Don’t step so far away from the data that you miss the details that provide meaning to the overviews.

Apparently ladybugs migrate this time of year, and it’s enough to show up on the radar as a giant rain cloud. Yeah.

The large echo showing up on SoCal radar this evening is not precipitation, but actually a cloud of lady bugs termed a "bloom" #CAwx pic.twitter.com/1C0rt0in6z

— NWS San Diego (@NWSSanDiego) June 5, 2019

For Lapham’s Quarterly, Elizabeth Della Zazzera turns back the clock to maps used for navigation, starting with the 1300s and through 1720:

From the fifteenth to the eighteenth century, European powers sent voyagers to lands farther and farther away from the continent in an expansionist period we now call the Age of Exploration. These journeys were propelled by religious fervor and fierce colonial sentiment—and an overall desire for new trade routes. They would not have been possible without the rise of modern cartography. While geographically accurate maps had existed before, the Age of Exploration saw the emergence of a sustained tradition of topographic surveying. Maps were being made specifically to guide travelers. Technology progressed quickly through the centuries, helping explorers and traders find their way to new imperial outposts—at least sometimes. On other occasions, hiccups in cartographic reasoning led their users even farther astray.

I particularly liked the part where in fourteen hundred ninety two, Columbus sailed the ocean blue — and made miscalculations because he misread the units on a map and ended up in the wrong part of the world.

Krist Wongsuphasawat, who recently interviewed for a healthy helping of visualization jobs, outlines the questions asked and the general flow of things.

[T]here are some sessions that your data visualization skills will play the key roles, but there will be tests for other skills as well. As I have mentioned earlier, data visualization is one of the main skills, but having only that is usually not good enough to land the roles. So do your homework, figure out what are the skills required for the target roles and make sure you can tick all of the checkboxes. If you are choosing the engineering track, there will be lots of expectations for front-end engineering skills.

From there, the tasks presented to you seem to vary a lot depending on what a company is looking for. Sounds stupendous.

Fathom Information Design recently made tools to find patterns in documents of text. They applied their tools to Bob Ross:

Using custom tools we’ve built to understand large document sets, we analyzed the transcripts of all 403 episodes of Bob Ross’ “The Joy of Painting” to see how his famous phrases evolved over 31 seasons. That analysis, which you can read in detail, revealed the clusters shown here, which are formed by patterns in the language Ross uses when talking about each episode’s painting.

For The Pudding, Matt Daniels and Russell Goldenberg used Wikipedia pageviews to replace city names with each city’s most popular resident:

Person/city associations were based on the thousands of “People from X city” pages on Wikipedia. The top person from each city was determined by using median pageviews (with a minimum of 1 year of traffic). We chose to include multiple occurrences for a single person because there is both no way to determine which is more accurate and people can “be from” multiple places.

So you end up with LeBron James for Akron, Barack Obama for Chicago, etc.

Fun.

See also the (non-data-driven) USA song map, which inspired this one. My favorite in this map genre is the series from R. Luke DuBois, who used online dating profiles to replace city names with the most unique personal qualities.

James Holzhauer is on a record-breaking Jeopardy! win streak. It’s not so much for the number of wins in a row — an impressive 30 so far — but for how much he wins per game. He’s on pace to break current record-holder Ken Jennings’ total winnings of $2.5 million in less than half the number of games.

Chicago Tribune made this chart to show Holzhauer’s cumulative sum:

Holzhauer commented: “This needs a @KenJennings overlay. Call it the bunny slope”

Ken Jennings responded: “In fairness to the graphic designer, it’s really hard to fit such a long streak on this teeny Holzhauer-scale chart.”

Not sure what’s more nerdy: the jokes or that I find them amusing.

Every month I collect links to visualization tools and resources. Here’s the good stuff for May 2019.

Christine Sun Kim, a deaf artist known for her work visualizing and creating experiences around sound, recently took up charts as a medium. From Anna Furman for The New York Times Style Magazine:

Channeling her experiences into images of geometric angles, musical notes and meme-like pie charts, Kim playfully combines different sign systems to create what she calls a “common language that all people can connect to.”

What’s she’s reading right now:

Maggie Nelson’s “The Art of Cruelty” and W.E.B. Du Bois’s “Data Portraits: Visualizing Black America.” I’m really into depictions of data. Du Bois’s book is a series of hand drawings and data graphs that visualize America. It’s just beautiful.

Nice.

Vox delves into why Ls and Rs often get replaced by Asian speakers using English as a second language. Some sounds aren’t prevalent in other languages, and it’s not the same across all Asian languages.

For The Guardian, Niko Kommenda shows the decrease in coal usage for power since 2012. As of this writing, it’s been just under 11 straight days with 0% of power generated by burning coal.

The data comes from Gridwatch, which in turn scrapes reports using the Balancing Mechanism Reporting Service from Elexon. Is there a US equivalent?

For The New York Times, Keith Collins shows the growing popularity of summer sequels among the big movie studios. If there is money to be made, they will come.

People misinterpret charts all of the time, because they go in with the wrong expectations before they even fully interpret what a chart is about.

Shelly Tan, for The Washington Post, has been counting on-screen deaths in Game of Thrones over the past few years. As the season ended, Tan described her process in an entertaining Twitter thread:

This graphic had a lot of numbers, so here are the final ones:

– 5 years of working on this project
– 6887 deaths
– 290 character illustrations
– Far too many hours of sleep lost

And now, at the end of it all, my watch has finally ended. Thanks for following along pic.twitter.com/w7VUPjJHE8

— Shelly Tan (@Tan_Shelly) May 22, 2019

I kept thinking about how her process transfers to counting all things. You know, like the decennial Census. The hand-wavy process always seems so straightforward. It’s like, sure, it’ll take a while, but the challenge is just time. But then you get into it, and there’s all these small bumps along the way that make everything more complicated. And then you’re like, great, well, I’ve already come this far. Better keep on counting.

Ivana Seric is a data scientist for the Philadelphia 76ers who tries to improve player effectiveness by analyzing tracking data. Aki Ito for Bloomberg:

I really want to see the relationship of winning and teams who more deeply follow statistics. Is it at a place yet where this actually helps or is still more about gut and heart?

For FiveThirtyEight, Amelia Thomson-DeVeaux and Gus Wezerek categorized and mapped new abortion restrictions enacted by state legislatures from 2011 to 2019:

The result is a complicated patchwork of abortion laws that have made it more time-consuming and expensive to get the procedure in certain parts of the country. In addition to counseling, waiting period and ultrasound requirements — all of which can increase the time and cost associated with the procedure — clinics have been steadily closing over the past few years because of a combination of factors, including the new state laws.

Giorgia Lupi, whose work exemplifies the use of data and visualization outside of analytic insights (think Dear Data), is now a partner at design consultancy Pentagram. For FastCompany, Mark Wilson with the news:

At Pentagram, where she’ll have access to the biggest brands in the world, Lupi believes she can find a greater reach for data design in general. “It’s a good opportunity to expand graphics beyond the niche field of data visualization, and figure out how data visualization can be part of our daily experiences–in the things we consume, wear, and see,” Lupi says. “I want to explore things I don’t think have been done before.”

Whoa.

Rachael Dottle, for FiveThirtyEight, looked for political differences in cities and ranked them, based on precinct voting margins for the 2016 election:

To see just how politically segregated America’s urban areas are, we used each city’s 2016 election results to calculate its dissimilarity index — basically, a number that tells us how separated its Republicans and Democrats are from one another, with higher numbers indicating more segregation. This technique is most often used to measure racial segregation, but political scientists have also used it to calculate partisan segregation. (One drawback of this method: A place that votes almost uniformly for one party — Democrat-soaked San Jose, California, for example — will have a low dissimilarity score. But that doesn’t mean Republicans and Democrats live next to each other in these places; it may just mean that the larger region is politically segregated, leaving the whole city as essentially a one-party enclave.)

Unsurprisingly, political and racial segregation are related.

The Upshot asked a similar question last year using similar data and mapping scheme, but they framed it differently.

The last episode is coming. Some people don’t like how it’s ending, and the IMDB ratings seem to reflect this. For The Upshot, Josh Katz and K.K. Rebecca Lai charted the changes over the seasons.

Reminds of me of the (now defunct) Graph TV a while back.