How to Append an Element to a List at Any Position in R

List in R is a data structure that can hold multiple types of elements. You can expand or shrink the list based on your requirements.

To grow the list, you can add an element (numeric value, character vectors, other lists, data frames, or functions) at whichever position you like.

Here are five ways to add an element to a list at any position:

1. Using append()
2. Using c()
3. Using the rlist library
4. Using $ operator
5. Using the double bracket [[

Method 1: Using append()

If you are picky about which position you want to add an element, append() is the method for you. It lets you add an element at the end of the list but provides an argument “after” through which you can add an element anywhere.

It is like magic wand in your hand that lets you place your new element exactly where you want it in the list.

Example 1: Adding an element at the end of the list

As you can see in this figure, we added an element (4) at the end of the list.

list1 <- list(a = 1, b = 2, c = 3)
list2 <- list(d = 4)

appended_list <- append(list1, list2)
print(appended_list)

Output

$a
[1] 1

$b
[1] 2

$c
[1] 3

$d
[1] 4

Example 2: Appending an element at the specific position

Here, we added an element (4) after the position 1 using the “after” parameter.

list1 <- list(1, 2, 3)

list2 <- append(list1, 4, after = 1)

print(list2)

Output

[[1]]
[1] 1

[[2]]
[1] 2

[[3]]
[1] 4

[[4]]
[1] 3

With after = 1, you are explicitly telling R to put the new element right after the first item.

Example 3: Appending multiple elements

The above figure shows that we added 3 elements (4, 5, 6) at the end of the list.

list1 <- list(1, 2, 3)
elements <- c(4, 5, 6)

multi_list <- append(list1, elements)

print(multi_list)

Output

[[1]]
[1] 1

[[2]]
[1] 2

[[3]]
[1] 3

[[4]]
[1] 4

[[5]]
[1] 5

[[6]]
[1] 6

Method 2: Using c()

To simultaneously add single or multiple elements to a list, use the c() function. This approach is straightforward but not the most efficient for large lists due to R’s copy-on-modify semantics.

The above figure shows that we appended element 4 at the end of the position.

list1 <- list(1, 2, 3)

list1 <- c(list1, 4)

print(list1)

Output

[[1]]
[1] 1

[[2]]
[1] 2

[[3]]
[1] 3

[[4]]
[1] 4

Method 3: Using the ‘rlist’ library

The above figure shows that we used the rlist library’s list.append() function to add an element (4) at the end of the list highlighted by the red marker.

For this practical, you need to install the “rlist” library. Use the below command to install it.

install.packages("rlist")

library("rlist")

list1 <- list(a = 1, b = 2, c = 3)

new_list <- list.append(list1, d = 4)

print(new_list)

Output

$a
[1] 1

$b
[1] 2

$c
[1] 3

$d
[1] 4

Method 4: Using $ operator

The $ operator is not typically used for adding new elements but can be used for modification. However, if the name provided after the $ does not exist in the list, it will add a new element with that name.

Example 1: Adding a new element

list1 <- list(a = 1, b = 2, c = 3)

list1$d <- 4

list1

Output

$a
[1] 1

$b
[1] 2

$c
[1] 3

$d
[1] 4

This approach is still unsuitable for adding new elements instead, you can use the $ operator to modify existing list elements.

Example 2: Modifying an existing element

In the above figure, we modified a list by updating element “b” to 21.

list1 <- list(a = 1, b = 2, c = 3)

list1$b <- 21

cat("After modifying the list", "\n")

print(list1)

Output

After modifying the list

$a
[1] 1

$b
[1] 21

$c
[1] 3

Method 5: Using the double bracket [[

The double bracket ([[) approach is more direct than the c() function and avoids some copying overhead, which is especially helpful in any type of loop.

Example

list1 <- list(1, 2, 3)

list1[[length(list1) + 1]] <- 4

cat("After adding an element the list", "\n")

print(list1)

Output

After adding an element the list

[[1]]
[1] 1

[[2]]
[1] 2

[[3]]
[1] 3

[[4]]
[1] 4

The output shows that the element “4” is added at the end of the list.

Krunal Lathiya

Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.