recode.haven_labelled: Recode values
In labelled: Manipulating Labelled Data

recode.haven_labelled

R Documentation

Recode values

Description

Extend dplyr::recode() method from dplyr to works with labelled vectors.

Usage

## S3 method for class 'haven_labelled'
recode(
  .x,
  ...,
  .default = NULL,
  .missing = NULL,
  .keep_value_labels = TRUE,
  .combine_value_labels = FALSE,
  .sep = " / "
)

Arguments

`.x`	A vector to modify
`...`	<`dynamic-dots`> Replacements. For character and factor `.x`, these should be named and replacement is based only on their name. For numeric `.x`, these can be named or not. If not named, the replacement is done based on position i.e. `.x` represents positions to look for in replacements. See examples. When named, the argument names should be the current values to be replaced, and the argument values should be the new (replacement) values. All replacements must be the same type, and must have either length one or the same length as `.x`.
`.default`	If supplied, all values not otherwise matched will be given this value. If not supplied and if the replacements are the same type as the original values in `.x`, unmatched values are not changed. If not supplied and if the replacements are not compatible, unmatched values are replaced with `NA`. `.default` must be either length 1 or the same length as `.x`.
`.missing`	If supplied, any missing values in `.x` will be replaced by this value. Must be either length 1 or the same length as `.x`.
`.keep_value_labels`	If TRUE, keep original value labels. If FALSE, remove value labels.
`.combine_value_labels`	If TRUE, will combine original value labels to generate new value labels. Note that unexpected results could be obtained if a same old value is recoded into several different new values.
`.sep`	Separator to be used when combining value labels.

Examples

x <- labelled(1:3, c(yes = 1, no = 2))
x
dplyr::recode(x, `3` = 2L)

# do not keep value labels
dplyr::recode(x, `3` = 2L, .keep_value_labels = FALSE)

# be careful, changes are not of the same type (here integers),
# NA arecreated
dplyr::recode(x, `3` = 2)

# except if you provide .default or new values for all old values
dplyr::recode(x, `1` = 1, `2` = 1, `3` = 2)

# if you change the type of the vector (here transformed into character)
# value labels are lost
dplyr::recode(x, `3` = "b", .default = "a")

# use .keep_value_labels = FALSE to avoid a warning
dplyr::recode(x, `3` = "b", .default = "a", .keep_value_labels = FALSE)

# combine value labels
x <- labelled(
  1:4,
  c(
    "strongly agree" = 1,
    "agree" = 2,
    "disagree" = 3,
    "strongly disagree" = 4
  )
)
dplyr::recode(
  x,
  `1` = 1L,
  `2` = 1L,
  `3` = 2L,
  `4` = 2L,
  .combine_value_labels = TRUE
)
dplyr::recode(
  x,
  `2` = 1L,
  `4` = 3L,
  .combine_value_labels = TRUE
)
dplyr::recode(
  x,
  `2` = 1L,
  `4` = 3L,
  .combine_value_labels = TRUE,
  .sep = " or "
)
dplyr::recode(
  x,
  `2` = 1L,
  .default = 2L,
  .combine_value_labels = TRUE
)

# example when combining some values without a label
y <- labelled(1:4, c("strongly agree" = 1))
dplyr::recode(y, `2` = 1L, `4` = 3L, .combine_value_labels = TRUE)

labelled documentation built on May 29, 2024, 9:34 a.m.