This tutorial explains the differences between the built-in R functions **apply()**, **sapply()**, **lapply()**, and **tapply()** along with examples of when and how to use each function.

**apply()**

Use the **apply()** function when you want to apply a function to the rows or columns of a matrix or data frame.

The basic syntax for the apply() function is as follows:

**apply(X, MARGIN, FUN)**

- X is the name of the matrix or data frame
- MARGIN indicates which dimension to perform an operation across (1 = row, 2 = column)
- FUN is the specific operation you want to perform (e.g. min, max, sum, mean, etc.)

The following code illustrates several examples of **apply()** in action.

#create a data frame with three columns and five rows data <- data.frame(a = c(1, 3, 7, 12, 9), b = c(4, 4, 6, 7, 8), c = c(14, 15, 11, 10, 6)) data # a b c #1 1 4 14 #2 3 4 15 #3 7 6 11 #4 12 7 10 #5 9 8 6 #find the sum of each row apply(data, 1, sum) #[1] 19 22 24 29 23 #find the sum of each column apply(data, 2, sum) # a b c #32 29 56 #find the mean of each row apply(data, 1, mean) #[1] 6.333333 7.333333 8.000000 9.666667 7.666667 #find the mean of each column, rounded to one decimal place round(apply(data, 2, mean), 1) # a b c #6.4 5.8 11.2 #find the standard deviation of each row apply(data, 1, sd) #[1] 6.806859 6.658328 2.645751 2.516611 1.527525 #find the standard deviation of each column apply(data, 2, sd) # a b c #4.449719 1.788854 3.563706

**lapply()**

Use the** lapply()** function when you want to apply a function to each element of a list, vector, or data frame and obtain a list as a result.

The basic syntax for the lapply() function is as follows:

**lapply(X, FUN)**

- X is the name of the list, vector, or data frame
- FUN is the specific operation you want to perform

The following code illustrates several examples of using **lapply()** on the columns of a data frame.

#create a data frame with three columns and five rows data <- data.frame(a = c(1, 3, 7, 12, 9), b = c(4, 4, 6, 7, 8), c = c(14, 15, 11, 10, 6)) data # a b c #1 1 4 14 #2 3 4 15 #3 7 6 11 #4 12 7 10 #5 9 8 6 #find mean of each column and return results as a list lapply(data, mean) # $a # [1] 6.4 # # $b # [1] 5.8 # # $c # [1] 11.2 #multiply values in each column by 2 and return results as a list lapply(data, function(data) data*2) # $a # [1] 2 6 14 24 18 # # $b # [1] 8 8 12 14 16 # # $c # [1] 28 30 22 20 12

We can also use **lapply()** to perform operations on lists. The following examples show how to do so.

#create a list x <- list(a=1, b=1:5, c=1:10) x # $a # [1] 1 # # $b # [1] 1 2 3 4 5 # # $c # [1] 1 2 3 4 5 6 7 8 9 10 #find the sum of each element in the list lapply(x, sum) # $a # [1] 1 # # $b # [1] 15 # # $c # [1] 55 #find the mean of each element in the list lapply(x, mean) # $a # [1] 1 # # $b # [1] 3 # # $c # [1] 5.5 #multiply values of each element by 5 and return results as a list lapply(x, function(x) x*5) # $a # [1] 5 # # $b # [1] 5 10 15 20 25 # # $c # [1] 5 10 15 20 25 30 35 40 45 50

**sapply()**

Use the** sapply()** function when you want to apply a function to each element of a list, vector, or data frame and obtain a **vector** instead of a list as a result.

The basic syntax for the sapply() function is as follows:

**sapply(X, FUN)**

- X is the name of the list, vector, or data frame
- FUN is the specific operation you want to perform

The following code illustrates several examples of using **sapply()** on the columns of a data frame.

#create a data frame with three columns and five rows data <- data.frame(a = c(1, 3, 7, 12, 9), b = c(4, 4, 6, 7, 8), c = c(14, 15, 11, 10, 6)) data # a b c #1 1 4 14 #2 3 4 15 #3 7 6 11 #4 12 7 10 #5 9 8 6 #find mean of each column and return results as a vector sapply(data, mean) # a b c #6.4 5.8 11.2 #multiply values in each column by 2 and return results as a matrix sapply(data, function(data) data*2) # a b c #[1,] 2 8 28 #[2,] 6 8 30 #[3,] 14 12 22 #[4,] 24 14 20 #[5,] 18 16 12

We can also use **sapply()** to perform operations on lists. The following examples show how to do so.

#create a list x <- list(a=1, b=1:5, c=1:10) x # $a # [1] 1 # # $b # [1] 1 2 3 4 5 # # $c # [1] 1 2 3 4 5 6 7 8 9 10 #find the sum of each element in the list sapply(x, sum) # a b c # 1 15 55 #find the mean of each element in the list sapply(x, mean) # a b c #1.0 3.0 5.5

**tapply()**

Use the** tapply()** function when you want to apply a function to subsets of a vector and the subsets are defined by some other vector, usually a factor.

The basic syntax for the tapply() function is as follows:

**tapply(X, INDEX, FUN)**

- X is the name of the object, typically a vector
- INDEX is a list of one or more factors
- FUN is the specific operation you want to perform

The following code illustrates an example of using **tapply()** on the built-in R dataset **iris .**

#view first six lines ofirisdataset head(iris) # Sepal.Length Sepal.Width Petal.Length Petal.Width Species #1 5.1 3.5 1.4 0.2 setosa #2 4.9 3.0 1.4 0.2 setosa #3 4.7 3.2 1.3 0.2 setosa #4 4.6 3.1 1.5 0.2 setosa #5 5.0 3.6 1.4 0.2 setosa #6 5.4 3.9 1.7 0.4 setosa #find the max Sepal.Length of each of the three Species tapply(iris$Sepal.Length, iris$Species, max) #setosa versicolor virginica # 5.8 7.0 7.9 #find the mean Sepal.Width of each of the three Species tapply(iris$Sepal.Width, iris$Species, mean) # setosa versicolor virginica # 3.428 2.770 2.974 #find the minimum Petal.Width of each of the three Species tapply(iris$Petal.Width, iris$Species, min) # setosa versicolor virginica # 0.1 1.0 1.4