Coerce lists and data.frames to data.table by reference
In data.table
parlance, all set*
functions change their input by reference. That is, no copy is made at all, other than temporary working memory, which is as large as one column.. The only other data.table
operator that modifies input by reference is :=
. Check out the See Also
section below for other set*
function data.table
provides.
setDT
converts lists (both named and unnamed) and data.frames to data.tables by reference. This feature was requested on Stackoverflow.
setDT(x, keep.rownames=FALSE, key=NULL, check.names=FALSE)
x |
A named or unnamed |
keep.rownames |
For |
key |
Character vector of one or more column names which is passed to |
check.names |
Just as |
When working on large lists
or data.frames
, it might be both time and memory consuming to convert them to a data.table
using as.data.table(.)
, as this will make a complete copy of the input object before to convert it to a data.table
. The setDT
function takes care of this issue by allowing to convert lists
- both named and unnamed lists and data.frames
by reference instead. That is, the input object is modified in place, no copy is being made.
The input is modified by reference, and returned (invisibly) so it can be used in compound statements; e.g., setDT(X)[, sum(B), by=A]
. If you require a copy, take a copy first (using DT2 = copy(DT)
). See ?copy
.
data.table
, as.data.table
, setDF
, copy
, setkey
, setcolorder
, setattr
, setnames
, set
, :=
, setorder
set.seed(45L) X = data.frame(A=sample(3, 10, TRUE), B=sample(letters[1:3], 10, TRUE), C=sample(10), stringsAsFactors=FALSE) # Convert X to data.table by reference and # get the frequency of each "A,B" combination setDT(X)[, .N, by=.(A,B)] # convert list to data.table # autofill names X = list(1:4, letters[1:4]) setDT(X) # don't provide names X = list(a=1:4, letters[1:4]) setDT(X, FALSE) # setkey directly X = list(a = 4:1, b=runif(4)) setDT(X, key="a")[] # check.names argument X = list(a=1:5, a=6:10) setDT(X, check.names=TRUE)[]
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