Catching up

Between being out of the country and starting a new job, I’ve been fairly delinquent about updating this blog. Here’s an attempt at catching up.


  • First, Cedric Sam mashes up 2008 political donation data to create a map of political contributors by party based on full (six-character) postal codes.

    Cedric explains:

    There were also some cleverly hidden public data that consists in the postal code of a single contributor. Using a Web browser, it was impossible to compile this data into a database. But using simple scripts with a command-line tool like curl, it was possible to know the location that a donor used to make its donation, including private residence. It might be of questionable good taste to reveal those on a map, but in an era of data mashups and visualisation, it makes perfect sense for what is after all public data.

    A man after my own heart. Another way of presenting this data would be to sum totals for each party at all levels by FSA, then map a rate (dollars per 1,000 of population, something like that.)


  • From the University of Toronto map library: a visualization of Toronto’s afternoon rush hour, 1915.

  • From the Guardian: maps of teen pregnancy rates and child poverty in Britain.

  • twitterdots.posterous.com maps 24 hours of a term on Twitter across the globe:

    24 Hours of Good Morning on Twitter from Rio Akasaka on Vimeo.


  • The Map Room points to a map of profanity on Twitter, in which the coastal South glows bright red:

    Daniel P. Huffman has created a map of profanity on Twitter (original PDF here). It takes a sample of 1.5 million geocoded tweets in March and April 2010 and maps the percentage of words in said tweets that are profanities. Salt Lake City never swears, apparently.


  • In the Times, a followup of sorts to our baby name maps:

    A new study finds that parents in newer, “frontier” states choose less-common baby names than parents in older states (like the original 13).


  • And the Norwegian paper Bergens Tidende maps a decade’s worth of road accident data for that country.
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