Assuming all list columns are of the same lengths, then this might be a
little faster?
dtUngroup <- function(dt) {
l <- names(dt)[dt[, lapply(.SD, class)]=="list"]
if (length(l)>0) {
nl <- setdiff(names(dt), l)
t <- sapply(dt[[l[1]]], length)
tmp <- dt[, .SD, .SDcols=nl]
tmp <- tmp[, lapply(.SD, rep, times=t)]
tmp <- cbind(tmp, dt[, lapply(.SD, unlist), .SDcols=l])
} else tmp <- dt
return(tmp)
}
# If you need to cast columns back to POSIXct, might be easier as follows:
res <- dtUngroup(DT)
res[, c := as.POSIXct(c, origin="1970-01-01")]
On 1/8/2016 9:23 AM, statquant3 wrote:
dtUngroup <- function(DT){
colClasses <- lapply(DT,FUN=class)
listCols <- which(colClasses=='list')
if(length(listCols)>0){
nonListCols <- setdiff(colnames(DT),listCols)
nbListElem <-
unlist(DT[,lapply(.SD,FUN=lengths),.SDcols=(listCols[1L])])
DT1 <-
DT[,lapply(.SD,FUN=rep,times=(nbListElem)),.SDcols=(nonListCols)]
DT1[,(listCols):=DT[,lapply(.SD,FUN=function(x)
do.call('c',x)),.SDcols=(listCols)]]
return(DT1)
}
return(DT)
}
This works... still 20x slower than the equivalent in kdb
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