tibble

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Build a data frame

tibble() constructs a data frame. It is used like base::data.frame(), but with a couple notable differences:

  • The returned data frame has the class tbl_df, in addition to data.frame. This allows so-called "tibbles" to exhibit some special behaviour, such as enhanced printing. Tibbles are fully described in tbl_df.

  • tibble() is much lazier than base::data.frame() in terms of transforming the user's input. Character vectors are not coerced to factor. List-columns are expressly anticipated and do not require special tricks. Column names are not modified.

  • tibble() builds columns sequentially. When defining a column, you can refer to columns created earlier in the call. Only columns of length one are recycled.

  • If a column evaluates to a data frame or tibble, it is nested or spliced. See examples.

tibble_row() constructs a data frame that is guaranteed to occupy one row. Vector columns are required to have size one, non-vector columns are wrapped in a list.

Usage
tibble(
  ...,
  .rows = NULL,
  .name_repair = c("check_unique", "unique", "universal", "minimal")
)

tibble_row( ..., .name_repair = c("check_unique", "unique", "universal", "minimal") )

Arguments
...

<dynamic-dots> A set of name-value pairs. These arguments are processed with rlang::quos() and support unquote via !! and unquote-splice via !!!. Use := to create columns that start with a dot.

Arguments are evaluated sequentially. You can refer to previously created elements directly or using the .data pronoun. An existing .data pronoun, provided e.g. inside dplyr::mutate(), is not available.

.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()

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.

Value

A tibble, which is a colloquial term for an object of class tbl_df. A tbl_df object is also a data frame, i.e. it has class data.frame.

See Also

Use as_tibble() to turn an existing object into a tibble. Use enframe() to convert a named vector into a tibble. Name repair is detailed in vctrs::vec_as_names(). See quasiquotation for more details on tidy dots semantics, i.e. exactly how the ... argument is processed.

Aliases
  • tibble
  • tibble_row
Examples
# NOT RUN {
# Unnamed arguments are named with their expression:
a <- 1:5
tibble(a, a * 2)

# Scalars (vectors of length one) are recycled:
tibble(a, b = a * 2, c = 1)

# Columns are available in subsequent expressions:
tibble(x = runif(10), y = x * 2)

# tibble() never coerces its inputs,
str(tibble(letters))
str(tibble(x = list(diag(1), diag(2))))

# or munges column names (unless requested),
tibble(`a + b` = 1:5)

# but it forces you to take charge of names, if they need repair:
try(tibble(x = 1, x = 2))
tibble(x = 1, x = 2, .name_repair = "unique")
tibble(x = 1, x = 2, .name_repair = "minimal")

## By default, non-syntactic names are allowed,
df <- tibble(`a 1` = 1, `a 2` = 2)
## because you can still index by name:
df[["a 1"]]
df$`a 1`
with(df, `a 1`)

## Syntactic names are easier to work with, though, and you can request them:
df <- tibble(`a 1` = 1, `a 2` = 2, .name_repair = "universal")
df$a.1

## You can specify your own name repair function:
tibble(x = 1, x = 2, .name_repair = make.unique)

fix_names <- function(x) gsub("\\s+", "_", x)
tibble(`year 1` = 1, `year 2` = 2, .name_repair = fix_names)

## purrr-style anonymous functions and constants
## are also supported
tibble(x = 1, x = 2, .name_repair = ~ make.names(., unique = TRUE))

tibble(x = 1, x = 2, .name_repair = ~ c("a", "b"))

# Tibbles can contain columns that are tibbles or matrices
# if the number of rows is compatible. Unnamed tibbled are
# spliced, i.e. the inner columns are inserted into the
# tibble under construction.
tibble(
  a = 1:3,
  tibble(
    b = 4:6,
    c = 7:9
  ),
  d = tibble(
    e = tibble(
      f = b
    )
  )
)
tibble(
  a = 1:4,
  b = diag(4),
  c = cov(iris[1:4])
)

# data can not contain POSIXlt columns, or tibbles or matrices
# with incompatible number of rows:
try(tibble(y = strptime("2000/01/01", "%x")))
try(tibble(a = 1:3, b = tibble(c = 4:7)))

# Use := to create columns with names that start with a dot:
tibble(.dotted = 3)
tibble(.dotted := 3)

# You can unquote an expression:
x <- 3
tibble(x = 1, y = x)
tibble(x = 1, y = !!x)

# You can splice-unquote a list of quosures and expressions:
tibble(!!! list(x = rlang::quo(1:10), y = quote(x * 2)))


# Use tibble_row() to construct a one-row tibble:
tibble_row(a = 1, lm = lm(Petal.Width ~ Petal.Length + Species, data = iris))
# }
Documentation reproduced from package tibble, version 3.0.3, License: MIT + file LICENSE

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