Coerce to data.table

Functions to check if an object is data.table, or coerce it if possible.

Usage

as.data.table(x, keep.rownames=FALSE, ...)

# S3 method for class 'data.table'
as.data.table(x, ..., key=NULL)

# 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)

Arguments

x: An R object.
keep.rownames: Default is FALSE. If TRUE, adds the input object's names as a separate column named "rn". keep.rownames = "id" names the column "id" instead. For lists and when calling data.table(), names from the first named vector are extracted and used as row names, similar to data.frame() behavior.
key: Character vector of one or more column names which is passed to setkeyv.
sorted: logical used in array method, default TRUE is overridden when key is provided.
value.name: character scalar used in array method, default "value".
na.rm: logical used in array method, default TRUE will remove rows with NA values.
...: Additional arguments to be passed to or from other methods.

Details

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.

If a data.frame is supplied, all classes preceding "data.frame" are stripped. Similarly, for data.table as input, all classes preceding "data.table" are stripped. as.data.table methods returns a copy of original data. To modify by reference see setDT and setDF.

keep.rownames argument can be used to preserve the (row)names attribute in the resulting data.table.

Examples

nn = c(a=0.1, b=0.2, c=0.3, d=0.4)
as.data.table(nn)
#>       nn
#>    <num>
#> 1:   0.1
#> 2:   0.2
#> 3:   0.3
#> 4:   0.4
as.data.table(nn, keep.rownames=TRUE)
#>        rn    nn
#>    <char> <num>
#> 1:      a   0.1
#> 2:      b   0.2
#> 3:      c   0.3
#> 4:      d   0.4
as.data.table(nn, keep.rownames="rownames")
#>    rownames    nn
#>      <char> <num>
#> 1:        a   0.1
#> 2:        b   0.2
#> 3:        c   0.3
#> 4:        d   0.4

# char object not converted to factor
cc = c(X="a", Y="b", Z="c")
as.data.table(cc)
#>        cc
#>    <char>
#> 1:      a
#> 2:      b
#> 3:      c
as.data.table(cc, keep.rownames=TRUE)
#>        rn     cc
#>    <char> <char>
#> 1:      X      a
#> 2:      Y      b
#> 3:      Z      c
as.data.table(cc, keep.rownames="rownames")
#>    rownames     cc
#>      <char> <char>
#> 1:        X      a
#> 2:        Y      b
#> 3:        Z      c

mm = matrix(1:4, ncol=2, dimnames=list(c("r1", "r2"), c("c1", "c2")))
as.data.table(mm)
#>       c1    c2
#>    <int> <int>
#> 1:     1     3
#> 2:     2     4
as.data.table(mm, keep.rownames=TRUE)
#>        rn    c1    c2
#>    <char> <int> <int>
#> 1:     r1     1     3
#> 2:     r2     2     4
as.data.table(mm, keep.rownames="rownames")
#>    rownames    c1    c2
#>      <char> <int> <int>
#> 1:       r1     1     3
#> 2:       r2     2     4
as.data.table(mm, key="c1")
#> Key: <c1>
#>       c1    c2
#>    <int> <int>
#> 1:     1     3
#> 2:     2     4

ll = list(a=1:2, b=3:4)
as.data.table(ll)
#>        a     b
#>    <int> <int>
#> 1:     1     3
#> 2:     2     4
as.data.table(ll, keep.rownames=TRUE)
#>        a     b
#>    <int> <int>
#> 1:     1     3
#> 2:     2     4
as.data.table(ll, keep.rownames="rownames")
#>        a     b
#>    <int> <int>
#> 1:     1     3
#> 2:     2     4

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)
#>         x     y
#>    <char> <num>
#> 1:      x     1
#> 2:      x     3
#> 3:      y     6
#> 4:      y     1
#> 5:      z     3
#> 6:      z     6
as.data.table(DF, keep.rownames=TRUE)
#>        rn      x     y
#>    <char> <char> <num>
#> 1:      A      x     1
#> 2:      B      x     3
#> 3:      C      y     6
#> 4:      D      y     1
#> 5:      E      z     3
#> 6:      F      z     6
as.data.table(DF, keep.rownames="rownames")
#>    rownames      x     y
#>      <char> <char> <num>
#> 1:        A      x     1
#> 2:        B      x     3
#> 3:        C      y     6
#> 4:        D      y     1
#> 5:        E      z     3
#> 6:        F      z     6

DT = data.table(x=rep(c("x","y","z"),each=2), y=c(1:6))
as.data.table(DT)
#>         x     y
#>    <char> <int>
#> 1:      x     1
#> 2:      x     2
#> 3:      y     3
#> 4:      y     4
#> 5:      z     5
#> 6:      z     6
as.data.table(DT, key='x')
#> Key: <x>
#>         x     y
#>    <char> <int>
#> 1:      x     1
#> 2:      x     2
#> 3:      y     3
#> 4:      y     4
#> 5:      z     5
#> 6:      z     6

ar = rnorm(27)
ar[sample(27, 15)] = NA
dim(ar) = c(3L,3L,3L)
as.data.table(ar)
#> Key: <V1, V2, V3>
#>        V1    V2    V3      value
#>     <int> <int> <int>      <num>
#>  1:     1     1     3 -0.9358474
#>  2:     1     2     2  0.4681544
#>  3:     2     2     1  2.0650249
#>  4:     2     2     2  0.3629513
#>  5:     2     3     1 -1.8630115
#>  6:     2     3     2  1.8885049
#>  7:     2     3     3  1.6235489
#>  8:     3     1     2 -0.9140748
#>  9:     3     2     3  0.1764886
#> 10:     3     3     1 -0.5220125
#> 11:     3     3     2 -0.0974451
#> 12:     3     3     3  0.1120381

Usage

Arguments

Details

See also

Examples