lapply Function in R with Examples

In this tutorial, we will discuss about lapply() function in R with some examples. lapply() function is available in base R package.

lapply() function in R

The lapply() function is the most popular function in R. The lapply() function takes a vector, list or data frame, a function (built-in or user-defined) as inputs and additional optional argument to the function. The lapply() function is similar to sapply() function, but it returns the output as list (lapply stands for list apply).

The general syntax of lapply() function is

lapply(X, FUN, ...)
  • X: an vector or list or data frame.
  • FUN: the function to be applied.
  • ...: optional argument to FUN.

The lapply(X,FUN,...) function apply the FUN to elements in a list or a vector or a data frame and returns a list of the same length as X.

The lapply() function can be used on objects like vectors, lists or data frame. The output of lapply() function is a list.

lapply() Function on vector

Example 1: lapply() function on vector

Compute natural logarithm of elements of vector x =10,25,30.

# Define vector x
x <- c(10,25,30)
# compute natural logarithm of each element of x
[1] 2.302585

[1] 3.218876

[1] 3.401197

Example 2: lapply() function on vector

Suppose we have a character vector of names as Name =(john","gloria","larry","rajan").

# Define character vector Name
Name <- c("john","gloria","rajan","mary","sonam")
# convert Names to upper case 
[1] "JOHN"

[1] "GLORIA"

[1] "RAJAN"

[1] "MARY"

[1] "SONAM"

Note that we can also use log function as log(x) on numeric vector to get a vector and toupper function as toupper(Name) on character vector Name to get the character vector. The lapply() function create the output as list.

lapply() Function on List

In order to use lapply() function, let us create a list as follows:

P <- c(10,12,28)
Q <- 1:5
R <- 11:15
myList <- list(P, Data = data.frame(Q,R))
[1] 10 12 28

  Q  R
1 1 11
2 2 12
3 3 13
4 4 14
5 5 15

Example 3: lapply() Function on List

Apply sum function on the components of list using lapply() function to get the sum of the elements of each component of list.

## apply the sum function on myList
[1] 50

[1] 80

Example 4: lapply() Function on List

When we use a square root function in lapply() function, it applies the square root function on each element of each component of a list and return the result as another list.

# apply sqrt function on myList
[1] 3.162278 3.464102 5.291503

         Q        R
1 1.000000 3.316625
2 1.414214 3.464102
3 1.732051 3.605551
4 2.000000 3.741657
5 2.236068 3.872983

lapply Function on Data Frame

Let us create a sample data frame to understand the use of lapply() function on data frame.

Name <- c("john","gloria","rajan","mary","sonam")
Gender <- factor(c("M","F","M","F","F"))
Height <- c(165,158,160,157,155)
Weight <- c(72,65,69,58,49)
df <-data.frame(Name,Gender,Height,Weight)
    Name Gender Height Weight
1   john      M    165     72
2 gloria      F    158     65
3  rajan      M    160     69
4   mary      F    157     58
5  sonam      F    155     49

Example 5: lapply() Function on Data Frame

Suppose we want to check the class of all columns of a data frame. Using lapply() function on data frame and specifying function as class to get the class of each column of a data frame.

[1] "character"

[1] "factor"

[1] "numeric"

[1] "numeric"

Example 6: lapply() Function on Data Frame

Suppose we want to calculate standard error of some columns of given data frame. First define a user-defined function for standard error as follows:

std.error <- function(x) {
  sd(x) / sqrt(length(x))

Using lapply() function on $3^{rd}$ and $4^{th}$ column of data frame df we can calculate standard error for the selected columns and get the result in list format.

# compute the standard error of  3:4 columns of df
[1] 1.702939

[1] 4.130375

Example 7: lapply() Function on Data Frame

Suppose we want to calculate quantile of $3^{rd}$ and $4^{th}$ column of data frame df.

Using lapply() function on $3^{rd}$ and $4^{th}$ column of data frame df we can calculate quantiles for the selected columns and get the result in list format.

# compute the standard error of  2:3 columns of df
25% 50% 75% 
157 158 160 

25% 50% 75% 
 58  65  69 

Note that as explained in the syntax of lapply() function, we can use optional argument ... to the function in lapply() function, like probs=c() for the quantile() function.


In this tutorial you learned about lapply() function in R and how to use lapply() function on vector,list and data frame with illustration.

Learn more about functions in R, refer to the following tutorials:

Hopefully you enjoyed learning this tutorial on lapply() function in R. Hope the content is more than sufficient to understand lapply() function in R.

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