tidyr: pivot_wider – R documentation

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pivot_wider

Pivot data from long to wide

Description

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

Learn more in vignette("pivot").

Usage

pivot_wider(
  data,
  id_cols = NULL,
  names_from = name,
  names_prefix = "",
  names_sep = "_",
  names_glue = NULL,
  names_sort = FALSE,
  names_repair = "check_unique",
  values_from = value,
  values_fill = NULL,
  values_fn = NULL,
  ...
)

Arguments

`data`	A data frame to pivot.
`id_cols`	<`tidy-select`> A set of columns that uniquely identifies each observation. Defaults to all columns in `data` except for the columns specified in `names_from` and `values_from`. Typically used when you have redundant variables, i.e. variables whose values are perfectly correlated with existing variables.
`names_from, values_from`	<`tidy-select`> A pair of arguments describing which column (or columns) to get the name of the output column (`names_from`), and which column (or columns) to get the cell values from (`values_from`). If `values_from` contains multiple values, the value will be added to the front of the output column.
`names_prefix`	String added to the start of every variable name. This is particularly useful if `names_from` is a numeric vector and you want to create syntactic variable names.
`names_sep`	If `names_from` or `values_from` contains multiple variables, this will be used to join their values together into a single string to use as a column name.
`names_glue`	Instead of `names_sep` and `names_prefix`, you can supply a glue specification that uses the `names_from` columns (and special `.value`) to create custom column names.
`names_sort`	Should the column names be sorted? If `FALSE`, the default, column names are ordered by first appearance.
`names_repair`	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, or `"unique"` to de-duplicated by adding numeric suffixes. See `vctrs::vec_as_names()` for more options.
`values_fill`	Optionally, a (scalar) value that specifies what each `value` should be filled in with when missing. This can be a named list if you want to apply different aggregations to different value columns.
`values_fn`	Optionally, a function applied to the `value` in each cell in the output. You will typically use this when the combination of `id_cols` and `value` column does not uniquely identify an observation. This can be a named list if you want to apply different aggregations to different value columns.
`...`	Additional arguments passed on to methods.

Details

pivot_wider() is an updated approach to spread(), designed to be both simpler to use and to handle more use cases. We recommend you use pivot_wider() for new code; spread() isn't going away but is no longer under active development.

Examples

# See vignette("pivot") for examples and explanation

fish_encounters
fish_encounters %>%
  pivot_wider(names_from = station, values_from = seen)
# Fill in missing values
fish_encounters %>%
  pivot_wider(names_from = station, values_from = seen, values_fill = 0)

# Generate column names from multiple variables
us_rent_income
us_rent_income %>%
  pivot_wider(names_from = variable, values_from = c(estimate, moe))

# When there are multiple `names_from` or `values_from`, you can use
# use `names_sep` or `names_glue` to control the output variable names
us_rent_income %>%
  pivot_wider(
    names_from = variable,
    names_sep = ".",
    values_from = c(estimate, moe)
  )
us_rent_income %>%
  pivot_wider(
    names_from = variable,
    names_glue = "{variable}_{.value}",
    values_from = c(estimate, moe)
  )

# Can perform aggregation with values_fn
warpbreaks <- as_tibble(warpbreaks[c("wool", "tension", "breaks")])
warpbreaks
warpbreaks %>%
  pivot_wider(
    names_from = wool,
    values_from = breaks,
    values_fn = mean
  )

tidyr

Tidy Messy Data

v1.1.3

MIT + file LICENSE

Authors

Hadley Wickham [aut, cre], RStudio [cph]

Initial release