Conditional Statements

🚦 R Control Flow: Conditional Statements

Imagine you’re a traffic cop directing cars at a busy intersection. Sometimes cars go left, sometimes right, sometimes straight—it all depends on where they want to go. That’s exactly what conditional statements do in R: they help your code make decisions!

🎯 What Are Conditional Statements?

Think of your code as a story where the hero (your program) reaches a fork in the road. Conditional statements are the signposts that say:

• “If it’s raining, take an umbrella”
• “If you’re hungry, eat lunch; else keep working”
• “Switch between different doors based on your magic key”

Let’s explore each type!

1️⃣ The if Statement

🧸 The Simple Question

The if statement is like asking a yes/no question. If the answer is “yes” (TRUE), do something. If “no” (FALSE), do nothing.

# Is it cold outside?
temperature <- 5

if (temperature < 10) {
  print("Wear a jacket!")
}

Output: "Wear a jacket!"

🎨 How It Works

graph TD
    A["Start"] --> B{Is condition TRUE?}
    B -->|Yes| C["Do the action"]
    B -->|No| D["Skip it"]
    C --> E["Continue"]
    D --> E

📝 The Recipe

if (condition) {
  # Code runs only if
  # condition is TRUE
}

Real-life example: A vending machine only gives you a snack if you put in enough money!

2️⃣ The if-else Statement

🍦 Two Choices

What if you want to do something different when the answer is “no”? That’s where else comes in!

age <- 8

if (age >= 18) {
  print("You can vote!")
} else {
  print("Too young to vote")
}

Output: "Too young to vote"

🎨 The Two Roads

graph TD
    A["Check age"] --> B{age >= 18?}
    B -->|Yes| C["Can vote!"]
    B -->|No| D["Too young"]
    C --> E["Done"]
    D --> E

📝 The Recipe

if (condition) {
  # When TRUE
} else {
  # When FALSE
}

Think of it like: “If it’s sunny, play outside. Otherwise, play inside.”

3️⃣ Nested Conditionals

🪆 Decisions Inside Decisions

Sometimes one question leads to another—like a treasure hunt with multiple clues! You can put if statements inside other if statements.

score <- 85
attendance <- 90

if (score >= 60) {
  if (attendance >= 80) {
    print("You passed! 🎉")
  } else {
    print("Good score, but")
    print("attend more classes!")
  }
} else {
  print("Study harder!")
}

Output: "You passed! 🎉"

🎨 The Nested Path

graph TD
    A["Start"] --> B{score >= 60?}
    B -->|No| C["Study harder!"]
    B -->|Yes| D{attendance >= 80?}
    D -->|Yes| E["You passed! 🎉"]
    D -->|No| F["Attend more!"]

💡 Pro Tip: else if Chains

When you have many choices, use else if:

grade <- 75

if (grade >= 90) {
  print("A - Excellent!")
} else if (grade >= 80) {
  print("B - Great job!")
} else if (grade >= 70) {
  print("C - Good work!")
} else {
  print("Keep trying!")
}

Output: "C - Good work!"

4️⃣ The ifelse() Function

⚡ The Quick Decision Maker

R has a special shortcut called ifelse(). It’s like a tiny decision machine that works super fast—especially with lists of things!

# Check multiple ages at once!
ages <- c(5, 12, 18, 25, 8)

status <- ifelse(ages >= 18,
                 "Adult",
                 "Child")

print(status)

Output: "Child" "Child" "Adult" "Adult" "Child"

📝 The Recipe

ifelse(test, yes_value, no_value)

🎯 One-Liner Magic

# Is the number even or odd?
num <- 7
result <- ifelse(num %% 2 == 0,
                 "Even", "Odd")
print(result)  # "Odd"

Why use it? When you need to check many values at once, ifelse() is your best friend!

5️⃣ The switch Statement

🚪 The Magic Door Selector

Imagine you have 5 doors, each with a different prize. The switch statement lets you pick the right door based on a key!

day <- "Monday"

message <- switch(day,
  "Monday" = "Start of week! 💪",
  "Friday" = "Weekend coming! 🎉",
  "Sunday" = "Rest day! 😴",
  "Regular day"  # Default
)

print(message)

Output: "Start of week! 💪"

🎨 How Switch Works

graph TD
    A["Get the key"] --> B{Which door?}
    B -->|Door 1| C["Prize 1"]
    B -->|Door 2| D["Prize 2"]
    B -->|Door 3| E["Prize 3"]
    B -->|Other| F["Default prize"]

📝 Two Ways to Use Switch

Way 1: Named choices (like above)

fruit <- "apple"
color <- switch(fruit,
  "apple" = "red",
  "banana" = "yellow",
  "grape" = "purple",
  "unknown"
)
# color = "red"

Way 2: Number position

choice <- 2
result <- switch(choice,
  "First option",
  "Second option",
  "Third option"
)
# result = "Second option"

🧠 Quick Comparison Table

🎮 Putting It All Together

Here’s a fun example combining everything:

# Pizza ordering system! 🍕

size <- "large"
extra_cheese <- TRUE

# Use switch for size
base_price <- switch(size,
  "small" = 8,
  "medium" = 12,
  "large" = 16,
  10  # default
)

# Use if-else for extras
if (extra_cheese) {
  total <- base_price + 2
  print("Extra cheese added!")
} else {
  total <- base_price
}

# Final message
print(paste("Total: quot;, total))

Output:

"Extra cheese added!"
"Total: $ 18"

🌟 Remember This!

🚦 Conditionals are traffic cops for your code!

• if = “Do this if yes”
• else = “Otherwise do this”
• Nested = “Decisions inside decisions”
• ifelse() = “Quick checks for many items”
• switch = “Pick from a menu of options”

You’ve just learned how to make your R code smart enough to make decisions! Now your programs can think, choose, and act differently based on any situation. 🎉

Happy coding! 🚀