map {purrr}R Documentation

Apply a function to each element of a list or atomic 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.

Usage

map(.x, .f, ...)

map_lgl(.x, .f, ...)

map_chr(.x, .f, ...)

map_int(.x, .f, ...)

map_dbl(.x, .f, ...)

map_raw(.x, .f, ...)

map_dfr(.x, .f, ..., .id = NULL)

map_dfc(.x, .f, ...)

walk(.x, .f, ...)

Arguments

.x

A list or atomic vector.

.f

A function, formula, or vector (not necessarily atomic).

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. If a component is not present, the value of .default will be returned.

...

Additional arguments passed on to the mapped function.

.id

Either a string or NULL. If a string, the output will contain a variable with that name, storing either the name (if .x is named) or the index (if .x is unnamed) of the input. If NULL, the default, no variable will be created.

Only applies to ⁠_dfr⁠ variant.

Value

See Also

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

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

Examples

Run examples

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

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

# Or a formula
1:10 %>%
  map(~ 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(~ paste(.x, "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(.$cyl) %>%
  map(~ lm(mpg ~ wt, data = .x)) %>%
  map(summary) %>%
  map_dbl("r.squared")

# If each element of the output is a data frame, use
# map_dfr to row-bind them together:
mtcars %>%
  split(.$cyl) %>%
  map(~ lm(mpg ~ wt, data = .x)) %>%
  map_dfr(~ as.data.frame(t(as.matrix(coef(.)))))
# (if you also want to preserve the variable names see
# the broom package)

[Package purrr version 0.3.4 Index]