pivot_longer: Pivot data from wide to long

In poorman: A Poor Man's Dependency Free Recreation of 'dplyr'

Pivot data from wide to long

Description

pivot_longer() "lengthens" data, increasing the number of rows and decreasing the number of columns. The inverse transformation is pivot_wider().

Usage

pivot_longer(
  data,
  cols,
  names_to = "name",
  names_prefix = NULL,
  names_sep = NULL,
  names_pattern = NULL,
  names_ptypes = list(),
  names_transform = list(),
  names_repair = "check_unique",
  values_to = "value",
  values_drop_na = FALSE,
  values_ptypes = list(),
  values_transform = list(),
  ...
)

Arguments

data	data.frame. The data to pivot.
cols	<poor-select>. Columns to pivot into longer format.
names_to	character(n). The name of the new column(s) that will contain the column names. If of length > 1, one of names_sep or names_pattern must be supplied. Two values have special meaning: NA discards the corresponding piece of the column name and ".value" indicates that the corresponding piece of the column name defines the name of the output column containing the values, overriding values_to.
names_prefix	character(1). A regular expression used to remove matching text from the start of each variable name.
names_sep, names_pattern	character(1). If names_to contains multiple values, this argument controls how the column name is broken up. names_sep is a fixed string on which to split the column names. names_pattern takes a regular expression containing matching groups (⁠()⁠); with a single value of names_to, the first matching group is used.
names_ptypes, values_ptypes	list(). Optionally, a named list of column name-prototype pairs, e.g. list(week = factor()), used to cast the newly created columns. Casts that lose information are an error.
names_transform, values_transform	list(). Optionally, a named list of column name-function pairs, e.g. list(week = as.integer), applied to the newly created columns. Functions may be given as formulas, e.g. ~ as.integer(.x).
names_repair	character(1) or function. What happens if the output has invalid column names. The default, "check_unique", is to error if the columns are duplicated. Use "minimal" to allow duplicates in the output, "unique" to de-duplicate by adding numeric suffixes or "universal" to also make the names syntactic. A function is applied to the names.
values_to	character(1). The name of the new column that will contain the values of the pivoted variables. The pivoted columns are combined following the tidyr rules: logical, integer and double columns are combined into the richest of those types, factors are combined into a factor with the union of their levels, factors and characters are combined into a character and columns of the same class keep that class. Other combinations are an error.
values_drop_na	logical(1). If TRUE, will drop rows that contain only NA in the values_to column. This effectively converts explicit missing values to implicit missing values, and should generally be used only when missing values in data were created by its structure.
...	Additional arguments passed on to methods.

Value

A data.frame.

Examples

wide_data <- data.frame(replicate(5, rnorm(10)))
# Customizing the names
pivot_longer(
  data = wide_data,
  cols = c(1, 2),
  names_to = "Column",
  values_to = "Numbers"
)

poorman documentation built on Oct. 29, 2026, 1:07 a.m.