I looking for a way to efficiently apply a function to each row of data.table. Let's consider the following data table:
library(data.table)
library(stringr)
x <- data.table(a = c(1:3, 1), b = c('12 13', '14 15', '16 17', '18 19'))
> x
a b
1: 1 12 13
2: 2 14 15
3: 3 16 17
4: 1 18 19
Let's say I want to split each element of column b
by space (thus yielding two rows for each row in the original data) and join the resulting data tables. For the example above, I need the following result:
a V1
1: 1 12
2: 1 13
3: 2 14
4: 2 15
5: 3 16
6: 3 17
7: 1 18
8: 1 19
The following would work if column a
has only unique values:
x[, list(str_split(b, ' ')[[1]]), by = a]
The following almost works (unless there are some identical rows in the original data table), but is ugly when x
has many columns and copies column b to the result, which I would like to avoid.
> x[, list(str_split(b, ' ')[[1]]), by = list(a,b)]
a b V1
1: 1 12 13 12
2: 1 12 13 13
3: 2 14 15 14
4: 2 14 15 15
5: 3 16 17 16
6: 3 16 17 17
7: 1 18 19 18
8: 1 18 19 19
What would be the most efficient and idiomatic way to solve this problem?
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