Nothing
##' This function checks whether there are overlapping between the
##' transitional countries.
##'
##'
##' @param old The FAOST_CODE of the old countries
##' @param new The FAOST_CODE of the new countries
##' @param var The variable to be checked
##' @param year The column which index the time.
##' @param data The data frame
##' @param take The type of check/replacement to be done.
##'
##' @export
##'
overlap = function(old, new, var, year = "Year", data, take){
n.var = length(var)
for(i in 1:n.var){
old_years = unique(data[data$FAOST_CODE %in% old &
!is.na(data[, var[i]]), year])
new_years = unique(data[data$FAOST_CODE %in% new &
!is.na(data[, var[i]]), year])
int_years = intersect(old_years, new_years)
if(length(int_years) > 0)
cat(paste0(var[i], " has overlap in:\n\t Year = ",
paste0(int_years, collapse = ", "),
"\n\tfor FAOST_CODE = ",
paste0(c(old, new), collapse = ", "), "\n"))
switch(take,
simpleCheck = {},
takeNew = {
data[data$FAOST_CODE %in% old &
data[, year] %in% int_years, var[i]] = NA
},
takeOld = {
data[data$FAOST_CODE %in% new &
data[, year] %in% int_years, var[i]] = NA
},
complete = {
for(j in sort(unique(int_years))){
if(NROW(data[data[, "FAOST_CODE"] %in% new &
!is.na(data[, var[i]]) & data[, year] == j, "FAOST_CODE"]) == length(new)) {
## All the new entities are there. Remove the old.
data[data[, "FAOST_CODE"] %in% old & data[, year] == j, var[i]] = NA
} else {
## Not all the new entities are there. Remove the new.
data[data[, "FAOST_CODE"] %in% new & data[, year] == j, var[i]] = NA
}
}
}
)
}
data
}
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