R Functions Intro

A function is a named, reusable block of code that performs a specific task. Instead of writing the same calculation five times across your script, you write it once as a function and call it by name whenever you need it. Functions make your code shorter, easier to test, and simpler to maintain.

Function Anatomy

function_name <- function(parameter1, parameter2) {
  # body: the code that runs
  result <- parameter1 + parameter2
  return(result)    # send back the answer
}

Diagram:
  Input → [parameter1, parameter2]
                    │
              function body
                    │
  Output ← return(result)

Your First Function

# Define the function
greet <- function(name) {
  message <- paste("Hello,", name, "! Welcome to R.")
  return(message)
}

# Call the function
greet("Priya")
# [1] "Hello, Priya ! Welcome to R."

greet("Arjun")
# [1] "Hello, Arjun ! Welcome to R."

Function With Multiple Parameters

rectangle_area <- function(length, width) {
  area <- length * width
  return(area)
}

rectangle_area(8, 5)    # 40
rectangle_area(12, 3)   # 36

Implicit Return

R automatically returns the value of the last evaluated expression. The explicit return() call is optional but recommended for clarity.

square <- function(x) {
  x ^ 2       # last expression is returned automatically
}

square(7)   # 49

Functions as Objects

In R, functions are objects — just like variables. You can assign them, pass them to other functions, and store them in lists.

# Function stored in a variable
double <- function(x) x * 2

# Pass a function to another function
apply_fn <- function(x, fn) fn(x)
apply_fn(5, double)   # 10

Checking if a Function Exists

is.function(mean)     # TRUE
is.function(sum)      # TRUE
is.function(42)       # FALSE (not a function)

Viewing Function Source Code

# For user-defined functions, just type the name without ()
greet          # prints the function code

# For built-in functions
body(mean)     # body of the function
formals(mean)  # argument list

Practical Example: BMI Calculator Function

calculate_bmi <- function(weight_kg, height_m) {
  bmi      <- weight_kg / (height_m ^ 2)
  bmi      <- round(bmi, 1)
  category <- if (bmi < 18.5) "Underweight" else
              if (bmi < 25)   "Normal"       else
              if (bmi < 30)   "Overweight"   else
                              "Obese"
  return(list(bmi = bmi, category = category))
}

result <- calculate_bmi(70, 1.75)
cat("BMI:", result$bmi, "—", result$category, "\n")

Output:

BMI: 22.9 — Normal

Function Best Practices

• Give functions verb-based names: calculate_tax(), clean_data(), plot_sales()
• Each function should do one thing well
• Keep functions short — if a function exceeds 20-30 lines, consider splitting it
• Document what arguments the function expects and what it returns

Functions are the building blocks of organized R code. Every package you install is a collection of functions. Every analysis script benefits from pulling repeated logic into functions. The investment in learning to write good functions pays off every day you use R.