Module 3
Conditional Statements and Loops
Control structures in R are used to control the flow of execution of various R expressions. They require the programmer to specify one or more conditions to be evaluated or tested by the program, along with a statement or statements to be executed if the condition is determined to be TRUE, and optionally, other statements to be executed if the condition is determined to be FALSE. In other words, control structures allow you to respond to inputs or to features of the data and execute different R expressions accordingly.
In this module we will discuss several commonly used control structures such as if-else statements, for and while loops, as well as break and next commands. Before we move on to these topics, first let’s discuss some relational and logical operators.
Relational and Logical Operations
Comparison Operators
The basic relational operators are called comparison operators and are listed in the table below:
| Operator | Name | Example |
|---|---|---|
| == | Equal | x == y |
| != | Not equal | x != y |
| > | Greater than | x > y |
| < | Less than | x < y |
| >= | Greater than or equal to | x >= y |
| <= | Less than or equal to | x <= y |
The possible outputs of these operations are either TRUE or FALSE. Here are some examples with these comparison operators:
print (5 == 5)
#> [1] TRUE
print(5 == 7)
#> [1] FALSE
print(5 != 5)
#> [1] FALSE
print(5 != 10)
#> [1] TRUE
print(5 < 2)
#> [1] FALSE
print(5 <= 4)
#> [1] FALSEWhen applied to vectors, these operators do element-wise comparisons (the first element of the first vector is compared to the first element of the second vector and so on). Suppose we have the following two vectors:
Then,
Logical Operators
Logical operators are used to combine conditional statements:
| Operator | Description |
|---|---|
| & | Element-wise Logical AND operator. It returns TRUE if both elements are TRUE |
| \(|\) | Element-wise Logical OR operator. It returns TRUE if one of the statement is TRUE |
| ! | Logical NOT - returns FALSE if statement is TRUE |
Here are some examples:
## & Operator
print(TRUE & TRUE)
#> [1] TRUE
print (TRUE & FALSE)
#> [1] FALSE
print(FALSE & FALSE)
#> [1] FALSE
print (5 == 5 & 10 < 6)
#> [1] FALSE
print(4!= 3 & 2 < 9)
#> [1] TRUE
print(x == y & x < y)
#> [1] FALSE FALSE FALSE FALSE
## | Operator
print(TRUE | TRUE)
#> [1] TRUE
print (TRUE | FALSE)
#> [1] TRUE
print(FALSE | FALSE)
#> [1] FALSE
print (5 == 5 | 10 < 6)
#> [1] TRUE
print(4!= 3 | 2 < 9)
#> [1] TRUE
print(x == y | x < y)
#> [1] TRUE TRUE TRUE FALSE
## ! Operator
print (!TRUE)
#> [1] FALSE
print(!FALSE)
#> [1] TRUE
print(!(4<2))
#> [1] TRUE
print(!(2 == 2 & 3 < 4))
#> [1] FALSEConditional Statements
IF Statement
An “if statement” is written with the if keyword, and it is used to specify a block of code to be executed if a condition is TRUE:
if (5 > 2) {
print("5 is greater than 2")
}
#> [1] "5 is greater than 2"No code will be executed if the conditional statement inside the parentheses is FALSE. Check it yourself:
if (5 < 2) {
print("5 is greater than 2")
}IF - ELSE Statement
The if-else combination is probably the most commonly used control structure in R. This structure allows you to test a condition and act on it depending on whether it’s TRUE or FALSE. If the condition is TRUE, then the code given in curly brackets after the if clause will be executed. If it is FALSE, then the code in curly brackets after the else clause will be executed:
a <- 5 ; b <- 2
if (b > a) {
print ("b is greater than a")
} else {
print("b is not greater than a")
}
#> [1] "b is not greater than a"Now try this example:
a <- 2 ; b <- 5
if (b > a) {
print ("b is greater than a")
} else {
print("b is not greater than a")
}
#> [1] "b is greater than a"You can pass as many conditions as you would like to by adding else if clause:
if (b > a) {
print ("b is greater than a")
} else if (a == b) {
print ("a and b are equal")
} else {
print ("a is greater than b")
}
#> [1] "b is greater than a"Try again with different values:
Nested IF-ELSE Statements
You can also have if statements inside if statements, this is called nested if statements.
x <- 50
if (x > 10) {
print("Above ten")
if (x > 20) {
print("and also above 20!")
} else {
print("but not above 20.")
}
} else {
print("below 10.")
}
#> [1] "Above ten"
#> [1] "and also above 20!"Now try it with x = 15 and x = 5:
x <- 15
if (x > 10) {
print("Above ten")
if (x > 20) {
print("and also above 20!")
} else {
print("but not above 20.")
}
} else {
print("below 10.")
}
#> [1] "Above ten"
#> [1] "but not above 20."
x <- 5
if (x > 10) {
print("Above ten")
if (x > 20) {
print("and also above 20!")
} else {
print("but not above 20.")
}
} else {
print("below 10.")
}
#> [1] "below 10."You can have multiple conditional statements in the if-else clause combined together:
ifelse() Function
Given that if only works with a single TRUE or FALSE, you might wonder what to do if you have a vector of logical values. ifelse() can handle vectors of logical values. The first argument of ifelse() function is a vector of logical values,the second argument is a value that it produces if the element of the logical vector is TRUE, and the third argument is a value that it produces if the element of the logical vector is FALSE. Check this example out:
Some Useful Functions: any() and all()
any() and all() functions come in handy when you work with conditional statement. Here are some examples:
x <- c(-2, -1, 0, 1, 2)
## all(). It return TRUE if all elements of a vector satisfy the condition
print(all(x > 0))
#> [1] FALSE
## any(). It return TRUE if at least one of elements in a vector satisfies the condition
print(any(x > 0))
#> [1] TRUE
## Here is an example
if(all(x < 0)) {
print("all are negative")
} else {
print ("not all of them are negative")
}
#> [1] "not all of them are negative"For Loops
There may be a situation when you need to execute a block of code multiple times. In general, statements are executed sequentially. The first statement in a function is executed first, followed by the second, and so on.
Programming languages provide various control structures that allow for more complicated execution paths. A loop statement allows us to execute a statement or groups of statements multiple times (iterate). It is a sequence of instructions that is repeated until a certain condition is reached. The most basic and commonly used type of loops is a for loop. The general format of a for loop is as follows:
for(loop.object in loop.vector) {
LOOP.CODE
}There are three key aspects of loops: The loop object, the loop vector, and the loop code:
-
Loop object: The object that will change for each iteration of the loop. This is usually a letter likei. -
Loop vector: A vector specifying all values that the loop object will take over the loop. You can specify the values any way you’d like (as long as it’s a vector). -
Loop code: The code that will be executed for all values in the loop vector.
Below you can find a few examples on how for loops can be utilized:
## Printing numbers from 1 to 10
for (i in 1:10){
print (i)
}
#> [1] 1
#> [1] 2
#> [1] 3
#> [1] 4
#> [1] 5
#> [1] 6
#> [1] 7
#> [1] 8
#> [1] 9
#> [1] 10
## Printing elements of the vector x
x <- c(10, 20, 30, 40, 50)
for (i in 1:length(x)){
print(x[i])
}
#> [1] 10
#> [1] 20
#> [1] 30
#> [1] 40
#> [1] 50
## Creating and populating an empty vector z
z <- c() # creating an empty vector.
for (i in 1:5){
z[i] <- 2*i
}
print(z)
#> [1] 2 4 6 8 10
## Creating and populating an empty list
a <- list() # creating an empty list
for (i in 1:4){
a[[i]] <- rnorm(i)
}
print(a)
#> [[1]]
#> [1] 1.858668
#>
#> [[2]]
#> [1] -0.07453658 0.70422023
#>
#> [[3]]
#> [1] -1.287425 0.933536 -1.147979
#>
#> [[4]]
#> [1] -1.4285506 0.4121117 0.5470766 -0.4287068
## Updating elements of the vector x
x <- c(1, 2, 3, 4, 5)
for (i in 1:length(x)){
x[i] <- x[i] ^ 2
}
print(x)
#> [1] 1 4 9 16 25
## Summing up numbers from 1 to 100
current.sum <- 0
for(i in 1:100) {
current.sum <- current.sum + i
}Break Statement
Loop control statements change execution from its normal sequence. Break statement stops the execution of a for loop when the condition specified is met. In other words, it stops before it has looped through all the items For example,
for(i in 1:60) {
if(i > 15){
break
}
print(i)
}
#> [1] 1
#> [1] 2
#> [1] 3
#> [1] 4
#> [1] 5
#> [1] 6
#> [1] 7
#> [1] 8
#> [1] 9
#> [1] 10
#> [1] 11
#> [1] 12
#> [1] 13
#> [1] 14
#> [1] 15Next Statement
With the next statement, you can skip an undesired iteration without terminating the loop:
## Skipping even numbers
for(i in 1:100) {
if(i %% 2 == 0){
next
}
print(i)
}
#> [1] 1
#> [1] 3
#> [1] 5
#> [1] 7
#> [1] 9
#> [1] 11
#> [1] 13
#> [1] 15
#> [1] 17
#> [1] 19
#> [1] 21
#> [1] 23
#> [1] 25
#> [1] 27
#> [1] 29
#> [1] 31
#> [1] 33
#> [1] 35
#> [1] 37
#> [1] 39
#> [1] 41
#> [1] 43
#> [1] 45
#> [1] 47
#> [1] 49
#> [1] 51
#> [1] 53
#> [1] 55
#> [1] 57
#> [1] 59
#> [1] 61
#> [1] 63
#> [1] 65
#> [1] 67
#> [1] 69
#> [1] 71
#> [1] 73
#> [1] 75
#> [1] 77
#> [1] 79
#> [1] 81
#> [1] 83
#> [1] 85
#> [1] 87
#> [1] 89
#> [1] 91
#> [1] 93
#> [1] 95
#> [1] 97
#> [1] 99For Loops Combined with If-Else Statements
You can even combine for loops with if-else statements:
x <- 1:10
for (i in 1:length(x)){
if(x[i] %% 2 == 0){
print(paste("The number", x[i], "is even"))
} else {
print(paste("The number", x[i], "is odd"))
}
}
#> [1] "The number 1 is odd"
#> [1] "The number 2 is even"
#> [1] "The number 3 is odd"
#> [1] "The number 4 is even"
#> [1] "The number 5 is odd"
#> [1] "The number 6 is even"
#> [1] "The number 7 is odd"
#> [1] "The number 8 is even"
#> [1] "The number 9 is odd"
#> [1] "The number 10 is even"Nested For Loops
Nested loops are commonly needed for multidimensional or hierarchical data structures (e.g. matrices, lists). Nesting beyond 2 to 3 levels often makes it difficult to read/understand the code. If you find yourself in need of a large number of nested loops, you may want to break up the loops by using functions (discussed in next lecture). Here is an example of nested loop:
## Creating and populating an empty matrix
matrix1 <- matrix(ncol = 4, nrow = 5) # creating an empty matrix
for (i in 1:dim(matrix1)[1]){
for (j in 1:dim(matrix1)[2]){
matrix1[i, j] <- i*j
}
}
print(matrix1)
#> [,1] [,2] [,3] [,4]
#> [1,] 1 2 3 4
#> [2,] 2 4 6 8
#> [3,] 3 6 9 12
#> [4,] 4 8 12 16
#> [5,] 5 10 15 20While Loops
While loops begin by testing a condition. If it is TRUE, then they execute the loop body. Once the loop body is executed, the condition is tested again, and so forth, until the condition is FALSE, after which the loop exits.
i <- 1
while (i < 10){
print(i)
i <- i + 1
}
#> [1] 1
#> [1] 2
#> [1] 3
#> [1] 4
#> [1] 5
#> [1] 6
#> [1] 7
#> [1] 8
#> [1] 9While Loops with Next Statements
While loops can be combined with next statements:
# Printing odd numbers that are less than 15
i <- 0
while (i < 15){
i <- i + 1
if(i %% 2 == 0){
next
}
print(i)
}
#> [1] 1
#> [1] 3
#> [1] 5
#> [1] 7
#> [1] 9
#> [1] 11
#> [1] 13
#> [1] 15While loops can potentially result in infinite loops if not written properly. Use with care! If you accidentally created and executed infinite loops, it will run forever and take up all your storage in R. To stop an infinite while loop, press the red stop sign that shows up in the top right corner of the console. Can you check and tell what is wrong with the while loops given below:
While Loops with Break Statements
Similarly, while loops can be combined with break statements:
i <- 1
while (i < 20){
print (i)
if (i == 5){
break
}
i <- i + 1
}
#> [1] 1
#> [1] 2
#> [1] 3
#> [1] 4
#> [1] 5Can you tell what would be the output of these while loops without running them?
i <- 1
while (i < 20){
print (i)
if (i == 5){
break
}
i <- i + 1
}
#> [1] 1
#> [1] 2
#> [1] 3
#> [1] 4
#> [1] 5
i <- 1
while (i < 20){
if (i == 5){
break
}
print (i)
i <- i + 1
}
#> [1] 1
#> [1] 2
#> [1] 3
#> [1] 4