Other than calls from my wife, I can’t even remember the last call I received that wasn’t a robocall. Based on data from the Robocall Index and the American Community Survey, Sara Fischer for Axios provides this straightforward map of robocalls by state.

For FiveThirtyEight, William T. Adler and Ella Koeze describe how a metric called partisan bias is used to assess partisan gerrymandering. As you might imagine, it’s fuzzy.

Marian Eerens charted the colors of each Adventures of Tintin book cover. The only thing missing is the actual covers on the mouseover.

It’s a straightforward thing, but I find these sort of abstract color charts calming for whatever reason. See also the colors of: campaign logos, LEGO kits, Game of Thrones episodes, Mister Rogers’ cardigans, Western films, Avengers comic book covers, science fiction book covers, and more.

Compared to a computer’s pseudo-random number generator, we are not good at picking random numbers. Ilya Perederiy made a quick game to show how bad you are:

Your fingers tend to repeat certain patterns even if you don’t notice it. The program keeps a database of each possible combination of 5 presses, and two counters are stored under each entry — one is for every zero that follows the combination, and the other one is for all the ones that follow this combination. So every time you press a key, an entry in the database gets updated. To make a prediction, the program needs only to look up the entry corresponding to the last 5 presses and decide by looking at the counters which key press is more likely to follow. The rest is up to Fortuna (velut luna). I’ve run this script with 200 pseudo-random inputs 100,000 times, and found that the distribution of correct guesses is approximately normal with µ=50% and σ=3.5% (this agrees with the binomial estimation, of course). The probability of the program guessing your inputs >57% (µ+2σ) of the time purely by chance is very slim, which suggests that you really aren’t good at making random choices.

Trey Harris, a previous tech administrator for a university, tells the story of a statistics department that couldn’t send email farther than 500 miles away. The story is more about the peculiarities of server admin in 2002, but I’m more interested in those statisticians:

“We could send email. Just not more than–”

“–500 miles, yes,” I finished for him, “I got that. But why didn’t you call earlier?”

“Well, we hadn’t collected enough data to be sure of what was going on until just now.” Right. This is the chairman of *statistics*. “Anyway, I asked one of the geostatisticians to look into it–”

“Geostatisticians…”

“–yes, and she’s produced a map showing the radius within which we can send email to be slightly more than 500 miles. There are a number of destinations within that radius that we can’t reach, either, or reach sporadically, but we can never email farther than this radius.”

Honestly, I’m not sure what’s more surprising: the 500-mile physical limitation on email or the statisticians troubleshooting for a few days before contacting the tech. [via kottke]

John Tukey wrote, “The greatest value of a picture is when it forces us to notice what we never expected to see.” Not everyone wants to see though.

FastCharts is the public version of the Financial Times’ in-house solution for making charts, uh, fast. Load some data. Get the chart fast. FastCharts. Kachow.

To connect servers around the world, there are actual cables that run under the ocean. The New York Times mapped current and future cables, with a focus on the ones owned by Amazon, Facebook, Google, and Microsoft. “Content providers like Microsoft, Google, Facebook and Amazon now own or lease more than half of the undersea bandwidth.” Sure. Totally fine.

TwoTone, by Datavized and supported by the Google News Initiative, is a straightforward tool to sonify a dataset. Upload your data, select the metric, speed, and instrument, and you get a tune output.

If you thought visualization was tricky perceptually, then you’re in for a treat with sonification. The two most useful examples I can think of off-hand were event-based, so maybe start with something like that.

I’m thoroughly enjoying the work coming from graphic designer Scott Reinhard as of late. He combines modern techniques with vintage feels. In his most recent, he provides a “look at what the lower 48 states of the United States would look like if it were flipped inside out.” Grab the print.

While we’re on the subject of distributions, Fathom used a collection of beeswarm charts to show documents about the Mueller investigation over time and connections between individuals. It’s called Porfiry. Filled circles represent documents that represent connections, and circle size represents the number of documents.

Right in my wheelhouse, Russell Goldenberg and Amber Thomas for The Pudding looked at where top high school basketball recruits end up in the NBA (if they’re drafted at all). I like how you get the distributions at each level and the path of each player. The distributions build using animation, which is something I’ve been interested in as of late.

Histograms for a general audience can be a challenge. I’m curious if building up the distributions over time can be helpful.

Timo Aho and Pekka Niittyvirta used sensors, LED lights, and timers to display future water lines:

By use of sensors, the installation interacts with the rising tidal changes; activating on high tide. The work provides a visual reference of future sea level rise.

The installation explores the catastrophic impact of our relationship with nature and its long term effects. The work provokes a dialogue on how the rising sea levels will affect coastal areas, its inhabitants and land usage in the future.

Love that a single line of light can represent so much.

John Snow, who often gets the credit for showing the geographical patterns of a cholera outbreak in London in 1854, wasn’t the only one visualizing data at the time. James Cheshire put together a collection of other charts made at the time.

[I]t wasn’t just Snow producing innovative maps and charts to support his cause. Snow was part of an arms race to get the best data communicated by the most compelling maps/ charts, to evidence his side of the debate against his contemporaries – people like William Farr who was also a master data visualiser.

Here’s a fun thing to try in R. Jean Fan posted some code snippets where you can load an image file and the result uses a hatching technique to recreate the image with shapes.

See also: Using the traveling salesman problem to re-sketch images.