IF, ELSE, and ELSE IF Statements in R

The if / else statement

Conditional statements let you run different code depending on whether a condition is TRUE or FALSE. The basic syntax in R is:

if (condition) {
  expr1
} else {
  expr2
}

Example 1: Simple condition

quantity <- 25

if (quantity > 20) {
  print("You sold a lot!")
} else {
  print("Not enough for today.")
}

## [1] "You sold a lot!"

Tip: consistent indentation matters a lot for readability.

The else if statement

Use else if to check multiple conditions in sequence.

if (condition1) {
  expr1
} else if (condition2) {
  expr2
} else {
  expr3
}

Example 2: Multiple conditions

quantity <- 10

if (quantity < 20) {
  print("Not enough for today.")
} else if (quantity > 20 && quantity <= 30) {
  print("Average day.")
} else {
  print("What a great day!")
}

## [1] "Not enough for today."

Note: - && is the scalar “AND” operator typically used in if() statements; & is vectorized and compares element-by-element.

Example: VAT rate by product category

Imagine three product categories with different VAT rates:

Category	Products	VAT
A	Books, magazines, newspapers, …	8%
B	Vegetables, meat, beverages, …	10%
C	T-shirts, jeans, pants, …	20%

We can apply the correct VAT rate with an if / else if chain:

category <- "A"
price <- 10

if (category == "A") {
  total <- price * 1.08
  cat("VAT rate: 8%.\nTotal price:", total, "\n")
} else if (category == "B") {
  total <- price * 1.10
  cat("VAT rate: 10%.\nTotal price:", total, "\n")
} else {
  total <- price * 1.20
  cat("VAT rate: 20%.\nTotal price:", total, "\n")
}

## VAT rate: 8%.
## Total price: 10.8

Extra (optional): vectorized if-else

If you need to apply conditions to an entire vector (not just a single value), you typically use ifelse() (base R) or dplyr::if_else() (type-stable).

x <- c(10, 25, 40)
ifelse(x > 20, "big", "small")

 

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A work by Gianluca Sottile

gianluca.sottile@unipa.it