J {data.table} | R Documentation |
Creates a data.table
to be passed in as the i
to a [.data.table
join.
# DT[J(...)] # J() only for use inside DT[...]. SJ(...) # DT[SJ(...)] CJ(..., sorted = TRUE, unique = FALSE) # DT[CJ(...)]
... |
Each argument is a vector. Generally each vector is the same length but if they are not then the usual silent repetition is applied. |
sorted |
logical. Should the input order be retained? |
unique |
logical. When |
SJ
and CJ
are convenience functions for creating a data.table in the context of a data.table 'query' on x
.
x[data.table(id)]
is the same as x[J(id)]
but the latter is more readable. Identical alternatives are x[list(id)]
and x[.(id)]
.
x
must have a key when passing in a join table as the i
. See [.data.table
J
: the same result as calling list. J is a direct alias for list but results in clearer more readable code.
SJ
: (S)orted (J)oin. The same value as J() but additionally setkey() is called on all the columns in the order they were passed in to SJ. For efficiency, to invoke a binary merge rather than a repeated binary full search for each row of i
.
CJ
: (C)ross (J)oin. A data.table is formed from the cross product of the vectors. For example, 10 ids, and 100 dates, CJ returns a 1000 row table containing all the dates for all the ids. It gains sorted
, which by default is TRUE for backwards compatibility. FALSE retains input order.
DT = data.table(A=5:1,B=letters[5:1]) setkey(DT,B) # re-orders table and marks it sorted. DT[J("b")] # returns the 2nd row DT[.("b")] # same. Style of package plyr. DT[list("b")] # same # CJ usage examples CJ(c(5,NA,1), c(1,3,2)) # sorted and keyed data.table do.call(CJ, list(c(5,NA,1), c(1,3,2))) # same as above CJ(c(5,NA,1), c(1,3,2), sorted=FALSE) # same order as input, unkeyed # use for 'unique=' argument x = c(1,1,2) y = c(4,6,4) CJ(x, y, unique=TRUE) # unique(x) and unique(y) are computed automatically