将data.table的子集分配给另一个data.table的子集

Question

I have two data.tables:

library(data.table)
dt1 <- data.table(A=1:10, B=1, C=2, D=3)
dt2 <- data.table(A2=5:9, B2=4, C2=5, D2=6)

I want to assign elements of column B2 and C2 in dt2 to column B and C in dt1 where A = A2, such that I get a table that looks like this:

dt1
#      A B C D
#  1:  1 1 2 3
#  2:  2 1 2 3
#  3:  3 1 2 3
#  4:  4 1 2 3
#  5:  5 4 5 3
#  6:  6 4 5 3
#  7:  7 4 5 3
#  8:  8 4 5 3
#  9:  9 4 5 3
# 10: 10 1 2 3

I know I can assign one column at a time:

id1 <- which(dt1$A %in% dt2$A2)
id2 <- which(dt2$A2 %in% dt1$A)
dt1$B[id1] <- dt2$B2[id2]
dt1$C[id1] <- dt2$C2[id2]

however this seems like a lot of lines of code to do only very little, especially if I had many columns.

I was thinking something like

# Not working:
dt1[id1][,list(B,C)] <- dt2[id2][,list(B2,C2)]

would work, but I get an error message.

Is there a smarter, nicer way to do it?

Answer 1

We can do a join on the 'A' with 'A2' and assign ( := ) the values of columns of interest to 'C' and 'D'

library(data.table)#v1.9.7+
dt1[dt2,  c('C', 'D') := .(C2, D2),  on = .(A= A2)]
dt1
#     A B C D
# 1:  1 1 2 3
# 2:  2 1 2 3
# 3:  3 1 2 3
# 4:  4 1 2 3
# 5:  5 1 5 6
# 6:  6 1 5 6
# 7:  7 1 5 6
# 8:  8 1 5 6
# 9:  9 1 5 6
#10: 10 1 2 3

---

If there are many columns that we need to change, instead of typing out the columns, we get the values using mget and assign it to the corresponding column names in 'dt1'

dt1[dt2, names(dt1)[3:4] :=  mget(names(dt2)[3:4]), on = .(A = A2)]