Replacing NAs witha new factor level in one column based on factor level in another column using data.table

Question

DATA = data.table(col_1 = factor(c("A", "B", "C", "C", "B", "A", "C")),
                  col_2 = factor(c("stuff", NA, NA, "stuff", NA, "different_stuff", NA)))

I have a big data set in which I would like to replace the NAs from col2 , that correspond to C from col1 , with a new factor level, eg yet_another_stuff . There are more NAs than there are observations with C level and I don't want to replace the NAs that belong to other level like B .

After uploading this data set the columns are already of class factor.

I would highly prefer to do so using data.table package due to the size of the data set.

Answer 1

我们可以在i指定逻辑条件，并在'col_2'中分配与'yet_another_stuff'条件对应的那些值

DATA[is.na(col_2) & col_1 == "C", col_2 := "yet_another_stuff"]