Map week continues. The first one was perhaps a bit boring. Mostly because the data was not normalized by area of each country. But you can still say something about the state of the economies.
Some data is better shown when split to categories. So, I made an algorithm that finds deciles from the data and colors the countries according to how they compare against these.
Map 1. Number of refugees from country. Data from Wikipedia (Feb 2013)
From Map 1 it can easily be seen that refugees come from all over the globe, but again it should be noted that no correction for population is made. So for example from the numbers available in the map, when corrected for population Finland and the US could have the same number of refugees per capita. Refugees from the US number over 500 times more than from Finland, which is a much larger factor that the ratio of populations would suggest.
This type of map also conceals the fact that there are a couple of countries in the last group that have sent out a lot of refugees.
Map 2. Origin of refugees, linear scale. Data from Wikipedia (Feb 2013)
Map 1 and Map 2 are based on the same data, but Afghanistan, Iraq and a couple of others really stand out from Map 2.
Where did the refugees go?
Map 3. Natives per refugee population in that country. Data from Wikipedia (Feb 2013)
Map 3 also tells something about where refugees want/can go and what sort of burden they are for the host country. It doesn’t tell anything about how rich the receiving country is so the burden will still varies.
Color selection in the maps is all mine and I apologise. I have pretty much no artistic talent or taste for that matter. Perhaps I need to make an algorithm that calculates which colors would give maximum contrast between the groups. Then I could say that the selection is based on something other than me manually inserting hex values that seem to be far from each other.