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Asylum data used in my blog post on refugee numbers in Europe: http://carsten.io/which-countries-should-be-able-to-handle-the-strain-in-the-european-migration-crisis/
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name | Est. GDP in USD 2015 | Applicants since 2011 | Est. Pop 2015 | Applicants by pop | Applicants by GDP | |
---|---|---|---|---|---|---|
Austria | 380.555 | 104489 | 8.556 | 12.21236559 | 274.5700359 | |
Belgium | 463.799 | 79209 | 11.239 | 7.047691076 | 170.7830332 | |
Bulgaria | 51.551 | 27124 | 7.166 | 3.785096288 | 526.1585614 | |
Denmark | 297.359 | 35302 | 5.629 | 6.271451412 | 118.7184514 | |
Finland | 235.276 | 14361 | 5.506 | 2.60824555 | 61.03895 | |
France | 2469.530 | 255800 | 64.213 | 3.983617025 | 103.5824631 | |
Germany | 3413.483 | 547034 | 81.360 | 6.723623402 | 160.2568403 | |
Greece | 207.148 | 42800 | 10.993 | 3.893386701 | 206.6155599 | |
Hungary | 126.691 | 129203 | 9.857 | 13.10774069 | 1019.82777 | |
Italy | 1842.835 | 155536 | 60.236 | 2.582110366 | 84.40039396 | |
Montenegro | 4.239 | 9158 | 0.625 | 14.6528 | 2160.415192 | |
Netherlands | 749.365 | 63889 | 16.935 | 3.772601122 | 85.25751803 | |
Norway | 420.958 | 47240 | 5.213 | 9.061960483 | 112.2202215 | |
Portugal | 201.036 | 38418 | 10.403 | 3.692973181 | 191.1001015 | |
Serbia | 47.131 | 65237 | 9.012 | 7.238903684 | 1384.16329 | |
Kosovo | 47.131 | 65237 | 9.012 | 7.238903684 | 1384.16329 | |
Spain | 1230.207 | 21112 | 46.393 | 0.455068653 | 17.16133951 | |
Sweden | 487.396 | 228601 | 9.830 | 23.25544252 | 469.0251869 | |
Switzerland | 688.434 | 98102 | 8.189 | 11.9797289 | 142.5002251 | |
Turkey | 752.510 | 209019 | 76.903 | 2.717956387 | 277.7624218 | |
United Kingdom | 2853.357 | 125139 | 64.938 | 1.927053497 | 43.8567624 |
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asylum <- read.csv('asylum-data.csv') | |
asylum <- asylum[order(asylum$Applicants.since.2011),] | |
options(scipen=999) | |
par(mai=c(2,3,1,1)) | |
barplot(asylum$Applicants.since.2011, main="Total number of asylum applications since 2011", xlab="Number of applications", names.arg=asylum$name, horiz=TRUE, las=1, col="black") | |
barplot(asylum$Applicants.by.pop, main="Number of asylum applications per 1000 inhabitants since 2011", xlab="Number of applications per 1000 inhabitants", names.arg=asylum$name, horiz=TRUE, las=1, col="black") | |
barplot(asylum$Applicants.by.GDP, main="Number of asylum applications since 2011, normalized by est. 2015 GDP in Billion USD ", xlab="Number of applications, normalized by est. 2015 GDP in Billion USD", names.arg=asylum$name, horiz=TRUE, las=1, col="black") |
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