Efficiently inserting default missing rows in a data.table

Question

Suppose I\'ve got the following data.table :

dt <- data.table(id=c(1,1,1,1,1,1,2,2,2,2),
           wday=c(\"mon\",\"tue\",\"wed\",\"thu\",\"         


        

Answer 1

One other possilibity with match and ddply :

FUN <- function(x) {
y <- x$val[match(c("mon", "tue", "wed", "thu", "fri", "sat", "sun"), x$wday, nomatch=NA)]
y[is.na(y)] <- 0
y <- data.frame(wday=c("mon", "tue", "wed", "thu", "fri", "sat", "sun"), val=y)
y
}
ddply(dt, .(id), FUN)

Answer 2

One straightforward way I could think of right now is to use expand.grid to get all combinations and then use that to subset with allow.cartesian = TRUE:

setkey(dt, "id", "wday")
vals <- c("mon", "tue", "wed", "thu", "fri", "sat", "sun")
idx <- expand.grid(vals, unique(dt$id))[, 2:1]
dt[J(idx), allow.cartesian=TRUE]

#     id wday val
#  1:  1  mon   2
#  2:  1  tue   3
#  3:  1  wed   5
#  4:  1  thu   8
#  5:  1  fri   6
#  6:  1  sat   2
#  7:  1  sun  NA
#  8:  2  mon   3
#  9:  2  tue   4
# 10:  2  wed  NA
# 11:  2  thu   2
# 12:  2  fri   6
# 13:  2  sat  NA
# 14:  2  sun  NA

Alternatively, it is possible to directly build the idx data table with CJ :

dt[CJ(unique(dt$id),vals), allow.cartesian=TRUE]