Exploring Data Visualization with Names

For this assignment, I visualized the ten most popular girls’ names in the U.S. from 2001 to 2010, using data from the Social Security Administration. I used Flourish’s bar chart with a year dropdown, so readers can step through the decade one year at a time and watch the rankings shift. Bars suit this data because each year is a ranked list.

The story I wanted to tell is a changing of the guard. Emily held the top spot from 2001 through 2007, then fell to sixth by 2010, and Madison dropped from second to eighth. Meanwhile, Isabella went from outside the top ten in 2003 to number one in 2009, and Sophia and Ava climbed from outside the list into the top five.

To make that story clearer, I changed several defaults. I turned off the legend, since every bar is already labeled, and switched to a single neutral color with Emily and Isabella highlighted so readers can follow them from year to year. I also fixed the x-axis maximum so it doesn’t rescale each year. With a fixed axis, you can see the bars shrink: Emily went from 25,059 birthnames in 2001 to 14,281 in 2010, and even Isabella’s winning total in 2010 was smaller than Emily’s in 2001.

This connects to our readings on honesty. Part of that decline may reflect parents choosing a wider variety of names, but U.S. births also fell after 2007, so the counts alone can’t tell the whole story. It’s also tempting to credit Twilight for Isabella’s rise, but as Tyler Vigen’s Spurious Correlations shows, a matching trend isn’t proof. Lauren Klein’s point that every chart comes from a particular context applies here too: names are cultural artifacts, and this dataset sorts every baby into a binary category. For DH, visualization is a starting point for asking questions, not a final answer.

1 thought on “Exploring Data Visualization with Names”

  1. I appreciate your connection between this dataset and Klein’s argument; I concur that it is important to remember where the data comes from. I think each chart should be designed in such a way that inherently provides the context. Though not every chart can be a perfect example of that, I believe this chart that you have here Is quite clear on the message you are trying to send with it. You have done good work tailoring the chart to fit your specifications. Did you experience any issues or difficulties when using Flourish? Rawgraphs.io was a little tricky for me and I am curious if Flourish offers anything different. Did you experiment with both programs or just choose Flourish?

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