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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
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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