rm(list = ls());
gc();

###importing
path_root <- "c:/users/nodal/desktop/"
gni.dt <- read.csv(paste0(path_root, "gni.csv"), skip = 4)
head(gni.dt)
colnames(gni.dt)

###Column value check
table(!is.na(gni.dt$X1960))
dim(gni.dt)[1]
dim(gni.dt)[1] - sum(is.na(gni.dt$X1965))
column.count <- array(NA, 60)
for(i in 5:64) {
  column.count[i] <- dim(gni.dt)[1] - sum(is.na(gni.dt[, i]))
}
column.count #start from year 1966

#indicator
ind <- which(!is.na(gni.dt$X1975))

#sum
na.count.fn <- function(x) {
  return(sum(is.na(x)))
}
gni.sum <- apply(gni.dt[ind, 16:64], 1, sum, na.rm =TRUE) #from 7
gni.na <- apply(gni.dt[ind, 16:64], 1, na.count.fn) #from 7
countries <- gni.dt[ind, 1]

#finalize
gni.df <- data.frame(country = countries, gni.sum = gni.sum, na.count = gni.na)
gni.df[order(-gni.df$gni.sum), ]