These functions are variants of map() iterate over multiple arguments in parallel. map2() and walk2() are specialised for the two argument case; pmap() and pwalk() allow you to provide any number of arguments in a list.

map2(.x, .y, .f, ...)

map2_lgl(.x, .y, .f, ...)

map2_int(.x, .y, .f, ...)

map2_dbl(.x, .y, .f, ...)

map2_chr(.x, .y, .f, ...)

map2_dfr(.x, .y, .f, ..., .id = NULL)

map2_dfc(.x, .y, .f, ...)

walk2(.x, .y, .f, ...)

pmap(.l, .f, ...)

pmap_lgl(.l, .f, ...)

pmap_int(.l, .f, ...)

pmap_dbl(.l, .f, ...)

pmap_chr(.l, .f, ...)

pmap_dfr(.l, .f, ..., .id = NULL)

pmap_dfc(.l, .f, ...)

pwalk(.l, .f, ...)

Arguments

.x, .y

Vectors of the same length. A vector of length 1 will be recycled.

.f

A function, formula, or atomic vector.

If a function, it is used as is.

If a formula, e.g. ~ .x + 2, it is converted to a function. There are three ways to refer to the arguments:

  • For a single argument function, use .

  • For a two argument function, use .x and .y

  • For more arguments, use ..1, ..2, ..3 etc

This syntax allows you to create very compact anonymous functions.

If character vector, numeric vector, or list, it is converted to an extractor function. Character vectors index by name and numeric vectors index by position; use a list to index by position and name at different levels. Within a list, wrap strings in get_attr() to extract named attributes. If a component is not present, the value of .default will be returned.

...

Additional arguments passed on to .f.

.id

If not NULL a variable with this name will be created giving either the name or the index of the data frame.

.l

A list of lists. The length of .l determines the number of arguments that .f will be called with. List names will be used if present.

Value

An atomic vector, list, or data frame, depending on the suffix. Atomic vectors and lists will be named if .x or the first element of .l is named.

If all input is length 0, the output will be length 0. If any input is length 1, it will be recycled to the length of the longest.

Details

Note that arguments to be vectorised over come before the .f, and arguments that are supplied to every call come after .f.

See also

Other map variants: imap, invoke, lmap, map, modify

Examples

x <- list(1, 10, 100) y <- list(1, 2, 3) z <- list(5, 50, 500) map2(x, y, ~ .x + .y)
#> [[1]] #> [1] 2 #> #> [[2]] #> [1] 12 #> #> [[3]] #> [1] 103 #>
# Or just map2(x, y, `+`)
#> [[1]] #> [1] 2 #> #> [[2]] #> [1] 12 #> #> [[3]] #> [1] 103 #>
# Split into pieces, fit model to each piece, then predict by_cyl <- mtcars %>% split(.$cyl) mods <- by_cyl %>% map(~ lm(mpg ~ wt, data = .)) map2(mods, by_cyl, predict)
#> $`4` #> Datsun 710 Merc 240D Merc 230 Fiat 128 Honda Civic #> 26.47010 21.55719 21.78307 27.14774 30.45125 #> Toyota Corolla Toyota Corona Fiat X1-9 Porsche 914-2 Lotus Europa #> 29.20890 25.65128 28.64420 27.48656 31.02725 #> Volvo 142E #> 23.87247 #> #> $`6` #> Mazda RX4 Mazda RX4 Wag Hornet 4 Drive Valiant Merc 280 #> 21.12497 20.41604 19.47080 18.78968 18.84528 #> Merc 280C Ferrari Dino #> 18.84528 20.70795 #> #> $`8` #> Hornet Sportabout Duster 360 Merc 450SE Merc 450SL #> 16.32604 16.04103 14.94481 15.69024 #> Merc 450SLC Cadillac Fleetwood Lincoln Continental Chrysler Imperial #> 15.58061 12.35773 11.97625 12.14945 #> Dodge Challenger AMC Javelin Camaro Z28 Pontiac Firebird #> 16.15065 16.33700 15.44907 15.43811 #> Ford Pantera L Maserati Bora #> 16.91800 16.04103 #>
pmap(list(x, y, z), sum)
#> [[1]] #> [1] 7 #> #> [[2]] #> [1] 62 #> #> [[3]] #> [1] 603 #>
# Matching arguments by position pmap(list(x, y, z), function(a, b ,c) a / (b + c))
#> [[1]] #> [1] 0.1666667 #> #> [[2]] #> [1] 0.1923077 #> #> [[3]] #> [1] 0.1988072 #>
# Matching arguments by name l <- list(a = x, b = y, c = z) pmap(l, function(c, b, a) a / (b + c))
#> [[1]] #> [1] 0.1666667 #> #> [[2]] #> [1] 0.1923077 #> #> [[3]] #> [1] 0.1988072 #>
# Vectorizing a function over multiple arguments df <- data.frame( x = c("apple", "banana", "cherry"), pattern = c("p", "n", "h"), replacement = c("x", "f", "q"), stringsAsFactors = FALSE ) pmap(df, gsub)
#> [[1]] #> [1] "axxle" #> #> [[2]] #> [1] "bafafa" #> #> [[3]] #> [1] "cqerry" #>
pmap_chr(df, gsub)
#> [1] "axxle" "bafafa" "cqerry"
## Use `...` to absorb unused components of input list .l df <- data.frame( x = 1:3 + 0.1, y = 3:1 - 0.1, z = letters[1:3] ) plus <- function(x, y) x + y not_run({ ## this won't work pmap(df, plus) }) ## but this will plus2 <- function(x, y, ...) x + y pmap_dbl(df, plus2)
#> [1] 4 4 4