The Meteoric Rise in Boys' Names Ending in 'N'

The hegemony of "Ryan" and "Aidan," as seen through Social Security Administration data 

Ryan. Ethan. Aidan. Mason. Since 2011, four of the 10 most popular names for baby boys have ended in the letter "n." To the extent that letter currently concludes a whopping 36 percent of boys' names.

The rise of "n"-at-the-end is a relatively recent thing, suggests Baby Name Wizard's Laura Wattenberg. If you look at the letter distribution from the year 1900, she notes, there were about 10 letters (most popular among them: "e," "n," "s," and "y") that proved popular as endings of boys' names. By 1950 that number had declined to about six, with "d" replacing "e" in the most-popular group. Today, to a crazy degree, it's all about the "n."

That rise is nicely visualized in the GIF above, created by the data scientist David Taylor for his blog prooffreader. Taylor compiled Social Security Administration data like those depicted below and compiled them into a shifting, composite image; in it you can see the rise of "n"—especially after the mid-1970s. 

courtesy David Taylor

I asked Taylor how he came to create the GIF—and how he got interested in this kind of dataviz in the first place. Here's what he told me: 

I work in genomics (a biofuel research project), so we have a TON of data to analyze, and it's always a struggle to create simple yet accurate visualizations of it. I sort of fell into it because nobody else in the lab was interested (they prefer doing science, go figure -- or as I like to say, they have a more restrictive definition of science than I do). I realized to my surprise that not only was I sorta good at it, I really enjoyed it! Since looking at genes all day gets kind of monotonous, I found myself downloading other public domain data sets on a lark and using them to practice my data mining and charting skills.

I started the blog last fall, and was certainly not expecting that I'd have almost 300,000 visitors six months later! I seem to have found a niche between overly simple and overly complicated data visualizations (probably because I'm self-taught, so I remember what it was like to look at a graph and not understand anything it was trying to say). I'm still learning, and I've been gratified that the vast majority of feedback has been either positive or, if negative, constructive and respectful. Maybe all those rumours about trolls on the Internet are exaggerated. Hmm, what dataset could I use to study that question ...?