R Data.Table with weights

Question

library(data.table)
data = data.table("STUDENT" = c(1:100),
                  "SAMPLEWEIGHT" = sample(12:99, r = T, 100),
"LABEL1" = sample(1:2, r = T, 100),
"LABEL3" = sample(1:3, r = T, 100),
"CAT"=sample(0:1,r = T, 100),
"FOX"=sample(0:1,r = T, 100),
"DOG"=sample(0:1,r = T, 100),
"MOUSE"=sample(0:1,r = T, 100),
"BIRD"=sample(0:1,r = T, 100))

dataWANT = data.frame("LABEL1" = c(1,1,1,2,2,2),
                                            "LABEL3" = c(1,2,3,1,2,3),
                                            "CAT_N" = NA,
                                            "CAT_PER" = NA,
                                            "FOX_N" = NA,
                                            "FOX_PER" = NA,
                                            "DOG_N" = NA,
                                            "DOG_PER" = NA,
                                            "MOUSE_N" = NA,
                                            "MOUSE_PER" = NA,
                                            "BIRD_N" = NA,
                                            "BIRD_PER" = NA)

I have a data.table call it data, and am attempting to try and summarize the student data like what is shown in dataWANT.

in dataWANT the columns that have _N at the end is just the count of values in the column that equals to 1 for each LABEL1 and LABEL3 combination so a total of 6 groups.

in dataWANT the columns that have _PER at the end is the weighted proportion of the groups that have ones in their column.

Answer 1

An option using data.table would be to group by 'LABEL1', 'LABEL3', specify the columns of interest in .SDcols , get the sum (as it binary columns) by looping over the .SD and concatenate with the weighted.mean based on the 'SAMPLEWEIGHT' column

library(data.table)
data[, c(setNames(lapply(.SD, sum), paste0(names(.SD), "_N")), 
  setNames(lapply(.SD, function(x) weighted.mean(x == 1, SAMPLEWEIGHT)), 
     paste0(names(.SD), "_PER"))),.(LABEL1, LABEL3), .SDcols = CAT:BIRD]