as_tibble()
turns an existing object, such as a data frame or
matrix, into a so-called tibble, a data frame with class tbl_df
. This is
in contrast with tibble()
, which builds a tibble from individual columns.
as_tibble()
is to tibble()
as base::as.data.frame()
is to
base::data.frame()
.
as_tibble()
is an S3 generic, with methods for:
data.frame
: Thin wrapper around the list
method
that implements tibble's treatment of rownames.
Default: Other inputs are first coerced with base::as.data.frame()
.
as_tibble_row()
converts a vector to a tibble with one row.
If the input is a list, all elements must have size one.
as_tibble_col()
converts a vector to a tibble with one column.
as_tibble(
x,
...,
.rows = NULL,
.name_repair = c("check_unique", "unique", "universal", "minimal"),
rownames = pkgconfig::get_config("tibble::rownames", NULL)
)# S3 method for data.frame
as_tibble(
x,
validate = NULL,
...,
.rows = NULL,
.name_repair = c("check_unique", "unique", "universal", "minimal"),
rownames = pkgconfig::get_config("tibble::rownames", NULL)
)
# S3 method for list
as_tibble(
x,
validate = NULL,
...,
.rows = NULL,
.name_repair = c("check_unique", "unique", "universal", "minimal")
)
# S3 method for matrix
as_tibble(x, ..., validate = NULL, .name_repair = NULL)
# S3 method for table
as_tibble(x, `_n` = "n", ..., n = `_n`, .name_repair = "check_unique")
# S3 method for `NULL`
as_tibble(x, ...)
# S3 method for default
as_tibble(x, ...)
as_tibble_row(
x,
.name_repair = c("check_unique", "unique", "universal", "minimal")
)
as_tibble_col(x, column_name = "value")
A data frame, list, matrix, or other object that could reasonably be coerced to a tibble.
Unused, for extensibility.
The number of rows, useful to create a 0-column tibble or just as an additional check.
Treatment of problematic column names:
"minimal"
: No name repair or checks, beyond basic existence,
"unique"
: Make sure names are unique and not empty,
"check_unique"
: (default value), no name repair, but check they are
unique
,
"universal"
: Make the names unique
and syntactic
a function: apply custom name repair (e.g., .name_repair = make.names
for names in the style of base R).
A purrr-style anonymous function, see rlang::as_function()
This argument is passed on as repair
to vctrs::vec_as_names()
.
See there for more details on these terms and the strategies used
to enforce them.
How to treat existing row names of a data frame or matrix:
NULL
: remove row names. This is the default.
NA
: keep row names.
A string: the name of a new column. Existing rownames are transferred
into this column and the row.names
attribute is deleted.
Read more in rownames.
Name for count column, default: "n"
.
Name of the column.
The default behavior is to silently remove row names.
New code should explicitly convert row names to a new column using the
rownames
argument.
For existing code that relies on the retention of row names, call
pkgconfig::set_config("tibble::rownames" = NA)
in your script or in your
package's .onLoad()
function.
Using as_tibble()
for vectors is superseded as of version 3.0.0,
prefer the more expressive as_tibble_row()
and
as_tibble_col()
variants for new code.
tibble()
constructs a tibble from individual columns. enframe()
converts a named vector to a tibble with a column of names and column of
values. Name repair is implemented using vctrs::vec_as_names()
.
# NOT RUN {
m <- matrix(rnorm(50), ncol = 5)
colnames(m) <- c("a", "b", "c", "d", "e")
df <- as_tibble(m)
as_tibble_row(c(a = 1, b = 2))
as_tibble_row(list(c = "three", d = list(4:5)))
as_tibble_row(1:3, .name_repair = "unique")
as_tibble_col(1:3)
as_tibble_col(
list(c = "three", d = list(4:5)),
column_name = "data"
)
# }
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