eur<-read_csv('GEOSTAT_grid_POP_1K_2011_V2_0_1.csv')

#two ways to extract east and north
eur$North <-str_match(eur$GRD_ID, "1kmN(\\d\\d\\d\\d)E(\\d\\d\\d\\d)")[,2]
eur$East <-str_match(eur$GRD_ID, "1kmN(\\d\\d\\d\\d)E(\\d\\d\\d\\d)")[,3]
eur<-eur%>%
mutate(
    lat = as.numeric(gsub('.*N([0-9]+)[EW].*', '\\1', GRD_ID))/100,
    lng = as.numeric(gsub('.*[EW]([0-9]+)', '\\1', GRD_ID)) * ifelse(gsub('.*([EW]).*', '\\1', GRD_ID) == 'W', -1, 1) / 100
  )
head(eur)

#get each countries population total
popu<-aggregate(eur$TOT_P, by=list(Category=eur$CNTR_CODE), FUN=sum)

for (row in 1:nrow(popu)) {
    country <- popu[row, "Category"]
    TOT_P  <- popu[row, "x"]
}

#now loop through each contry and find the North and east km with half the people either side
for (row in 1:nrow(popu)) {
    country <- popu[row, "Category"]
    TOT_P  <- popu[row, "x"]

    Coun<-filter(eur, DATA_SRC == country)

#stop when you have half the population
thresholdValue <- (TOT_P/2)
#head east until you have counted half the people
Coun<-Coun[order(Coun$East),]
ix <- length(which(cumsum(Coun$TOT_P) <= thresholdValue))
first<-Coun[ix,]$East

#head south until you have counted half the people
Coun<-Coun[order(Coun$North),]
iy <- length(which(cumsum(Coun$TOT_P) <= thresholdValue))


cat(country, first ,strtoi(Coun[iy,]$North))

cat("\n")
}