Ways to improve for loop in R - r

Question

I have a large file and need to match admin ids with users something like this:
TABLE1 TABLE 2
INDEX V1 IDS AdmID
1 A 30 30
2 U 3 123
3 U 25 60
4 U 4 .
5 U 5 .
6 A 123 .
7 U 7
8 U 8
9 U 9
10 A 60
11 U 26
12 U 2
. . .
. . .
. . .
I want something like this:
COMPLETE TABLE
INDEX V1 IDS ADMIN_ID
1 A 30 30
2 U 3 30
3 U 25 30
4 U 4 30
5 U 5 30
6 A 123 123
7 U 7 123
8 U 8 123
9 U 9 123
10 A 60 60
11 U 26 60
12 U 2 60
. . . .
. . . .
. . . .
So I wrote this loop, but is taking forever to finish. Any idea of how to use apply() on this situation:
ln=10,000;#number of records in the Adm table
TABLE2= index of the adm ids
for (k in 1:ln){
w<-TABLE2$A_ID[k] #Ids of the adms
for(i in seq(from=AdmID[k], to=AdmID[k+1], by=1)){
TABLE1$ADMIN_ID[i]<-w
}
}

Answer 1

It'll be easier if how the mapping is applied by records - admin$ind. Cumulative sums are obtained and the mapping table is reversed - admin. Then ids can be replaced sequentially - in your case, 12, 9, 5.
df <- data.frame(index = c(1:12),
v1 = c("A","U","U","U","U","A","U","U","U","A","U","U"),
ids = 13:24,
admin = 0)
# need rule to assign ids - ind
admin <- data.frame(ind = c(5,4,3), id = c(30,123,60))
# get cumulative sum and reverse admin table
admin$cum <- cumsum(admin$ind)
admin <- admin[nrow(admin):1,]
admin
ind id cum
3 3 60 12
2 4 123 9
1 5 30 5
# ids will be subsequently updated - 12, 9, 5
for(i in 1:length(admin$cum)) {
df[as.numeric(row.names(df)) <= admin$cum[i], 4] <- admin$id[i]
}
df
index v1 ids admin
1 1 A 13 30
2 2 U 14 30
3 3 U 15 30
4 4 U 16 30
5 5 U 17 30
6 6 A 18 123
7 7 U 19 123
8 8 U 20 123
9 9 U 21 123
10 10 A 22 60
11 11 U 23 60
12 12 U 24 60
Below is another version that uses the individual matching rule, but the cumulative one.
df <- data.frame(index = c(1:12),
v1 = c("A","U","U","U","U","A","U","U","U","A","U","U"),
ids = 13:24)
# need rule to assign ids - ind
admin <- data.frame(ind = c(5,4,3), id = c(30,123,60))
df$admin <- do.call(c, lapply(1:length(admin$ind), function(x) {
rep(admin$id[x], sum(as.numeric(row.names(df)) <= admin$ind[x]))
}))