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Gary

I like that area chart a lot, it perfectly illustrates a point: the number of people in slums is constant, while those above slum status are increasing.

I like the map too - I had no idea Botswana had higher-than-average per-capita GDP. I think the starkness of above-below is a bit misleading, though - some of these countries are very close to the global mean like Brazil or South Africa, some are very very far away like Haiti or Ethiopia or Qatar. http://bit.ly/svFmXr for a quickly whipped-up example (based on IMF data), which doesn't quite do it but you see the difference between South America and Africa.

Gary

Ah, this is better: http://bit.ly/s2c8pa - the rich outliers were killing differentiation further down.

Stef

Concerning the map, and the two classes (below and above average): We had a map with a "normal" classification before (four or five classes), but then decided we'd need something "easier" for the general public and quick readers. The thing with the below/above is that one will always have a good bunch of countries below the average, even if many of them experienced high increases over recent years. So, this map is only telling half of the truth, if one will...

Nen@recycledaggregates

A picture speaks a thousand words!

Jörgen Abrahamsson

About the life expectancy chart. The angles are too steep should average around 45. Just widen the chart by one third or so. Also the global value should be faded and not highlited being the least specific(and containing the other values)
About the age distribution chart. Stacked bar charts are almost always bad. And when comparing distribution you need to use relative figures % of population not absolute millions of people.
That is just plain wrong.

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Marketing analytics and data visualization expert. Author and Speaker. Currently at Vimeo and NYU. See my full bio.

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