If & Else

Life is full of decisions — and so is code. In R, you make decisions using if and else statements. They let your script choose a path based on whether a condition is true or false. You'll also meet ifelse(), which is R's vectorized way of handling conditions — super handy when you're working with whole columns of data at once.

if and else

The basic structure is simple: write if, put a condition in parentheses, and wrap the action in curly braces. Add else to handle the "otherwise" case, and else if for extra branches.

x <- 10

if (x > 5) {
  print("x is greater than 5")
} else {
  print("x is 5 or less")
}

# Multiple branches
y <- 0

if (y > 0) {
  print("Positive")
} else if (y < 0) {
  print("Negative")
} else {
  print("Zero")
}

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Vectorized ifelse()

Regular if works on a single value. But what if you have a whole vector and want to check each element? That's where ifelse() shines. It takes a condition, a value if true, and a value if false — and it recycles them across your entire vector.

scores <- c(55, 82, 91, 47, 73)
grades <- ifelse(scores >= 70, "Pass", "Fail")
print(grades)

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Nested Conditions

You can nest ifelse() calls to handle multiple categories. Just chain another ifelse() inside the "false" spot.

marks <- c(45, 72, 88, 60, 95)

result <- ifelse(marks >= 80, "Distinction",
          ifelse(marks >= 60, "Merit",
          ifelse(marks >= 40, "Pass", "Fail")))

print(result)

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🧪 Quick Quiz

Which function does vectorized conditional operations in R?

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