Mike Bostock and Shan Carter visualized how states have shifted parties over the years, going back to 1952.

Recent elections have placed a heavy emphasis on “swing states” — Ohio, Florida, and a handful of other states most-easily swayed from one party to the other. Yet in the past, many more states shifted between the Democratic and Republican parties. A look at how the states stack up in the current FiveThirtyEight forecast and how they have shifted over past elections.

Each row represents an election, and the horizontal axis reflects the size of a lead for a party. So as you scroll down, you can see how much (or little) a state has changed across elections.

Instead of taking the obvious exploratory route, where you select your state and scroll to the bottom, Bostock and Carter took a story-driven approach. Points of interest are on the left. Click on a button and the relevant states for that insight are highlighted. (Although you can still mouse over states to see their paths and keep states highlighted by with a continuous scroll.) This is a good one worth exploring for a while.

See also Adrien Friggeri’s interactive from earlier this year that shows Senate agreement.

Sustainable Design Lab at MIT and MoDe Studio estimated the potential hotspots for electric photovoltaics in Cambridge, Massachusetts and mapped it.

“High PV Potential Area” is the footprint, in square feet, of the portions of a roof that, by considering both the real surface projection to its actual slope and this surface’s annual irradiation, yield a “good” to “excellent” result. These values are based on MIT’s calculations and are shown as orange and yellow dots on the viewer, respectively.

If all the door-to-door salesmen trying to sell me solar panels showed me something like this for where I live, I’d be a lot more receptive.

Number of likes and shares for a Facebook post are just simple aggregates that give you an idea of how popular that post was, but they don’t tell you anything about how that post got so popular. For Facebook Stories, Stamen Design explored how a single post can spread through the network, via three viral photos shared by George Takei.

Each visualization is made up of a series of branches, starting from George. As each branch grows, re-shares split off onto their own arcs. Sometimes, these re-shares spawn a new generation of re-shares, and sometimes they explode in short-lived bursts of activity. The two different colors show gender, and each successive generation becomes lighter as time goes by. And the curves are just for snazz.

So you see a beautiful burst in the beginning, as the photo is shared by people who follow Takei, and then the photo spreads within smaller groups of friends. The above is from the animation that shows how a graphic for famous failures spread.

From the October 10 Boston Metro. Oops. [via]

There are an estimated 20,000 to 25,000 polar bears in the world, and the population is expected to decline by 30 percent over the next three generations. Periscopic, in collaboration with the Polar Bear Specialist Group, highlighted the changing populations in this interactive.

The data can be viewed by subpopulation, by nation, and by ecoregions. In the first two views, you can click on geographic regions to see more details about the area, which includes a text overview and time series for more troubling numbers on polar bears killed by humans and pollution. Finally, when you click on a time series or the pollutant levels, you can see the data at a higher granularity.

So there are a few ways to examine the data and different angles to explore. You’ll want spend some time with this one.

I’m not sure where this is originally from, but I found it on an intro to geology course page. What happens when midnight comes around again?

As you’ve probably heard, Apple and Samsung have been in a bit of a kerfuffle over the past few months. We own that patent for that thing. No, we have this patent for that. The state of technology patents is all over the place. The New York Times takes a closer look. Also, don’t miss the video and side-by-side comparisons.

How many people does it take for there to be a 50% chance that a pair in the group has the same birthday? Only 23 people. What about a 99% chance? Maybe even more shocking: 57 people. This is the birthday problem, which every undergrad who’s taken a stat course has seen. Steven Strogataz explains the logic and calculations.

Intuitively, how can 23 people be enough? It’s because of all the combinations they create, all the opportunities for luck to strike. With 23 people, there are 253 possible pairs of people (see the notes for why), and that turns out to be enough to push the odds of a match above 50 percent.

Incidentally, if you go up to 43 people — the number of individuals who have served as United States president so far — the odds of a match increase to 92 percent. And indeed two of the presidents do have the same birthday: James Polk and Warren Harding were both born on Nov. 2.

The Johnny Carson clip referenced in the article is worth watching. Carson tries to test the results with the audience, but goes about it the wrong way.

Santiago Ortiz visualized every episode of the show in the interactive Lostalgic. It’s a set a four views that shows character occurrences and relationships and the lines they said during various parts of each episode.

The first view, shown above, is a bar chart vertically arranged by time, where each row represents an act. A profile picture is shown whenever the corresponding character says something. The next two views, the network graph and co-occurrence matrix show interactions between characters, and finally, if you want to relive it all over again, you can choose the reenactment, and the animation will cycle through the characters and scripts.

I only watched a handful of episodes right before the last one, but realized my efforts to watch all six seasons would be useless, even if I watched 24/7 before the finale. I got to the part where they found a dead person in a tree. So I’m only appreciating this from the technical side. I suspect fans of the show will love it. [Thanks, Santiago]

Mapping data over time can be challenging, especially when you have a lot of data to load in the beginning. Torque, the new open source project by CartoDB, is a step towards making the process easier.

Torque allows you to create beautiful visualizations with big temporal datasets by bundling HTML5 browser rendering technologies with a generic and efficient temporal data transfer format created using the CartoDB SQL API. Torque visualisations work on desktop and ipads, and work well on temporal datasets with hundreds of thousands or even millions of datapoints.

It’s still in the early stages but should be one to keep an eye on.

Check out this map for a sense of what Torque can help you do. The map animates historical edits to OpenStreetMap in Madrid. Also this. [Thanks, Carlos]

In case you’re interested in learning how much you suck at US state geography, here’s a game to help. The goal is to match up states on the blank country map, and you end with an average error in miles. I did not do well. [via kottke]

Jeffrey Heer on visualization for interactive exploration:

We were visualizing the results of a chain of models, including text modeling and dimensionality reduction. These models can sometimes give rise to misleading results, which we then spotted in the visualization. This result led us to consider how visualizations must do more than just turn data into images — it is vital that visualizations support interactive exploration and verification, so that one can not only uncover new hypotheses but begin the process of assessing their credibility. Another result of this work is that the insights gained from the visualizations enabled us to design better machine learning methods, such that our mathematical models of textual similarity better matched the judgments of human experts.

The rest of the Scientific American article is worth reading, mostly for the other quotes from Heer and Ben Shneiderman.

Yes, this is real. Israeli Prime Minister Benjamin Netanyahu used a bomb-shaped diagram to illustrate the line that must be drawn to prevent Iran from creating nuclear weapons. No doubt this a serious matter, but I’m not sure the drawing lends value to the message.

In the same spirit of the quick update site on Olympic records a couple of months ago, the Guardian and Real Clear Politics tell you if Obama is still president and if Romney is president. Each balloon represents a state, sized by electoral votes, and the number of balloons in each hand represent projected voting, based on current polls. Straight to the point.

Hey, I think it’s election season, and you know what that means. It’s time to dig into campaign finance data from the Federal Election Commission. The Washington Post gives you a view into the amount of money raised and spent in both camps, where it’s coming from and where it’s going. They start with the high-level aggregates, and as you scroll down, you get the time series, followed by the breakdowns for money raised.

The spending categories at the bottom are the most interesting bit. They cover advertising and mail, down to consulting and events. Payroll was a lot higher than I would’ve thought.

In the latest Chrome experiment, Google mapped cloud coverage around the world in Cloud Globe. The interactive animation shows coverage from July 1, 2010 to September 12, 2012, with a globe that you can move around as expected and a timeline on the bottom that indicates high levels of coverage. As the animation plays through, storms are highlighted with a circle and pointer. Finally, you can turn on the vegetation layer, and the green regions happen to be under the clouds. Imagine that.

Jo Wood, a professor of visual analytics, visualized five million bike rides using data from Barclays Cycle Hire.

In the animation (see below) the least travelled routes begin to fade out after about 15 seconds – “like a graphic equaliser,” says collaborator Andrew Huddart, also at City University. Around the 1-minute mark, structure emerges from the chaos and three major systems become clear: routes around, and through, the lozenge-shaped Hyde Park in the west, and commutes in and out of King’s Cross St Pancras in the north and between Waterloo and the City in the east.

Each arc represents a trip from point A to point B (obviously not a true path or we’d see roads), and flow direction indicates which way people went the most between the two. [via The Guardian]

Now that you know how color labeling changes by gender, I bet you’re wondering how it varies by language. Dave Oleson and Dawn Ho had a look in this simple color wheel. You can hover over colors for labels by country, and you can search for colors via text box.

On the whole, it looks like countries have extremely similar conceptions of color. Type “blue” into the search box, click on the different countries, and you can see the overlap. There are outliers though. Some narrower colors – such as “purple” – are used much more in Japan than in Russia. The use of certain modifiers such as “light” are used pretty uniformly across the color spectrum in English, but much more prevalently in the Blue-Green region in Japanese.

I wish there were a better way to see differences between countries. Luckily, you can download the data and have a look yourself. [Thanks, Dave]

Update: When you search for a color and then click on the flags, you can see the differences between countries.