Seemingly Logarithmic Transformation for Graphical Demonstration of Income Distribution? http://www.businessinsider.com/pictures-of-toys-around-the-world-2016-8#in-a-latvian-home-living-on-11381month-per-adult-the-favorite-toy-is-a-stuffed-animal-43
I saw the above shared on Facebook recently. If you scroll down through the images you come to what initially appears to be a Normal Probability Graph. But the X-Axis seems to show the same distance between (\$30,\$300) and (\$300,\$3000).
Though not explained, I assume they took a logarithmic transformation of the X-variable. My question is, what is the advantage of doing this? I always assumed that the only reason for a logarithmic transformation is so that a data analyst/scientist could properly apply analysis techniques to derive a solution.
Thank you in advance.
 A: This is taken from the Dollar Street (https://www.gapminder.org/dollar-street/matrix), a visualization project pin pointing that there aren't really "poor" countries per se; but we are all just on different parts of a spectrum of economic capability. The project highlights that infrastructures such as coal burning stove is not really a "country" or "culture" thing but rather income-driven. Poor people in any country can burn coal, if they are not able to afford cleaner or more efficient fuel.
To show that idea, they ranked 100 international households by income on an imaginary street, and provided many snapshots about infrastructure and commodities for each household. If they don't log-transform the income, the street visualization will have to be very long, with tons of houses packed on the left, and the houses get sparser and sparser as we move towards higher income; such design will be difficult to navigate. The log-transformed street allows for a more even distribution of the house icons.
Anna Rosling did a TED Talk on this project if you're interested to know more.
