Turn vector output into columns in data.table along with other columns?
data.table, r
Solution
You should just change the `list` to `c`. `c` with any value of type `list` will automatically result in a `list`):
featuresDT <- quote(c(x = mean(X),
y = mean(Y),
z = mean(Z),
as.list(quantile(X))))
DT[, eval(featuresDT), by = "group"]
group x y z 0% 25% 50% 75% 100%
1: 1 2.000000 12.00000 22.00000 1 1.5 2 2.5 3
2: 2 5.000000 15.00000 25.00000 4 4.5 5 5.5 6
3: 3 8.000000 18.00000 28.00000 7 7.5 8 8.5 9
4: 4 4.333333 14.33333 24.33333 1 1.5 2 6.0 10
5: 5 4.000000 14.00000 24.00000 3 3.5 4 4.5 5
6: 6 7.000000 17.00000 27.00000 6 6.5 7 7.5 8
7: 7 6.666667 16.66667 26.66667 1 5.0 9 9.5 10
8: 8 3.000000 13.00000 23.00000 2 2.5 3 3.5 4
9: 9 6.000000 16.00000 26.00000 5 5.5 6 6.5 7
10: 10 9.000000 19.00000 29.00000 8 8.5 9 9.5 10
Problem
My questions is related to this one: Turn vector output into columns in data.table? But my situation is a bit more complicated. I am not only returning the vector as the columns, but I am also calculating other columns at the same time. E.g.: ``` DT = data.table(X = 1:10, Y = 11:20, Z = 21:30, group = rep(1:10, each = 3)) featuresDT <- quote(list(x = mean(X), y = mean(Y), z = mean(Z), as.list(quantile(X)))) DT[, eval(featuresDT), by = "group"] ``` where `quantile` returns a length 5 vector. Instead of getting a data.table with 8 columns, I am getting one with 4 columns and the `quantile` results are displayed as extra rows and `x, y and z` are duplicated 5 times. I also tried `dist = as.list(quantile(X)` but that gives the same result but different column name.