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 rowsdata <- 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 rowapply(data, 1, sum)#[1] 19 22 24 29 23#find the sum of each columnapply(data, 2, sum)# a b c #32 29 56 #find the mean of each rowapply(data, 1, mean)#[1] 6.333333 7.333333 8.000000 9.666667 7.666667#find the mean of each column, rounded to one decimal placeround(apply(data, 2, mean), 1)# a b c #6.4 5.8 11.2 #find the standard deviation of each rowapply(data, 1, sd)#[1] 6.806859 6.658328 2.645751 2.516611 1.527525#find the standard deviation of each columnapply(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 usinglapply()on the columns of a data frame.
#create a data frame with three columns and five rowsdata <- 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 listlapply(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 listlapply(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 listx <- 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 listlapply(x, sum)# $a# [1] 1## $b# [1] 15## $c# [1] 55#find the mean of each element in the listlapply(x, mean)# $a# [1] 1## $b# [1] 3## $c# [1] 5.5#multiply values of each element by 5 and return results as a listlapply(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 avector 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 usingsapply()on the columns of a data frame.
#create a data frame with three columns and five rowsdata <- 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 vectorsapply(data, mean)# a b c #6.4 5.8 11.2 #multiply values in each column by 2 and return results as a matrixsapply(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 listx <- list(a=1, b=1:5, c=1:10) x# $a# [1] 1## $b# [1] 1 2 3 4 5## $c# [1] 1 2 3 4 5 6 7 8 9 10#find the sum of each element in the listsapply(x, sum)# a b c # 1 15 55 #find the mean of each element in the listsapply(x, mean)# a b c #1.0 3.0 5.5
tapply()
Use the tapply() function when you want to apply a function tosubsetsof a vector and the subsets are defined by some other vector, usually a factor.
The basic syntax for the tapply() function is as follows:
tapply(X, INDEX, FUN)
- X is the name of the object, typically a vector
- INDEX is a list of one or more factors
- FUN is the specific operation you want to perform
The following code illustrates an example of usingtapply()on the built-in R dataset iris.
#view first six lines of iris datasethead(iris)# Sepal.Length Sepal.Width Petal.Length Petal.Width Species#1 5.1 3.5 1.4 0.2 setosa#2 4.9 3.0 1.4 0.2 setosa#3 4.7 3.2 1.3 0.2 setosa#4 4.6 3.1 1.5 0.2 setosa#5 5.0 3.6 1.4 0.2 setosa#6 5.4 3.9 1.7 0.4 setosa#find the max Sepal.Length of each of the three Speciestapply(iris$Sepal.Length, iris$Species, max)#setosa versicolor virginica # 5.8 7.0 7.9 #find the mean Sepal.Width of each of the three Speciestapply(iris$Sepal.Width, iris$Species, mean)# setosa versicolor virginica # 3.428 2.770 2.974#find the minimum Petal.Width of each of the three Speciestapply(iris$Petal.Width, iris$Species, min)# setosa versicolor virginica # 0.1 1.0 1.4
