Conditional Replacing with NA in R (two dataframes) - r

Question

I have
idx <- c(1397, 2000, 3409, 3415, 4077, 4445, 5021, 5155)
idy <- c( 1397, 2000, 2860, 3029, 3415, 3707, 4077, 4445, 5021, 5155,
5251, 5560)
agex <- c(NA, NA, NA, 35, NA, 62, 35, 46)
agey <- c( 3, 45, 0, 89, 7, 2, 13, 24, 58, 8, 3, 45)
dat1 <- as.data.frame(cbind(idx, agex))
dat2 <- as.data.frame(cbind(idy, agey))
Now I want whenever agex = NA, and idx = idy, that agey = NA, so that
idy agey
1 1397 NA
2 2000 NA
3 2860 0
4 3029 89
5 3415 7
6 3707 2
7 4077 NA
8 4445 24
9 5021 58
10 5155 8
11 5251 3
12 5560 45
I have tried this
ifelse(is.na(dat1$agex) | dat1$idx %in% dat2$idy, NA, dat2$agey)
it returns NAs at the correct indices, but shortens idy to the length of idx.

Answer 1

I want whenever agex = NA, and idx = idy, that agey = NA
With a data.table update join...
library(data.table)
setDT(dat1); setDT(dat2)
dat2[dat1[is.na(agex)], on=.(idy = idx), agey := NA]
dat2
idy agey
1: 1397 NA
2: 2000 NA
3: 2860 0
4: 3029 89
5: 3415 7
6: 3707 2
7: 4077 NA
8: 4445 24
9: 5021 58
10: 5155 8
11: 5251 3
12: 5560 45
How it works
dat1[is.na(agex)] is the subset where agex is NA
DT[mDT, on=, j] is a join where rows of mDT are looked up in DT using on=
j is done in the joined subset of DT
when j is k := expr, column k of DT is updated