purrr (version 1.1.0)

map: Apply a function to each element of a vector

Description

The map functions transform their input by applying a function to each element of a list or atomic vector and returning an object of the same length as the input.

• map() always returns a list. See the modify() family for versions that return an object of the same type as the input.

• map_lgl(), map_int(), map_dbl() and map_chr() return an atomic vector of the indicated type (or die trying). For these functions, .f must return a length-1 vector of the appropriate type.

• map_vec() simplifies to the common type of the output. It works with most types of simple vectors like Date, POSIXct, factors, etc.

• walk() calls .f for its side-effect and returns the input .x.

Usage

map(.x, .f, ..., .progress = FALSE)
map_lgl(.x, .f, ..., .progress = FALSE)
map_int(.x, .f, ..., .progress = FALSE)
map_dbl(.x, .f, ..., .progress = FALSE)
map_chr(.x, .f, ..., .progress = FALSE)
map_vec(.x, .f, ..., .ptype = NULL, .progress = FALSE)
walk(.x, .f, ..., .progress = FALSE)

Value

The output length is determined by the length of the input. The output names are determined by the input names. The output type is determined by the suffix:

• No suffix: a list; .f() can return anything.

• _lgl(), _int(), _dbl(), _chr() return a logical, integer, double, or character vector respectively; .f() must return a compatible atomic vector of length 1.

• _vec() return an atomic or S3 vector, the same type that .f returns. .f can return pretty much any type of vector, as long as its length 1.

• walk() returns the input .x (invisibly). This makes it easy to use in a pipe. The return value of .f() is ignored.

Any errors thrown by .f will be wrapped in an error with class purrr_error_indexed.

Arguments

.x

A list or atomic vector.

.f

A function, specified in one of the following ways:

• A named function, e.g. mean.

• An anonymous function, e.g. \(x) x + 1 or function(x) x + 1.

• A formula, e.g. ~ .x + 1. You must use .x to refer to the first argument. No longer recommended.

• A string, integer, or list, e.g. "idx", 1, or list("idx", 1) which are shorthand for \(x) pluck(x, "idx"), \(x) pluck(x, 1), and \(x) pluck(x, "idx", 1) respectively. Optionally supply .default to set a default value if the indexed element is NULL or does not exist.

Wrap a function with in_parallel() to declare that it should be performed in parallel. See in_parallel() for more details. Use of ... is not permitted in this context.

...

Additional arguments passed on to the mapped function.

We now generally recommend against using ... to pass additional (constant) arguments to .f. Instead use a shorthand anonymous function:

# Instead of
x |> map(f, 1, 2, collapse = ",")
# do:
x |> map(\(x) f(x, 1, 2, collapse = ","))

This makes it easier to understand which arguments belong to which function and will tend to yield better error messages.

.progress

Whether to show a progress bar. Use TRUE to turn on a basic progress bar, use a string to give it a name, or see progress_bars for more details.

.ptype

If NULL, the default, the output type is the common type of the elements of the result. Otherwise, supply a "prototype" giving the desired type of output.

See Also

map_if() for applying a function to only those elements of .x that meet a specified condition.

Other map variants: imap(), lmap(), map2(), map_depth(), map_if(), modify(), pmap()

Examples

# Compute normal distributions from an atomic vector
1:10 |>
  map(rnorm, n = 10)

# You can also use an anonymous function
1:10 |>
  map(\(x) rnorm(10, x))

# Simplify output to a vector instead of a list by computing the mean of the distributions
1:10 |>
  map(rnorm, n = 10) |>  # output a list
  map_dbl(mean)           # output an atomic vector

# Using set_names() with character vectors is handy to keep track
# of the original inputs:
set_names(c("foo", "bar")) |> map_chr(paste0, ":suffix")

# Working with lists
favorite_desserts <- list(Sophia = "banana bread", Eliott = "pancakes", Karina = "chocolate cake")
favorite_desserts |> map_chr(\(food) paste(food, "rocks!"))

# Extract by name or position
# .default specifies value for elements that are missing or NULL
l1 <- list(list(a = 1L), list(a = NULL, b = 2L), list(b = 3L))
l1 |> map("a", .default = "???")
l1 |> map_int("b", .default = NA)
l1 |> map_int(2, .default = NA)

# Supply multiple values to index deeply into a list
l2 <- list(
  list(num = 1:3,     letters[1:3]),
  list(num = 101:103, letters[4:6]),
  list()
)
l2 |> map(c(2, 2))

# Use a list to build an extractor that mixes numeric indices and names,
# and .default to provide a default value if the element does not exist
l2 |> map(list("num", 3))
l2 |> map_int(list("num", 3), .default = NA)

# Working with data frames
# Use map_lgl(), map_dbl(), etc to return a vector instead of a list:
mtcars |> map_dbl(sum)

# A more realistic example: split a data frame into pieces, fit a
# model to each piece, summarise and extract R^2
mtcars |>
  split(mtcars$cyl) |>
  map(\(df) lm(mpg ~ wt, data = df)) |>
  map(summary) |>
  map_dbl("r.squared")

if (FALSE) { # interactive() && rlang::is_installed("mirai") && rlang::is_installed("carrier")
# Run in interactive sessions only as spawns additional processes

# To use parallelized map:
# 1. Set daemons (number of parallel processes) first:
mirai::daemons(2)

# 2. Wrap .f with in_parallel():
mtcars |> map_dbl(in_parallel(\(x) mean(x)))

# Note that functions from packages should be fully qualified with `pkg::`
# or call `library(pkg)` within the function
1:10 |>
  map(in_parallel(\(x) vctrs::vec_init(integer(), x))) |>
  map_int(in_parallel(\(x) { library(vctrs); vec_size(x) }))

# A locally-defined function (or any required variables)
# should be passed via ... of in_parallel():
slow_lm <- function(formula, data) {
  Sys.sleep(0.5)
  lm(formula, data)
}

mtcars |>
  split(mtcars$cyl) |>
  map(in_parallel(\(df) slow_lm(mpg ~ disp, data = df), slow_lm = slow_lm))

# Tear down daemons when no longer in use:
mirai::daemons(0)
}