Learn R Programming

tibble (version 3.1.0)

new_tibble: Tibble constructor and validator

Description

Creates or validates a subclass of a tibble. These function is mostly useful for package authors that implement subclasses of a tibble, like sf or tsibble.

new_tibble() creates a new object as a subclass of tbl_df, tbl and data.frame. This function is optimized for performance, checks are reduced to a minimum.

validate_tibble() checks a tibble for internal consistency. Correct behavior can be guaranteed only if this function runs without raising an error.

Usage

new_tibble(x, ..., nrow, class = NULL, subclass = NULL)

validate_tibble(x)

Arguments

x

A tibble-like object.

...

Name-value pairs of additional attributes.

nrow

The number of rows, required.

class

Subclasses to assign to the new object, default: none.

subclass

Deprecated, retained for compatibility. Please use the class argument.

Construction

For new_tibble(), x must be a list. The ... argument allows adding more attributes to the subclass. An nrow argument is required. This should be an integer of length 1, and every element of the list x should have vctrs::vec_size() equal to this value. (But this is not checked by the constructor). This takes the place of the "row.names" attribute in a data frame. x must have names (or be empty), but the names are not checked for correctness.

Validation

validate_tibble() checks for "minimal" names and that all columns are vectors, data frames or matrices. It also makes sure that all columns have the same length, and that vctrs::vec_size() is consistent with the data.

See Also

tibble() and as_tibble() for ways to construct a tibble with recycling of scalars and automatic name repair.

Examples

Run this code
# NOT RUN {
# The nrow argument is always required:
new_tibble(list(a = 1:3, b = 4:6), nrow = 3)

# Existing row.names attributes are ignored:
try(new_tibble(iris, nrow = 3))

# The length of all columns must be compatible with the nrow argument:
try(new_tibble(list(a = 1:3, b = 4:6), nrow = 2))
# }

Run the code above in your browser using DataLab