best way to transpose data.table

[UPDATE: there is now a native `transpose()` function in `data.table` package] I often need to transpose a `data.table`, every time it takes several lines of code and I am wondering if there's any better solution than mine. if we take sample table ``` library(data.table) mydata <- data.table(col0=c("row1","row2","row3"), col1=c(11,21,31), col2=c(12,22,32), col3=c(13,23,33)) mydata # col0 col1 col2 col3 # row1 11 12 13 # row2 21 22 23 # row3 31 32 33 ``` and just transpose it with `t()`, it will be transposed to the matrix with conversion to `character` type, while applying `data.table` to such matrix will lose `row.names`: ``` t(mydata) # [,1] [,2] [,3] # col0 "row1" "row2" "row3" # col1 "11" "21" "31" # col2 "12" "22" "32" # col3 "13" "23" "33" data.table(t(mydata)) # V1 V2 V3 # row1 row2 row3 # 11 21 31 # 12 22 32 # 13 23 33 ``` so I had to write a function for this: ``` tdt <- function(inpdt){ transposed <- t(inpdt[,-1,with=F]); colnames(transposed) <- inpdt[[1]]; transposed <- data.table(transposed, keep.rownames=T); setnames(transposed, 1, names(inpdt)[1]); return(transposed); } tdt(mydata) # col0 row1 row2 row3 # col1 11 21 31 # col2 12 22 32 # col3 13 23 33 ``` is there anything I could optimize here or do it in "nicer" way?