Coerce to data.table
Functions to check if an object is data.table
, or coerce it if possible.
as.data.table(x, keep.rownames=FALSE, ...) ## S3 method for class 'data.table' as.data.table(x, ...) ## S3 method for class 'array' as.data.table(x, keep.rownames=FALSE, key=NULL, sorted=TRUE, value.name="value", na.rm=TRUE, ...) is.data.table(x)
x |
An R object. |
keep.rownames |
Default is |
key |
Character vector of one or more column names which is passed to |
sorted |
logical used in array method, default |
value.name |
character scalar used in array method, default |
na.rm |
logical used in array method, default |
... |
Additional arguments to be passed to or from other methods. |
as.data.table
is a generic function with many methods, and other packages can supply further methods.
If a list
is supplied, each element is converted to a column in the data.table
with shorter elements recycled automatically. Similarly, each column of a matrix
is converted separately.
character
objects are not converted to factor
types unlike as.data.frame
.
keep.rownames
argument can be used to preserve the (row)names attribute in the resulting data.table
.
nn = c(a=0.1, b=0.2, c=0.3, d=0.4) as.data.table(nn) as.data.table(nn, keep.rownames=TRUE) as.data.table(nn, keep.rownames="rownames") # char object not converted to factor cc = c(X="a", Y="b", Z="c") as.data.table(cc) as.data.table(cc, keep.rownames=TRUE) as.data.table(cc, keep.rownames="rownames") mm = matrix(1:4, ncol=2, dimnames=list(c("r1", "r2"), c("c1", "c2"))) as.data.table(mm) as.data.table(mm, keep.rownames=TRUE) as.data.table(mm, keep.rownames="rownames") as.data.table(mm, key="c1") ll = list(a=1:2, b=3:4) as.data.table(ll) as.data.table(ll, keep.rownames=TRUE) as.data.table(ll, keep.rownames="rownames") DF = data.frame(x=rep(c("x","y","z"),each=2), y=c(1,3,6), row.names=LETTERS[1:6]) as.data.table(DF) as.data.table(DF, keep.rownames=TRUE) as.data.table(DF, keep.rownames="rownames") DT = data.table(x=rep(c("x","y","z"),each=2), y=c(1:6)) as.data.table(DT) as.data.table(DT, key='x') ar = rnorm(27) ar[sample(27, 15)] = NA dim(ar) = c(3L,3L,3L) as.data.table(ar)
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