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().

recode(.x, ..., .default = NULL, .missing = NULL)

recode_factor(.x, ..., .default = NULL, .missing = NULL,
.ordered = FALSE)

## Arguments

.x A vector to modify 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. These dots support tidy dots features. 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. If supplied, any missing values in .x will be replaced by this value. Must be either length 1 or the same length as .x. If TRUE, recode_factor() creates an ordered factor.

## Value

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.

## Details

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.

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.

## Examples

# 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")#>  [1] "Apple" "b"     "b"     "Apple" "Apple" "c"     "c"     "Apple" "b"
#> [10] "b"    recode(char_vec, a = "Apple", b = "Banana")#>  [1] "Apple"  "Banana" "Banana" "Apple"  "Apple"  "c"      "c"      "Apple"
#>  [9] "Banana" "Banana"
# Use .default as replacement for unmatched values
recode(char_vec, a = "Apple", b = "Banana", .default = NA_character_)#>  [1] "Apple"  "Banana" "Banana" "Apple"  "Apple"  NA       NA       "Apple"
#>  [9] "Banana" "Banana"
# Use a named character vector for unquote splicing with !!!
level_key <- c(a = "apple", b = "banana", c = "carrot")
recode(char_vec, !!!level_key)#>  [1] "apple"  "banana" "banana" "apple"  "apple"  "carrot" "carrot" "apple"
#>  [9] "banana" "banana"
# For numeric values, named arguments can also be used
num_vec <- c(1:4, NA)
recode(num_vec, 2 = 20L, 4 = 40L)#> [1]  1 20  3 40 NA
# Or if you don't name the arguments, recode() matches by position.
# (Only works for numeric vector)
recode(num_vec, "a", "b", "c", "d")#> [1] "a" "b" "c" "d" NA # .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")#> [1] "a"       "nothing" "c"
# 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")#> Warning: Unreplaced values treated as NA as .x is not compatible. Please specify replacements exhaustively or supply .default#> [1] NA  "b" NA  "d" NA # use .default to change the replacement value
recode(num_vec, "a", "b", "c", .default = "other")#> [1] "a"     "b"     "c"     "other" NA     # use .missing to replace missing values in .x
recode(num_vec, "a", "b", "c", .default = "other", .missing = "missing")#> [1] "a"       "b"       "c"       "other"   "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))#> [1] Apple b     c
#> Levels: Apple b c
# 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")#> Warning: Unreplaced values treated as NA as .x is not compatible. Please specify replacements exhaustively or supply .default#> [1] z    y    x    <NA> <NA>
#> Levels: z y xrecode_factor(num_vec, 1 = "z", 2 = "y", 3 = "x",
.default = "D")#> [1] z    y    x    D    <NA>
#> Levels: z y x Drecode_factor(num_vec, 1 = "z", 2 = "y", 3 = "x",
.default = "D", .missing = "M")#> [1] z y x D M
#> Levels: z y x D 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")#> [1] a z y
#> Levels: z y arecode_factor(factor(letters[1:3]), b = "z", c = "y")#> [1] a z y
#> Levels: z y a
# 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)#>  [1] apple  banana banana apple  apple  carrot carrot apple  banana banana
#> Levels: apple banana carrot