Reputation: 10362
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.
Upvotes: 4
Views: 596
Reputation: 118889
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
Upvotes: 3
Reputation: 132989
Try this:
featuresDT <- quote(cbind(list(x = mean(X),
y = mean(Y),
z = mean(Z)),
as.data.table(t(quantile(X)))))
Upvotes: 1