a <- data.frame(id = 1:3, v1 = c(\'a\', NA, NA), v2 = c(NA, \'b\', \'c\'))
b <- data.frame(id = 1:3, v1 = c(NA, \'B
The type of merge you specify probably won't be possible using merge (with data frames), although saying that usually invites being proved wrong.
You also omit some details: will there always be a single unique non-NA value in each column for each id value? If so, this will work:
ab <- rbind(a,b)
> colFun <- function(x){x[which(!is.na(x))]}
> ddply(ab,.(id),function(x){colwise(colFun)(x)})
id v1 v2
1 1 a A
2 2 B b
3 3 C c
A similar strategy should work with data.tables as well:
abDT <- data.table(ab,key = "id")
> abDT[,list(colFun(v1),colFun(v2)),by = id]
id V1 V2
[1,] 1 a A
[2,] 2 B b
[3,] 3 C c