Converting a List of Variables into a data.table object

Question

Is there a more elegant way of converting a list of variables into a data.table object?

This does not give the desired result.

require(data.table)
set.seed(1)
Var.List <- list(a=sample(letters, 10, rep=T),b=rnorm(10), c=rnorm(10))
data.table(Var.List)

The following does give the desired result, but is slow with big lists/tables. Is there a better way? I run into this problem quite often when aggregating results from the foreach package.

data.table(as.data.frame(Var.List))

    a          b           c
 1: g -0.8204684 -0.04493361
 2: j  0.4874291 -0.01619026
 3: o  0.7383247  0.94383621
 4: x  0.5757814  0.82122120
 5: f -0.3053884  0.59390132
 6: x  1.5117812  0.91897737
 7: y  0.3898432  0.78213630
 8: r -0.6212406  0.07456498
 9: q -2.2146999 -1.98935170
10: b  1.1249309  0.61982575

Answer 1

Edit: The best solution (h.t. Arun) is to just do as.data.table(Var.List), invoking as.data.table()'s ready-made "list" method.

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Just like data.frame(), data.table() will accept a data.frame, a matrix, or an arbitrary number of vectors as inputs, processing them via its ... argument.

Taking advantage of the latter option, you can use do.call() to construct a data.table from a list of such vectors:

do.call(data.table, Var.List)
    a          b           c
 1: g -0.8204684 -0.04493361
 2: j  0.4874291 -0.01619026
 3: o  0.7383247  0.94383621
 4: x  0.5757814  0.82122120
 5: f -0.3053884  0.59390132
 6: x  1.5117812  0.91897737
 7: y  0.3898432  0.78213630
 8: r -0.6212406  0.07456498
 9: q -2.2146999 -1.98935170
10: b  1.1249309  0.61982575