Redesigning a visualization can be useful in teaching a point. Make a graphic better (or “better” depending on what angle you’re looking from) with a different layout and visual encodings. Perhaps the most well-known is Edward Tufte’s redesign from his book Visual Explanations in which he reworks a diagram used in decision-making for the space shuttle Challenger launch.

However, Fernanda Viégas and Martin Wattenberg explain why such redesigns can be problematic and offer a more useful approach.
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Designer Michael Pecirno experiments with single-subject maps in his project Minimal Maps. No boundaries, just landscape.
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From Finger Magazine a few years back, in the heyday of rickrolling and humor charts. Maybe some choose to forget this era, but I’m never gonna give you up, let you down, or run around and desert you.

Location-based data from social media can be interesting to analyze and map, but there are a lot of inherent challenges with the data. The main one, which designers often ignore, is that it’s safe to make inferences straight from the tweets alone. That is, there’s an assumption that the data is representative of the real-life population when in fact there are a ton of social implications to consider. The folks at Floatingsheep, a team of geographers, know better. CityLab highlights some of the team’s work.
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Data journalism is relatively new as a concept, but in practice it has been around for a good while. Scott Klein for ProPublica tells the story of Horace Greeley, an editor for the New York Tribune and a congressman in the mid-1800s. Greely was displeased with a law that specified mileage compensation for travel to the capital, so he found a way to prove his point with data.
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Ri Liu provides an exploratory view of gender gaps around the world through labor participation, parliament participation, and income. Be sure to try the sorting options, which help you pull out quick insights from about 160 time series.

There are a lot of beards and other types of facial hair in Major League Baseball. In case you’re wondering how many and at what level, the Washington Post has you covered with a breakdown.
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Jeffrey Heer, computer science professor and co-founder of Trifacta, describes the future of visualization in a short 10-minute talk. It’s one where people aren’t taken out of the analysis loop, but computers can provide a bit more help than they do now.
Watch the talk

If you don’t want to bother with JavaScript but want to publish interactive graphics for the web or use interaction to explore your data, htmlwidgets might be for you.
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In a straightforward map, Seth Kadish shows the percentage of county residents who commute out of state, according to estimates from the American Community Survey.
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I hate all things commute- and traffic-related, and it’s probably why I like to learn about what makes commutes painful. Maybe if I know more about what’s happening, I won’t get so frustrated when I have to drive.

Transportation engineering PhD candidate Lewis Lehe has a look at bottlenecks and gridlock, creating simulations of both. The former is when too many cars want to do the same thing at once, like enter at a freeway entrance. Gridlock is when a bottleneck in one direction causes a bottleneck in the other direction, and then the same happens the other way around, starting a horrible, horrible cycle.

Stefanie Posavec, known around these parts for her manual data design and Giorgia Lupi, known for constantly drawing and searching for complexity, are sending each other data postcards once a week for a year. They call the data-drawing project Dear Data.
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People like to poke fun at 3-D charts, mostly because they don’t work or a third dimension just isn’t needed. However, this chart by Gregor Aisch and Amanda Cox for the Upshot is a fine exception to the rule.
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For a class project, Katie Kowalsky, Dylan Moriarty, and Robin Tolochko examined changes in abortion policy since Roe v. Wade in 1973.
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The Elements of Data Analytic Style by John Hopkins biostatistics professor Jeff Leek is a non-technical guide to the stuff they don’t always cover in Stat 101, and it’s priced as pay-what-you-want. In short, it tells you how to be a good data analyst.

I just started flipping through it, and the text is straightforward with a lot of practical advice, based on experience. It takes you from tidying your data, to exploratory analysis, causality, presenting your results, and reproducibility. Lots of bullet points and common pitfalls.

Get it now. And while you’re at it, you might also be interested in the Data Science specialization from Leek and his John Hopkins cronies on Coursera.

In their continued work on the No Ceilings project, Fathom describes the current iteration of the site that shows 20 years of data, across hundreds of indicators.
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Unlike traditional bracket-picking, the Upshot’s bracket game has a twist. You still want to pick the winners, but you get rewarded extra points if you choose a winning team that’s less of a crowd favorite.
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