list()

Updated March 13, 2026 · Data Types

list data-types r collections

Lists are the most flexible data structure in R. Unlike vectors, which must contain elements of the same type, lists can hold objects of different types, different lengths, and even other lists or functions. This makes lists ideal for storing complex, hierarchical data and returning multiple values from functions.

Creating Lists

Create a list using the list() function:

# A simple list with different types
my_list <- list(
  name = "Alice",
  age = 30,
  scores = c(85, 92, 78),
  active = TRUE
)

# Accessing elements
my_list[[1]]        # "Alice" (by index)
my_list$name       # "Alice" (by name)
my_list[["age"]]   # 30 (by name with brackets)

List Structure and Inspection

Lists have a recursive nature — they can contain other lists:

# Nested list
nested <- list(
  a = 1:3,
  b = list(
    c = c("x", "y"),
    d = matrix(1:4, nrow = 2)
  )
)

# Check structure
str(nested)
# List of 2
#  $ a: int [1:3] 1 2 3
#  $ b:List of 2
#   ..$ c: chr [1:2] "x" "y"
#   ..$ d: int [1:2, 1:2] 1 2 3 4

Accessing and Modifying Elements

Use [[]] for single elements and [] for sub-lists:

x <- list(a = 1, b = 2, c = 3)

# Double brackets return the element itself
x[["a"]]        # 1 (numeric)
x[[1]]          # 1 (same thing)

# Single brackets return a sub-list
x["a"]          # List of 1

# Adding new elements
x$d <- 4
x[["e"]] <- 5

# Removing elements
x[["b"]] <- NULL

Converting Between Lists and Vectors

Use unlist() to flatten a list into a vector:

my_list <- list(a = c(1, 2), b = c(3, 4))
unlisted <- unlist(my_list)
unlisted
# a1 a2 b1 b2 
#  1  2  3  4

Convert a vector to a list with as.list():

vec <- 1:3
as.list(vec)
# [[1]]
# [1] 1
# [[2]]
# [1] 2
# [[3]]
# [1] 3

Applying Functions to Lists

The lapply() function applies a function to each element, returning a list:

my_list <- list(a = 1:3, b = 4:6, c = 7:9)

lapply(my_list, sum)
# $a
# [1] 6
# $b
# [1] 15
# $c
# [1] 24

# sapply simplifies the result to a vector
sapply(my_list, sum)
#   a   b   c 
#   6  15  24

For more complex iteration, see the purrr functions reference.

Common Patterns

Returning Multiple Values from a Function

Lists are the standard way to return multiple objects:

calculate_stats <- function(x) {
  list(
    mean = mean(x),
    median = median(x),
    sd = sd(x),
    n = length(x)
  )
}

result <- calculate_stats(c(1, 2, 3, 4, 5))
result$mean      # 3
result$median    # 3

Storing Heterogeneous Data

Lists excel when you need to combine different data types:

person <- list(
  name = "Bob",
  age = 28,
  skills = c("R", "Python", "SQL"),
  contact = list(
    email = "bob@example.com",
    phone = "555-0123"
  )
)