Convert a dataset_df to a base data.frame

Converts a dataset_df into a plain data.frame. By default this strips semantic metadata (label, unit, concept/definition, namespace) from each column, but this can be controlled via the strip_attributes argument.

Dataset-level metadata remains attached as inert attributes.

Usage

# S3 method for class 'dataset_df'
as.data.frame(
  x,
  ...,
  strip_attributes = TRUE,
  optional = FALSE,
  stringsAsFactors = FALSE
)

Arguments

x

A dataset_df.

...

Passed to base::as.data.frame().

strip_attributes

Logical: should column-level semantic metadata be stripped? Default: TRUE.

optional

logical. If TRUE, setting row names and converting column names (to syntactic names: see make.names) is optional. Note that all of R's base package as.data.frame() methods use optional only for column names treatment, basically with the meaning of data.frame(*, check.names = !optional). See also the make.names argument of the matrix method.

stringsAsFactors

logical: should the character vector be converted to a factor?

Value

A base R data.frame without the dataset_df class.

Examples

data(orange_df)
as.data.frame(orange_df)
#>        rowid tree  age circumference
#> 1   orange:1    1  118            30
#> 2   orange:2    1  484            58
#> 3   orange:3    1  664            87
#> 4   orange:4    1 1004           115
#> 5   orange:5    1 1231           120
#> 6   orange:6    1 1372           142
#> 7   orange:7    1 1582           145
#> 8   orange:8    2  118            33
#> 9   orange:9    2  484            69
#> 10 orange:10    2  664           111
#> 11 orange:11    2 1004           156
#> 12 orange:12    2 1231           172
#> 13 orange:13    2 1372           203
#> 14 orange:14    2 1582           203
#> 15 orange:15    3  118            30
#> 16 orange:16    3  484            51
#> 17 orange:17    3  664            75
#> 18 orange:18    3 1004           108
#> 19 orange:19    3 1231           115
#> 20 orange:20    3 1372           139
#> 21 orange:21    3 1582           140
#> 22 orange:22    4  118            32
#> 23 orange:23    4  484            62
#> 24 orange:24    4  664           112
#> 25 orange:25    4 1004           167
#> 26 orange:26    4 1231           179
#> 27 orange:27    4 1372           209
#> 28 orange:28    4 1582           214
#> 29 orange:29    5  118            30
#> 30 orange:30    5  484            49
#> 31 orange:31    5  664            81
#> 32 orange:32    5 1004           125
#> 33 orange:33    5 1231           142
#> 34 orange:34    5 1372           174
#> 35 orange:35    5 1582           177