around the eighth-grade level, and in contrast, James Madison's 1815 address had a reading level of 25.3.
My guess is this has to do with changes in how we write and talk more than anything else. Lee Drutman and Dan Drinkard for the Sunlight Foundation ran a more rigorous analysis on Congressional records back in May, and the declining trend is similar.
Information visualization firm Periscopic just published a thoughtful interactive piece on gun murders in the United States, in 2010. It starts with the individuals: when they were killed, coupled with the years they potentially lost. Each arc represents a person, with lived years in orange and the difference in potential years in white. A mouseover on each arc shows more details about that person.
Carlos Scheidegger and Kenny Shirley, along with Chris Volinsky, visualized Major League Baseball Hall of Fame voting, from the first class in 1936 (which included Babe Ruth) up to present.
All a fan can do is accept that Baseball Hall of Fame voting, conducted by the Baseball Writers Association of America (BBWAA), is a phenomenon unto itself. If we can't understand baseball Hall of Fame voting, though, maybe the next best thing is visualizing the data behind it. The set of interactive plots on this webpage is our attempt to do that. We were especially interested in two things: (1) viewing the trajectories of BBWAA vote percentage by year for different players throughout history, and (2) simultaneously viewing the career statistics of these players, to help find patterns and explain their trajectories (or to reassure ourselves that the writers really are crazy).
The interactive is on the analysis side of the spectrum, so you might be a bit lost if you don't know a lick about baseball. However, if your're a baseball fan, there's a lot to play around with and dimensions to poke around at, as you can filter on pretty much all player stats such as home run count, batting average, and innings played. At the very least, you're getting a peek at how statisticians pick and prod at their data.
Start at the examples section for quick direction. I eventually found myself looking for downward trajectories. Poor Mark McGwire. [Thanks, Chris]