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Daniel Ferry

I'll leave the merits of the FreshBooks chart to you and Steve Few, but I thought it was interesting enough to recreate it in Excel. I added animation to the chart and think it came out quite well:


Daniel Ferry


First thing, map illiterate refers to someone who can't read a map, I think you meant geographic illiteracy.

While I don't think the map was particularly well-executed, e.g. the magnifying glass effect and the overlapping bubbles. I disagree that all the map does is belittle the reader, and I think maps are more useful as a visualization tool than you let on. Displaying this data on a map immediately tells me that FreshBooks distributes primarily in Europe, and Mexico while hardly in S. America and Africa. This isn't as easily interpreted from the column chart at the bottom.

Anyway, I enjoy your blog and draw a lot of useful information from here even if we don't see eye to eye regarding maps.

dan l

This is yet another example of a map adding little or no value to the data. The presence of geographic data is not an excuse to give a lesson on maps.

Displaying this data on a map immediately tells me that FreshBooks distributes primarily in Europe, and Mexico while hardly in S. America and Africa.

I agree! With both of you!

That being said, the example isn't great:

Why use the heatmap type technique (different shades of grey) when you already have the bubbles? If you're starting at the upper left hand corner when you look at it, you'll notice that the entire continent is dark. Whut am I looking at here? Sales by continent? OOOOOO ok bubbles, yeah they just so happen to have similar activity....no wait...canada and the us have 1000 sales a pop and Mexico has 4k. Wait, whut?

I think what our host is talking about in terms of calling the audience stupid, is the use of the lines to trail to/fro the bars on the bottom to the map on top. In using a map, you're capitalizing on the fact that your audience already knows the map. If you don't believe your audience knows the map, why is it being use to begin with?


I'm a great believer in sorting and grouping. Grouping the bars into categories labelled Europe, North America, South America, and so on would easily achieve the same benefits as the map, without the need for a map.

The grouped bar chart would instantly prompt exclamations such as "Look! Freshbooks distributes to Europe a lot, and to South and Central America hardly at all, except for Mexico!"


"Grouping the bars into categories labeled Europe, North America, South America"

Very true, and I think that would probably be the best approach in this case. Although, the advantage of the map is that the bar charts don't have data in South America (the Caribbean and Central America do). So in this case the map reveals as much about where there is no data as where there is.


Just on the map, David pointed out you can immediately tell *where* all the bacon is, and *where else* is really really poor. That's one index into the data: by size of the measure.

The other, of course, is geographic location! You haven't suggested an alternative, but if I gave you a spreadsheet of all locations and their values (or even just the bars at the bottom) and said "tell me South Africa's value", would you start scanning down the list of locations and hope they're sorted in alphabetical order so it's really easy to find SA? But then the measures are all over the place and you can't tell where the maximum is.

So if the data are sorted by the measure values (as with the bars), now your locations are out of alphabetical order and it's not simple to find a given location.

I disagree with the grouping comment that grouping would achieve the same benefit as the map.

One thing I don't like is that the title says "where the first billion dollars came from" but then the data measure "average invoice size".

I see the largest dots and think - that's where the most money came from, but I suspect China with its average invoice size of 1,009 and population of 1,324,655,000 probably drew more of the bikkies than Australia with its comparable average invoice size of 1,002 and just 1.6% of China's population at just 21,431,800.

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Kaiser Fung. Business analytics and data visualization expert. Author and Speaker.
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