R: Replace column depending on match of two other columns - r

Question

Lets assume there are 2 columns of two huge dataframes (different lengths) like:
df1 df2
A 1 C X
A 1 D X
B 4 C X
A 1 F X
B 4 A X
B 4 B X
C 7 B X
Each time there is a match in the 1st columns, X should be replaced with data from column 2 of df1. If the 1st column of df2 contains Elements, which are still not in the first column of df1 (F, D), X should be replaced with 0.
Hence there is a huge dataframe, a loop in a loop would not be useful.
The solution should look like this:
df1 df2
A 1 C 7
A 1 D 0
B 4 C 7
A 1 F 0
B 4 A 1
B 4 B 4
C 7 B 4
Thank You in advance

Answer 1

As there are duplicate rows in 'df1', we can get the unique rows
df3 <- unique(df1)
Then, use match to get the idnex
i1 <- match(df2$Col1, df3$Col1)
and based on the index, assign
df2$Col2 <- df3$Col2[i1]
If there are no matches, it would be NA, which can be changed to 0
df2$Col2[is.na(df2$Col2)] <- 0
df2
# Col1 Col2
#1 C 7
#2 D 0
#3 C 7
#4 F 0
#5 A 1
#6 B 4
#7 B 4
Or this can be done with data.table by joining on the 'Col1' and assigning the 'Col2' (after removing the Col2 from the second data) with the Col2 from 'df3'
library(data.table)
setDT(df2)[, Col2 := NULL][df3, Col2 := Col2, on = .(Col1)]
data
df1 <- structure(list(Col1 = c("A", "A", "B", "A", "B", "B", "C"), Col2 = c(1,
1, 4, 1, 4, 4, 7)), class = "data.frame", row.names = c(NA, -7L
))
df2 <- structure(list(Col1 = c("C", "D", "C", "F", "A", "B", "B"), Col2 = c("X",
"X", "X", "X", "X", "X", "X")), class = "data.frame", row.names = c(NA,
-7L))