if-else statements and logical conditions

Sometimes we want our code to make a decision: do one thing if a condition is true, and something else if it’s false. In R, the tool for this is if ... else. The pattern looks like this:

if (condition) {
  do_something
} else {
  do_something_else
}

Suppose we roll a six-sided die:

roll <- sample(1:6, size = 1)
roll

[1] 2

We might want to check whether the outcome is “big” (4, 5, or 6) or “small” (1, 2, or 3). Here’s how we can use if else to do that:

if (roll >= 4) {
  result <- "Big"
} else {
  result <- "Small"
}

result

[1] "Small"

Let’s unpack:

• First, sample(1:6, size = 1) chooses a random number from 1 to 6;
• Then the if else checks: if the roll is 4 or higher, we call it “Big.” Otherwise, we call it “Small.”

This is how you can make simple decisions in R code.

Logical conditions

In the condition of if, you can use logical comparisons. Here are the most common ones:

Operator	Meaning	Example
==	equal to	x == 3 is TRUE if x is 3
!=	not equal to	x != 3 is TRUE if x is not 3
<	less than	x < 5 is TRUE if x is less than 5
<=	less than or equal	x <= 5
>	greater than	x > 10
>=	greater than or equal	x >= 10
&	AND (both conditions true)	x > 0 & x < 5
|	OR (at least one true)	x < 0 | x > 10
!	NOT (negates a condition)	!(x == 3)
%in%	element of a vector	x %in% c(1,2,3) is TRUE if x is 1, 2, or 3

Here they are in action:

x <- 4
x > 3       

[1] TRUE

x < 3       

[1] FALSE

x >= 3 & x <= 5   

[1] TRUE

x < 3 | x > 5     

[1] FALSE

!(x == 4)   

[1] FALSE

Here is how these might be deployed in the context of if-else:

if (x > 0 & x %% 2 == 0) {
  result <- "Positive even"
} else {
  result <- "Other"
}
result

[1] "Positive even"