Maturing lifecycle

as_tibble() turns an existing object, such as a data frame, list, 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:

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`)

# S3 method for NULL
as_tibble(x, ...)

# S3 method for default
as_tibble(x, ...)

Arguments

x

A data frame, list, matrix, or other object that could reasonably be coerced to a tibble.

...

Other arguments passed on to individual methods.

.rows

The number of rows, useful to create a 0-column tibble or just as an additional check.

.name_repair

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()

See name-repair for more details on these terms and the strategies used to enforce them.

rownames

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.

_n, validate

For compatibility only, do not use for new code.

n

Name for count column, default: "n".

Row names

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.

See also

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 documents the details of name repair.

Examples

l <- list(x = 1:500, y = runif(500), z = 500:1) df <- as_tibble(l) m <- matrix(rnorm(50), ncol = 5) colnames(m) <- c("a", "b", "c", "d", "e") df <- as_tibble(m) as_tibble(as.list(1:3), .name_repair = "unique")
#> New names: #> * `` -> `..1` #> * `` -> `..2` #> * `` -> `..3`
#> # A tibble: 1 x 3 #> ..1 ..2 ..3 #> <int> <int> <int> #> 1 1 2 3
# Prefer enframe() for vectors enframe(1:3)
#> # A tibble: 3 x 2 #> name value #> <int> <int> #> 1 1 1 #> 2 2 2 #> 3 3 3
enframe(1:3, name = NULL)
#> # A tibble: 3 x 1 #> value #> <int> #> 1 1 #> 2 2 #> 3 3
# For list-like inputs, `as_tibble()` is considerably simpler than # `as.data.frame()` and hence faster
# NOT RUN { if (requireNamespace("bench", quietly = TRUE)) { l2 <- replicate(26, sample(letters), simplify = FALSE) names(l2) <- letters bench::mark( as_tibble(l2, .name_repair = "universal"), as_tibble(l2, .name_repair = "unique"), as_tibble(l2, .name_repair = "minimal"), as_tibble(l2), as.data.frame(l2), check = FALSE ) } # }