Speaking of relationship timelines, Chris Lewis used texting history with his girlfriend after the first swipe on Bumble as the backdrop of their own story. A few 21k messages later, they’re engaged and live together. [Thanks, Chris]

Sarah Leo, a visual journalist at The Economist, looked through the archives and found some charts that could use a re-design.

After a deep dive into our archive, I found several instructive examples. I grouped our crimes against data visualisation into three categories: charts that are (1) misleading, (2) confusing and (3) failing to make a point. For each, I suggest an improved version that requires a similar amount of space — an important consideration when drawing charts to be published in print.

Very nice. Archive lookups are often accompanied by “ooo, vintage, therefore good” but Leo takes it the other direction.

Found this tidbit interesting: “Until fairly recently, we were less comfortable with statistical software (like R) that allows more sophisticated visualisations.”

Every month I collect practical resources, new tools, code, and datasets. Here’s the good stuff for March.

Sometimes you really do need to get away. Escape, part search engine and part research project from students at the MIT Senseable City Laboratory in Singapore, shows you the cheapest flights out of any given city. Just put in a location, and you get color-coded connections to everywhere around the world.

The Stanford Open Policing Project just released a dataset for police traffic stops across the country:

Currently, a comprehensive, national repository detailing interactions between police and the public doesn’t exist. That’s why the Stanford Open Policing Project is collecting and standardizing data on vehicle and pedestrian stops from law enforcement departments across the country — and we’re making that information freely available. We’ve already gathered over 200 million records from dozens of state and local police departments across the country.

You can download the data as CSV or RDS, and there are fields for stop date, stop time, location, driver demographics, and reasons for the stop. As you might imagine, the data from various municipalities comes at varying degrees of detail and timespans. I imagine there’s a lot to learn here both from the data and from working with the data.

There’s less than a month until taxes are due. It’s the most wonderful time of year, isn’t it? As you probably know, there are some changes in deductions, limits, and refund amounts this year, but who the changes affect depends on many variables. For Bloomberg, Ben Steverman and Marie Patino, provide an easier-to-follow breakdown of common groups and variables, how the groups’ total taxes differ from last year, and how they contrast against each other.

There’s a new hotness in chart town. It’s a bar chart. But it moves to show rankings over time.

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.