Using the apply functions in R

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One of the core functionalities of R is the apply family of functions, which are designed to simplify the manipulation of data in R. The apply functions allow us to perform a single operation over multiple elements of an array or data frame, and return the result in a specific format. In this blog post, we will explore the different apply functions in R and their use cases and examples.

1. lapply

lapply() stands for “list apply” and is used to apply a function to each element of a list and return a list. The syntax for lapply is as follows:

lapply(X, FUN, ...)

where X is the list on which the function will be applied, and FUN is the function that will be applied to each element of the list. The output will be a list with the same length as the input list.

Example: Suppose we have a list of numbers and we want to calculate their squares using the lapply function. Here is how we can do it:

> my_list <- list(1, 2, 3, 4, 5)
> squared_list <- lapply(my_list, function(x) x^2)
> squared_list
[[1]]
[1] 1

[[2]]
[1] 4

[[3]]
[1] 9

[[4]]
[1] 16

[[5]]
[1] 25

2. sapply

sapply() is similar to lapply(), but it simplifies the output to the most appropriate data type. The syntax for sapply is as follows:

sapply(X, FUN, …)

where X is the list on which the function will be applied, and FUN is the function that will be applied to each element of the list. The output will be a vector or matrix, depending on the input and output of the function.

Example: Suppose we have a list of numbers and we want to calculate their squares using the sapply function. Here is how we can do it:

> my_list <- list(1, 2, 3, 4, 5)
> squared_list <- sapply(my_list, function(x) x^2)
> squared_list
[1]  1  4  9 16 25

3. vapply

vapply() is similar to sapply(), but it allows you to specify the output data type explicitly. The syntax for vapply is as follows:

vapply(X, FUN, FUN.VALUE, ...)

where X is the list on which the function will be applied, FUN is the function that will be applied to each element of the list, and FUN.VALUE is the output data type that the function should return. The output will be a vector or matrix of the specified data type.

Example: Suppose we have a list of numbers and we want to calculate their squares using the vapply function, and we want the output to be of type numeric. Here is how we can do it:

> my_list <- list(1, 2, 3, 4, 5)
> squared_list <- vapply(my_list, function(x) x^2, FUN.VALUE = numeric(1))
> squared_list
[1]  1  4  9 16 25

4. tapply

Example: Suppose we have a data frame that contains information on students in a school, including their grades and the subject they took the exam in.

     name subject grade
1   Alice    Math    90
2     Bob English    80
3 Charlie    Math    95
4   David Science    85
5     Eve English    75

We can use tapply() to calculate the mean grade for each subject:

> tapply(students$grade, students$subject, mean)
English    Math Science 
   77.5    92.5    85.0 

5. mapply

The mapply() function applies a function to multiple lists in parallel. The function takes the first element from each list and applies the function to them, then it takes the second element from each list and so on until it reaches the end of the shortest list.

Example: Here’s an example of how mapply() works:

a <- c(1, 2, 3)
b <- c(4, 5, 6)
c <- c(7, 8, 9)

mapply(function(x, y, z) x * y + z, a, b, c)

[1] 11 18 27

In this example, the function takes three arguments: x, y, and z. The mapply() function applies the function to the first elements of a, b, and c, so x = 1, y = 4, and z = 7. The result of the function is 11. Then it applies the function to the second elements of a, b, and c, so x = 2, y = 5, and z = 8. The result of the function is 18. Finally, it applies the function to the third elements of a, b, and c, so x = 3, y = 6, and z = 9. The result of the function is 27.

Happy l-s-t-v-m-applying!!!