Creates a data.table to be passed in as the i to a [.data.table join.
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Each argument is a vector. Generally each vector is the same length but if they are not then usual silent repitition is applied.
logical. Should the input order be retained?
CJ are convenience functions for creating a data.table in the context of a data.table 'query' on
x[data.table(id)] is the same as
x[J(id)] but the latter is more readable. Identical alternatives are
x must have a key when passing in a join table as the
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
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.
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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