Baseball games grew longer over the decades, with the average length well over three hours in recent years. Ben Blatt and Francesca Paris, for NYT’s The Upshot, show how a few rule changes this season keep the ball moving for shorter games.
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The Programme for International Student Assessment (PISA), run by the OECD since 2000, surveys teenage students to estimate the quality of education around the world. One of the questions asked: “What kind of job do you expect to have when you are about 30 years old?” For Vox, Alvin Chang walks through how the responses changed over the past two decades, which appears to suggest that students are less certain about what the future holds.
There are some tricky spots in explaining misalignment between ambition and preparation, but Chang does a good job of moving along step-by-step.
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With a cross between the games Wordle and GeoGuessr, Russell Samora for The Pudding made a daily game that challenges you to geolocate a place based on images of the place from Wikimedia Commons. You get five guesses to click on a map, and after each guess you get a new image and the number of miles you were off.
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When you think of household types in the United States, the most common ones probably come to mind: single, married couple, married couple with a kid, or married couple with two kids.
But there are thousands of others. Let’s look at all of them.
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You’ve probably heard about big data breaches over the years. They’re in the news or you get an email from a company that kindly reminds you to reset your password, because a few million accounts might have been exposed. Julian Fell, Ben Spraggon, and Matt Liddy for ABC News show how bits of information from all the known breaches can add up to form a complete profile of you.
Enter an email address and see how many breaches it went through, plus what information was stolen. Yay, 14 breaches for me.
Also check out Have I Been Pwned, where the data for the interactive comes from. It provides more background on individual breaches. [Thanks, Matt]
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You’ve probably heard of esports, where people compete against each other in multiplayer video games. Financial Modeling World Cup runs esports for Microsoft Excel. Players get a fixed amount of time to accomplish complex spreadsheet tasks, and whoever figures out the correct answers in the least amount of time wins.
The two-hour all-star battle last year even had running commentary and post-competition interviews. It is so gloriously nerdy. [via kottke]
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Cutting the national debt is a complex process that involves a lot more than personal preferences of an individual. But what if you simplified the task to a bunch of yes-no answers and made it into a Tinder-style swiping game? Szu Yu Chen, Chris Alcantara, and Jeff Stein for The Washington Post put you in charge of the choices.
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Research by Edward W. Felten, Manav Raj, and Robert Seamans provides estimates for how occupations will be impacted by artificial intelligence, such as ChatGPT and Midjourney, based on AI exposure and demographics. Yan Wu and Sergio Peçanha, for The Washington Post, provide a rundown and searchable charts for the work so that you can check your own occupation.
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To show income sources for different groups and people, I wanted to show a percentage breakdown between wages, business, and investments, but also show the total amounts.
A while back I showed how people spend their money using a mosaic plot followed by unit charts, so I figured I’d just combine the two, and this is what I got, which shows average income sources by income group.
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The 2023 Eurovision Song Contest finished up this past weekend with the winning song coming from Sweden. Hundreds of millions of people watch the contest worldwide, but I’m pretty sure most Americans’ impressions come from the satirical Will Ferrell movie, so this visual guide by Reuters should be helpful.
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Alvin Chang, for The Pudding, illustrated the search for his kimchi, which is a metaphor for other things. Interact with the items in the story and be sure to turn the sound on. There are charts tucked away for historical context.
Many of my best memories throughout life are tied to food, so this one struck home for me.
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To show the scale of tax cuts and Australia’s budget, ABC News takes the long, vertical unit chart approach, and the squares just keep coming. This is one of those scrollers that works best on mobile.
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Filed under random but fun calculations, Alasdair Rae estimated the number of people within interstate boundaries:
I loaded up a MapTiler streets backdrop layer in QGIS, created polygons from the the US national road network file from the Department of Transportation website (this required a lot of error checking/fixing) and then summed the population of all areas bounded by Interstates – including those in Hawaii, Alaska and Puerto Rico.
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People scored their current life from 0 to 10, where 0 is their worst possible life and 10 is their best possible life. The older they were, the more likely they were to say they were living their best.
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Achim Zeileis and Paul Murrell provide a rundown of the more user-friendly color palettes available in R by default since version 4.0. The new palettes make it easier to see differences and less like saturated output from an old computer.
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Mona Chalabi, known around these parts for her illustrative approach to data journalism, was awarded a Pulitzer Prize for her New York Times piece on Jeff Bezos’ extreme wealth. She compared the scale of Jeff Bezos wealth against median wealth, and the absurdity of the scale leant itself to ridiculous comparisons.
Amazing. Congratulations to Mona.
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Charts that use two different scales on the same vertical often get the automatic “misleading” label, because if you stretch and shrink two data series enough, you’ll eventually find a way to make them look related. Toph Tucker argues that the automatic dismissal is misguided:
So yes, dual axes transform the series, and that transformation can lie. But it is the same kind of transformation that is already built into the Pearson correlation coefficient. Insofar as dual axes are bad, so is the Pearson correlation coefficient. Their merits and their badness go together. Dual axes are good at showing spurious correlation because they are good at showing correlation.
The challenge is that when you see a line chart with time on the horizontal axis and multiple data lines, it’s hard to separate coordinate systems and we’ve learned to read the lines as patterns over time. On the other hand, a scatterplot (or a connected one for time) highlights the relationship.
So while you don’t need to avoid dual axes completely, you should be careful when you do.