Visualizing global human development statistics

Thanks to Costa at Sustainable Research for pointing out this amazing data visualization tool. The folks at Gapminder have put together an interactive graph that lets you plot a variety of statistics by country, like “physicians per 1000 people”, and “percent urban population”. After looking at a lot of different relationships (hmm, what happens with % women in the labor force vs. % of government spending on the military?), I’m surprised how few variable pairs have a clear relationship. Most of them look random, or maybe have different trends for different regions. But what begins to become interesting is identifying the outliers, like, who has higher per capita CO2 emissions than the US? Who would’ve guessed Trinidad and Guam? Looking at trends over time is also fascinating. Time runs as a variable-speed animation, so you can step through the decades and watch China’s life expectancy dip during the cultural revolution, and watch Rwanda’s make a startling plummet during the genocide.

Beyond the specific statistics available, this is an amazing tool for visualizing data. Between the x-axis, y-axis, dot color, dot size, and time animation, you can individually select and see 5 dimensions of data at the same time, all with a friendly and effective user interface. Of course, it raises the question of whether people can actually process that much information. I found myself turning one or more dimensions off so as not to confuse myself. Maybe with experience you could train yourself to detect patterns or outliers in a 5-D visualization, but I wonder if you’d be able to see, for instance, a 3-way interaction that wasn’t obvious in any 2-D representation.

  1. #1 written by Sarah November 7th, 2007 at 22:46

    Hey Josh, glad I tried your site today. Hans Rosling did a fantastic demo of the early software at last year’s TED Talks:

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  2. #2 written by Genug November 7th, 2007 at 23:07

    Take-home message: it sucks to be Africa. Seems like most of the world made strides in life expectancy over the last 30 years with the exception of Africa. AIDS, malaria, TB, war… the gifts of colonialism that keep on giving?

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  3. #3 written by Sarah November 7th, 2007 at 23:19

    I’m not sure that’s the total take-home message. Yes, it still sucks to be some regions of Africa, but part of Rosling’s point was that some of the conventional developed-versus-undeveloped-world ideas are out of date. The strength of the tool, as Josh mentioned, is that one can see patterns and interactions in a number of dimensions, rather than the simplistic 2D representations that have driven a lot of discourse for the last few decades.

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  4. #4 written by Moira November 8th, 2007 at 16:33

    I’m not surprised that Guam has such high CO2 emissions. It has a very small population and a huge tourist industry, with dozens of posh hotels. Tourists from all over Asia come to Guam to golf, and the air conditioners and lights are always maxed at those resorts.

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  5. #5 written by Joan Denoo November 11th, 2007 at 14:29

    How did you get the Guam stats? I am using “The Gapminder World 2006 beta” version, is there a more recent or different version?

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  6. #6 written by Joan Denoo November 11th, 2007 at 14:36

    Using Life Expectancy on the verticle axis and Income per capita on the horizontal, and selecting Botswana, Lesotho and Zimbabwe compared to Japan, U.S. and Luxembourg, one can see the effects of disease, poverty, and colonialism on African nations.

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  7. #7 written by Joan Denoo November 11th, 2007 at 14:39

    I would like to see a chart of the U.S. by income groups. Does anyone know how to do that?

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  8. #8 written by joshuah November 13th, 2007 at 10:58


    The number of countries/protectorates changes depending on the data set. I saw Guam and the U.S. Virgin islands when looking at CO2 over time, but not many other data sets seem to have them in there.

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