Chapter 12 Loops

Loops are another type of control flow structure. They dictate how many times a series of commands should be run. There are two type of loops, a while loop and a for loop. These two loops operate similarly and are found in other programming languages such as C and Python.

12.1 While Loop

A while loop is used when you want to perform a task indefinitely, until a particular condition is met. It’s a condition-controlled loop.

The loop will continue until the condition is FALSE.

x = 5

# If statement is true, keep running the loop 
while (x != 0 ) {
  print(x)
  x = x - 1
}

## [1] 5
## [1] 4
## [1] 3
## [1] 2
## [1] 1

If the condition is false at the start, the while loop will never be executed at all.

x = 0

# If statement starts as TRUE,  the loop will never run 
while (x != 0 ) {
  print(x)
  x = x - 1
}

12.2 For Loops

The for statement in R is a bit different from what you usually use in other programming languages. Rather than iterating over a numeric progression, R’s for statement iterates over the items of a vector or a list. The items are iterated in the order that they appear in the vector.

# Iterate through a vector
colors <- c("red","green","blue","yellow")

for (x in colors) {
  print(x)
}

## [1] "red"
## [1] "green"
## [1] "blue"
## [1] "yellow"

lst <- list(3.14, "Hi", c(1,2,3))

for (i in lst) {
  print(i)
}

## [1] 3.14
## [1] "Hi"
## [1] 1 2 3

If you need to execute a group of statements for a specified number of times, use sequence operator : or built-in function seq().

# Print 'Hello!' 3 times
for (x in 1:3) {
  print("Hello!")
}

## [1] "Hello!"
## [1] "Hello!"
## [1] "Hello!"

for (x in seq(from=2,to=8,by=2)) {
  print(x^2)
}

## [1] 4
## [1] 16
## [1] 36
## [1] 64

12.3 Break

The break statement is used to exit the loop immediately. It simply jumps out of the loop altogether, and the program continues after the loop.

x <- 5

# If statement starts as TRUE,  the loop will never run 
while (x != 0 ) {
  print(x)
  x = x - 1
  
  if(x == 2){
    print("Entered IF statement, stop loop")
    break 
  }
  
}

## [1] 5
## [1] 4
## [1] 3
## [1] "Entered IF statement, stop loop"

If not given an adequate stopping criteria or break statement the loop will continue forever. For example, if we started the above examples at x = -2. The break statement is particularly important for the while loop.

The break statement can also be used in a for loop. It simply jumps out of the loop altogether, and the program continues after the loop.

colors <- c("red","green","blue","yellow")
for (x in colors) {
  if (x == "blue"){
       break 
  }
  print(x)
}

## [1] "red"
## [1] "green"

The for loops do not have the same risk of “running forever”, like while loops have.

12.4 Next

We can also use the next command in both for loops and while loops in order to skip executing a command.

for(i in 1:10){
  
  i <- i^2
  
  if(i <5){
    next
  }
  
  print(i)
}

## [1] 9
## [1] 16
## [1] 25
## [1] 36
## [1] 49
## [1] 64
## [1] 81
## [1] 100

The code inside the loop will run until it reaches the next statement. Once

12.5 Nested Loops

We can also create loops within loops. We refer to creating loops within other loops as a nested loop.

for(i in 1:10){
  for(j in 1:3){
    statement = paste("i=", i, ", j=", j)
    print(statement)
  }
}

## [1] "i= 1 , j= 1"
## [1] "i= 1 , j= 2"
## [1] "i= 1 , j= 3"
## [1] "i= 2 , j= 1"
## [1] "i= 2 , j= 2"
## [1] "i= 2 , j= 3"
## [1] "i= 3 , j= 1"
## [1] "i= 3 , j= 2"
## [1] "i= 3 , j= 3"
## [1] "i= 4 , j= 1"
## [1] "i= 4 , j= 2"
## [1] "i= 4 , j= 3"
## [1] "i= 5 , j= 1"
## [1] "i= 5 , j= 2"
## [1] "i= 5 , j= 3"
## [1] "i= 6 , j= 1"
## [1] "i= 6 , j= 2"
## [1] "i= 6 , j= 3"
## [1] "i= 7 , j= 1"
## [1] "i= 7 , j= 2"
## [1] "i= 7 , j= 3"
## [1] "i= 8 , j= 1"
## [1] "i= 8 , j= 2"
## [1] "i= 8 , j= 3"
## [1] "i= 9 , j= 1"
## [1] "i= 9 , j= 2"
## [1] "i= 9 , j= 3"
## [1] "i= 10 , j= 1"
## [1] "i= 10 , j= 2"
## [1] "i= 10 , j= 3"

Here is an example of a nested loop which changes the elements of matrix to be the product of the row and column location.

my_matrix <- matrix(NA, nrow = 5, ncol = 5)

for(i in 1:nrow(my_matrix)){
  for(j in 1:nrow(my_matrix)){
    my_matrix[i,j] = i*j
  }
}

my_matrix

##      [,1] [,2] [,3] [,4] [,5]
## [1,]    1    2    3    4    5
## [2,]    2    4    6    8   10
## [3,]    3    6    9   12   15
## [4,]    4    8   12   16   20
## [5,]    5   10   15   20   25

12.6 Examples

A few more examples.

12.6.1 Example 1

Below we create a function that has only one argument, vec, an arbitrary numeric vector. This function create a new vector containing all elements in vec whole numbers, and returns this new vector. If there are no whole numbers in vec, then it returns NA.

# Create a subset of x which only contains whole numbers
# ARGUMENTS: vec, a numeric vector 
# RETURNS: whole_vec, a vector containing all whole numbers
#                   will equal NA if there are no whole numbers
whole_num <- function(vec){
  
  # Initialize whole_vec
  whole_vec <-NULL
  
  # For loop, go through each element in vec 
  for(i in vec){
    if( i == round(i)){
      whole_vec <- c(whole_vec, i)
    } 
  }
  
  # Check to make sure there was at least one whole number
  if(length(whole_vec)==0){
    whole_vec = NA
  }
  
  return(whole_vec)
}


# Test case 
tester <- c(1, 3, 5.5, 10.8, pi, 62)
whole_num(tester)  # Should return 1, 3, 62

## [1]  1  3 62

12.6.2 Example 2

Below we create a function that has only one argument, bound, a numeric object of length one. This function returns the minimum number of subsequent whole numbers (starting from 1) that must be added together in order to reach (or surpass) bound. For example, suppose bound=16. Then 1+2+3+4+5 = 15, and 1+2+3+4+5+6 = 21. Thus, the function would return 6.

get_num <- function(bound = 16){
  
  # Initialize values
  total <- 0 
  i <- 0
  
  # Use while loop to reach bound 
  while(total <= bound){
    i <- i + 1
    total <- total + i 
  }
  return(i)
}

get_num(15)

## [1] 6

STAT 107 Outline of Class Notes