Recode values
This is a vectorised version of switch()
: you can replace
numeric values based on their position or their name, and character or factor
values only by their name. This is an S3 generic: dplyr provides methods for
numeric, character, and factors. For logical vectors, use if_else()
. For
more complicated criteria, use case_when()
.
You can use recode()
directly with factors; it will preserve the existing
order of levels while changing the values. Alternatively, you can
use recode_factor()
, which will change the order of levels to match
the order of replacements. See the forcats
package for more tools for working with factors and their levels.
recode(.x, ..., .default = NULL, .missing = NULL) recode_factor(.x, ..., .default = NULL, .missing = NULL, .ordered = FALSE)
.x |
A vector to modify |
... |
< 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 |
.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
|
.missing |
If supplied, any missing values in |
.ordered |
If |
A vector the same length as .x
, and the same type as
the first of ...
, .default
, or .missing
.
recode_factor()
returns a factor whose levels are in the same order as
in ...
. The levels in .default
and .missing
come last.
na_if()
to replace specified values with a NA
.
coalesce()
to replace missing values with a specified value.
tidyr::replace_na()
to replace NA
with a value.
# For character values, recode values with named arguments only. Unmatched # values are unchanged. char_vec <- sample(c("a", "b", "c"), 10, replace = TRUE) recode(char_vec, a = "Apple") recode(char_vec, a = "Apple", b = "Banana") # Use .default as replacement for unmatched values. Note that NA and # replacement values need to be of the same type. For more information, see # https://adv-r.hadley.nz/vectors-chap.html#missing-values recode(char_vec, a = "Apple", b = "Banana", .default = NA_character_) # Throws an error as NA is logical, not character. ## Not run: recode(char_vec, a = "Apple", b = "Banana", .default = NA) ## End(Not run) # Use a named character vector for unquote splicing with !!! level_key <- c(a = "apple", b = "banana", c = "carrot") recode(char_vec, !!!level_key) # For numeric values, named arguments can also be used num_vec <- c(1:4, NA) recode(num_vec, `2` = 20L, `4` = 40L) # Or if you don't name the arguments, recode() matches by position. # (Only works for numeric vector) recode(num_vec, "a", "b", "c", "d") # .x (position given) looks in (...), then grabs (... value at position) # so if nothing at position (here 5), it uses .default or NA. recode(c(1,5,3), "a", "b", "c", "d", .default = "nothing") # Note that if the replacements are not compatible with .x, # unmatched values are replaced by NA and a warning is issued. recode(num_vec, `2` = "b", `4` = "d") # use .default to change the replacement value recode(num_vec, "a", "b", "c", .default = "other") # use .missing to replace missing values in .x recode(num_vec, "a", "b", "c", .default = "other", .missing = "missing") # For factor values, use only named replacements # and supply default with levels() factor_vec <- factor(c("a", "b", "c")) recode(factor_vec, a = "Apple", .default = levels(factor_vec)) # Use recode_factor() to create factors with levels ordered as they # appear in the recode call. The levels in .default and .missing # come last. recode_factor(num_vec, `1` = "z", `2` = "y", `3` = "x") recode_factor(num_vec, `1` = "z", `2` = "y", `3` = "x", .default = "D") recode_factor(num_vec, `1` = "z", `2` = "y", `3` = "x", .default = "D", .missing = "M") # When the input vector is a compatible vector (character vector or # factor), it is reused as default. recode_factor(letters[1:3], b = "z", c = "y") recode_factor(factor(letters[1:3]), b = "z", c = "y") # Use a named character vector to recode factors with unquote splicing. level_key <- c(a = "apple", b = "banana", c = "carrot") recode_factor(char_vec, !!!level_key)
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