Data Driven Digest for December 19

Each Friday we share some favorite reporting on, and examples of, data driven visualizations and embedded analytics that came onto our radar in the past week.


The Song Remains the Same: Music is in the air at holiday time, and that can prompt people like David Taylor – a professional data wrangler with musical training – to compose fun data driven experiments.

Last week Taylor published Most decade-specific words in Billboard popular songs titles, 1890-2014, a snippet of which is shown above. Be sure to click the picture or link for the whole thing – and if you want even more detail, Taylor dives into the data, code, methodology, and other observations here.



The Names Have Been Changed: With holiday letters arriving in our mailboxes (postal and electronic), we’re bombarded with the sterling accomplishments of our friends’ children. But if you only hear from these proud parents once a year, you might not recall if young Emerson or Casey or Jessie is a boy or girl.

Their names don’t help, as you can see in the chart above from Randal Olson. Working with a U.S. government data set, Olson charted the 25 most gender-neutral names given to at least 5,000 U.S. babies since 1986. Olson, a doctoral candidate in computer science at Michigan State University whose hobby is “data tinkerer,” has other insightful data visualizations on his blog.



Ruble Roils: On a more serious note, many factors are contributing to the economic crisis in Russia, making it difficult for the layman to understand the roots of the problem and its possible consequences. Data visualizations can help, and political scientist Ian Bremmer (@ianbremmer) has collected several pertinent examples in his article, Russia’s Collapse in 5 Stats.

Bremmer drew his visualizations from the Wall Street Journal (above), The Economist Intelligence Unit, and Business Insider. Bonus: On Wednesday, Holger Zschaepitz (@Schuldensuehner) charted the fact that the market capitalization of the entire Russian stock exchange is now lower than the market cap of one company: Google.

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