Remove rows from data.table in R based on values of several columns

Question

I have a data.table in R which has several ids and a value. For each combination of ids, there are several rows. If one of these rows contains NA in the column 'value', I would like to remove all rows with this combination of ids. For example, in the table below, I would like to remove all rows for which id1 == 2 and id2 == 1 .

If I had only one id I would do dat[!(id1 %in% dat[is.na(value),id1])] . In the example, this would remove all rows where i1 == 2. However, I did not manage to include several columns.

dat <- data.table(id1 = c(1,1,2,2,2,2),
                  id2 = c(1,2,1,2,3,1),
                  value = c(5,3,NA,6,7,3))

Answer 1

If you want to check per combination of id1 and id2 if any of the values are NA s and then remove that whole combination, you can insert an if statement per group and only retrieve the results (using .SD ) if that statement returns TRUE .

dat[, if(!anyNA(value)) .SD, by = .(id1, id2)]
#    id1 id2 value
# 1:   1   1     5
# 2:   1   2     3
# 3:   2   2     6
# 4:   2   3     7

Or similarly,

dat[, if(all(!is.na(value))) .SD, by = .(id1, id2)]