SESSION 20

In R, apply functions are used to perform operations on arrays, lists, data frames, and other data structures. These functions allow you to avoid writing explicit loops, making your code more efficient and concise. Below is a detailed breakdown of the most common apply functions: apply(), lapply(), sapply(), tapply(), and mapply().

1. apply()

The apply() function is used to apply a function to the rows or columns of a matrix or data frame. You specify the data structure, the margin (1 for rows, 2 for columns), and the function to apply.

Syntax:

R

apply(X, MARGIN, FUN, ...)

• X: The matrix or data frame.

• MARGIN: The margin to apply the function over. 1 for rows, 2 for columns.

• FUN: The function to apply.

• ...: Additional arguments passed to FUN.

Example: Apply Function to Matrix Rows and Columns

R

# Create a matrix

mat <- matrix(1:9, nrow = 3, byrow = TRUE)

# Apply sum function over rows (MARGIN = 1)

apply(mat, 1, sum)  # Sum of rows

Output:

csharp

[1]  6 15 24

R

# Apply sum function over columns (MARGIN = 2)

apply(mat, 2, sum)  # Sum of columns

Output:

csharp

[1] 12 15 18

Here, apply() is used to calculate the sum of each row and column of the matrix mat.

2. lapply()

The lapply() function is used to apply a function to each element of a list and returns a list. It is generally used for list-like objects.

Syntax:

R

lapply(X, FUN, ...)

• X: The list (or other data structure).

• FUN: The function to apply.

• ...: Additional arguments passed to FUN.

Example: Apply Function to List Elements

R

# Create a list

my_list <- list(a = 1:3, b = 4:6, c = 7:9)

# Apply sum function to each element of the list

lapply(my_list, sum)

Output:

css

$a

[1] 6

$b

[1] 15

$c

[1] 24

In this example, lapply() applies the sum() function to each element of my_list.

3. sapply()

The sapply() function is similar to lapply(), but it tries to simplify the result. If the result can be simplified into a vector or matrix, sapply() will return that, instead of a list.

Syntax:

R

sapply(X, FUN, ...)

• X: The list (or other data structure).

• FUN: The function to apply.

• ...: Additional arguments passed to FUN.

Example: Simplify Result of Applying Function

R

# Create a list

my_list <- list(a = 1:3, b = 4:6, c = 7:9)

# Apply sum function and simplify the result into a vector

sapply(my_list, sum)

Output:

css

a  b  c 

 6 15 24 

Here, sapply() simplifies the result of lapply() into a numeric vector.

4. tapply()

The tapply() function applies a function to subsets of a vector based on a factor (or grouping variable). It is particularly useful when you want to perform group-wise operations.

Syntax:

R

tapply(X, INDEX, FUN, ...)

• X: The vector to apply the function to.

• INDEX: A factor or list of factors that define the groups.

• FUN: The function to apply.

• ...: Additional arguments passed to FUN.

Example: Group-wise Operations with tapply()

R

# Create a vector and a factor for grouping

x <- c(10, 20, 30, 40, 50, 60)

groups <- factor(c("A", "A", "B", "B", "C", "C"))

# Apply sum function to subsets of x based on the grouping factor

tapply(x, groups, sum)

Output:

css

A  B  C 

30 70 110 

Here, tapply() calculates the sum of x for each group in the factor groups.

5. mapply()

The mapply() function is an apply function that applies a function to multiple arguments in parallel. It is a multivariate version of sapply() and allows you to pass multiple arguments.

Syntax:

R

mapply(FUN, ..., MoreArgs = NULL, SIMPLIFY = TRUE, USE.NAMES = TRUE)

• FUN: The function to apply.

• ...: Arguments to FUN.

• MoreArgs: Additional arguments passed to FUN.

• SIMPLIFY: Logical. If TRUE, the result will be simplified (e.g., into a vector or matrix).

• USE.NAMES: Logical. If TRUE, names of the results are generated based on the input arguments.

Example: Apply Function to Multiple Arguments

R

# Function to add two numbers

add <- function(x, y) {

  return(x + y)

}

# Use mapply to apply the add function to multiple pairs of numbers

mapply(add, c(1, 2, 3), c(4, 5, 6))

Output:

csharp

[1] 5 7 9

In this example, mapply() applies the add() function to multiple pairs of numbers, returning a vector of sums.

Practical Example Comparing All Functions

Let’s say we have a list of numbers, and we want to calculate their squares.

# Create a list

numbers <- list(a = 1:3, b = 4:6, c = 7:9)

# Using apply() on a matrix

mat <- matrix(1:9, nrow=3)

apply(mat, 2, sum)  # Sum of columns

# Using lapply() to square each list element

lapply(numbers, function(x) x^2)

# Using sapply() to square each list element and simplify

sapply(numbers, function(x) x^2)

# Using tapply() to group and calculate squares (example with factor)

group <- factor(c("X", "X", "Y", "Y", "Z", "Z"))

tapply(c(1, 2, 3, 4, 5, 6), group, sum)

# Using mapply() to square corresponding elements from two vectors

mapply(function(x, y) x + y, 1:3, 4:6)

This practical example shows how each function can be used in different contexts, giving you more flexibility in data manipulation tasks.