Answer the questions. Produce more focused and useful charts.

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Vox, in collaboration with The Pudding, looked at what happens when a song goes viral on TikTok. It heads down the TikTok-to-Spotify pipeline, which signals money to be made and draws labels to take advantage.

Matthew Crump, a psychology professor who discovered high volume cheating in his class via WhatsApp, outlines the saga in five parts. Bonus points for use of R to analyze the evidence:

I do a lot of teaching on using computational tools for reproducible data analysis. I can input some data and run it through a script for analysis. When the data changes I can run it through the same script and get the new analysis. The chat archive had changed and this time it was easier to do the analysis all over again. I redid all the counts of academic integrity violations and rewrote the forms spelling out sanctions for each student. So many forms, I died a little inside once for every form.

There are baby formula shortages in the United States. A criticism from some who don’t know what they’re talking about are for parents to “just” breastfeed. Alyssa Rosenberg for Washington Post Opinion discusses the challenges behind that from a time perspective:

Even in the best-case scenario, breastfeeding isn’t free. It costs money for the supplies that keep a nursing mother comfortable and healthy enough to keep producing milk. And it costs time. I can show you exactly how much time, because I used an app to track every minute I spent nursing and pumping over the first six months of my son’s life.

She then translates the many hours spent into dollars, based on your salary.

To estimate public interest in the many political issues across the United States, Axios used Google Trends data to map issues by congressional district. Switch between the many topics, and you see a choropleth map (that can change to a cartogram), along with a barcode chart to show the distribution of interest among all districts.

I’m not sure if it’s that beneficial to see the overall geographic distributions for most topics, but it’s useful as a point of reference to look at specific districts. For me, the barcode chart is the most interesting with the distributions shifting quite a bit from topic to topic.

In election reporting, there’s a gap between real-time results and final results, so news orgs use statistical models to show where results appear to be headed. For The Washington Post, Adrian Blanco and Artur Galocha explain the basic concepts behind their model, using a fictional state called Voteland.

RJ Andrews digs up the PC archives of charting software. Scrolling through the thread, you can see the roots of Excel in the software that pre-dates the 1987 Windows release, along with what was considered nice back in the day. In many ways, such as in the interface, features, and chart types, things haven’t changed that much over the past few decades.

Here’s the good stuff for May.

This chart from The New York Times, based on estimates from Our World In Data and World Bank, shows GDP per capita against gun homicide rates. The United States stands alone. Why.

The Washington Post maintains a database of school shootings (which is sad in itself that such a thing has to exist) to keep record of tragedy that the U.S. government does not track. They calculated the number of kids since Columbine who were exposed to such terrible events:

The Washington Post spent a year determining how many children have been affected by school shootings, beyond just those killed or injured. To do that, reporters attempted to identify every act of gunfire at a primary or secondary school during school hours since the Columbine High massacre on April 20, 1999. Using Nexis, news articles, open-source databases, law enforcement reports, information from school websites and calls to schools and police departments, The Post reviewed more than 1,000 alleged incidents but counted only those that happened on campuses immediately before, during or just after classes.

The events are terrible when they happen, and they go on to affect thousands of others for a lifetime — kids who were just going on with their daily activities.

Alicia P.Q. Wittmeyer, for NYT Opinion, approached the one-million mark for Covid deaths with text messages. The piece starts on February 29, 2020, when the first person died because of Covid. The count to 1 million begins, and a recurring ticker reminds you of the increase over time. Thirteen text message threads between someone who died and a person who cared remind you that the numbers are real.

The war in Ukraine continues, but the scale and objects appear to have changed over time. Josh Holder, Marco Hernandez, and Jon Huang for The New York Times mapped the shrinking scope as Russia loses more soldiers and resources.

Cindermedusae by Marcin Ignac is “a generative encyclopedia of imaginary sea creatures.” I’m into the aesthetic.

Alyssa Fowers and Leslie Shapiro, for The Washington Post, used the stories of 114 individuals to show weekly Covid deaths. Each story is “cut short”, making the length of each fragment match counts for the corresponding week.

My brain was slightly confused by the metaphor at first. The lower the count, the more an individual’s story is cut short, but my intuition expected that more deaths would mean stories were cut short more.

That said, the sentiment is in the right place. Maybe the stories didn’t need to be tied to weekly counts? I’m imagining something closer to Periscopic’s piece from 2013 on lives cut short by guns.

Without purpose, there isn’t a whole lot to grasp on.

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Neil Halloran, known for his documentary films that lean strongly on data visualization, collaborated with RAND to explain the possibility (or lack) of a nuclear winter. In the last third of the film, Halloran also discusses the pursuit of absolute truth and whether it’s truly worth it in the end. Lots to think about.

If you’re into R and analyzing sports data, you’ll want to save this CRAN task view:

This CRAN Task View contains a list of packages useful for sports analytics. Most of the packages are sport-specific and are grouped as such. However, we also include a General section for packages that provide ancillary functionality relevant to sports analytics (e.g., team-themed color palettes), and a Modeling section for packages useful for statistical modeling. Throughout the task view, and collected in the Related links section at the end, we have included a list of selected books and articles that use some of these packages in substantive ways. Our goal in compiling this list is to help researchers find the tools they need to complete their work in R.

Leonardo is an open source project from Adobe that helps you pick accessible colors. There’s a JavaScript API along with a browser tool that lets you select colors interactively.

Color is a common encoding to visualize data. It can be used directly in choropleth maps or heatmaps, indirectly as a redundant encoding, it can be decorative, and it can be used for all the things in between. However, a color scheme doesn’t work if a big chunk of your audience is not able to see the differences. So it’s good to see these sorts of tools available.

Leonardo is an extension of Chroma.js. Gregor’s Chroma.js palette helper is still my go-to to keep color schemes in check.

Sergio Peçanha and Yan Wu, for The Washington Post, used a combination unit chart with individual icons to represent the scale and weight of the near million Covid deaths in the United States.

Compare this with NYT’s particle-based charts and Axios’ scaled squares. It’s kind of in between the two in level of abstraction, but all three carry similar messages, with a focus on the one-million mark.