unnest_wider: Unnest a list-column into columns
In tidyr: Tidy Messy Data

unnest_wider

R Documentation

Unnest a list-column into columns

Description

unnest_wider() turns each element of a list-column into a column. It is most naturally suited to list-columns where every element is named, and the names are consistent from row-to-row. unnest_wider() preserves the rows of x while modifying the columns.

Learn more in vignette("rectangle").

Usage

unnest_wider(
  data,
  col,
  names_sep = NULL,
  simplify = TRUE,
  strict = FALSE,
  names_repair = "check_unique",
  ptype = NULL,
  transform = NULL
)

Arguments

`data`	A data frame.
`col`	<`tidy-select`> List-column(s) to unnest. When selecting multiple columns, values from the same row will be recycled to their common size.
`names_sep`	If `NULL`, the default, the names will be left as is. If a string, the outer and inner names will be pasted together using `names_sep` as a separator. If any values being unnested are unnamed, then `names_sep` must be supplied, otherwise an error is thrown. When `names_sep` is supplied, names are automatically generated for unnamed values as an increasing sequence of integers.
`simplify`	If `TRUE`, will attempt to simplify lists of length-1 vectors to an atomic vector. Can also be a named list containing `TRUE` or `FALSE` declaring whether or not to attempt to simplify a particular column. If a named list is provided, the default for any unspecified columns is `TRUE`.
`strict`	A single logical specifying whether or not to apply strict vctrs typing rules. If `FALSE`, typed empty values (like `list()` or `integer()`) nested within list-columns will be treated like `NULL` and will not contribute to the type of the unnested column. This is useful when working with JSON, where empty values tend to lose their type information and show up as `list()`.
`names_repair`	Used to check that output data frame has valid names. Must be one of the following options: `⁠"minimal⁠`": no name repair or checks, beyond basic existence, `⁠"unique⁠`": make sure names are unique and not empty, `⁠"check_unique⁠`": (the default), no name repair, but check they are unique, `⁠"universal⁠`": make the names unique and syntactic a function: apply custom name repair. tidyr_legacy: use the name repair from tidyr 0.8. a formula: a purrr-style anonymous function (see `rlang::as_function()`) See `vctrs::vec_as_names()` for more details on these terms and the strategies used to enforce them.
`ptype`	Optionally, a named list of prototypes declaring the desired output type of each component. Alternatively, a single empty prototype can be supplied, which will be applied to all components. Use this argument if you want to check that each element has the type you expect when simplifying. If a `ptype` has been specified, but `simplify = FALSE` or simplification isn't possible, then a list-of column will be returned and each element will have type `ptype`.
`transform`	Optionally, a named list of transformation functions applied to each component. Alternatively, a single function can be supplied, which will be applied to all components. Use this argument if you want to transform or parse individual elements as they are extracted. When both `ptype` and `transform` are supplied, the `transform` is applied before the `ptype`.

Examples

df <- tibble(
  character = c("Toothless", "Dory"),
  metadata = list(
    list(
      species = "dragon",
      color = "black",
      films = c(
        "How to Train Your Dragon",
        "How to Train Your Dragon 2",
        "How to Train Your Dragon: The Hidden World"
      )
    ),
    list(
      species = "blue tang",
      color = "blue",
      films = c("Finding Nemo", "Finding Dory")
    )
  )
)
df

# Turn all components of metadata into columns
df %>% unnest_wider(metadata)

# Choose not to simplify list-cols of length-1 elements
df %>% unnest_wider(metadata, simplify = FALSE)
df %>% unnest_wider(metadata, simplify = list(color = FALSE))

# You can also widen unnamed list-cols:
df <- tibble(
  x = 1:3,
  y = list(NULL, 1:3, 4:5)
)
# but you must supply `names_sep` to do so, which generates automatic names:
df %>% unnest_wider(y, names_sep = "_")

# 0-length elements ---------------------------------------------------------
# The defaults of `unnest_wider()` treat empty types (like `list()`) as `NULL`.
json <- list(
  list(x = 1:2, y = 1:2),
  list(x = list(), y = 3:4),
  list(x = 3L, y = list())
)

df <- tibble(json = json)
df %>%
  unnest_wider(json)

# To instead enforce strict vctrs typing rules, use `strict`
df %>%
  unnest_wider(json, strict = TRUE)

tidyr documentation built on June 24, 2024, 5:14 p.m.