Introduction to Functions in R

Functions are like recipes - they take ingredients (inputs), follow a set of instructions, and produce a result (output). In R, functions help us: - Avoid repeating code - Make our code more organized - Make our code reusable

Basic Function Structure

A function in R has this basic structure:

function_name <- function(parameter1, parameter2) {
  # Function body - what the function does
  result <- # some operation
  return(result)
}

Simple Function Examples

Let’s start with some very simple functions:

# 1. A function to calculate the square of a number
square_number <- function(x) {
  result <- x * x
  return(result)
}

# Try it out
square_number(5)  # Returns 25

## [1] 25

square_number(3)  # Returns 9

## [1] 9

# 2. A function to greet someone
greet_person <- function(name) {
  greeting <- paste("Hello,", name, "!")
  return(greeting)
}

# Try it out
greet_person("Alice")

## [1] "Hello, Alice !"

greet_person("Bob")

## [1] "Hello, Bob !"

Functions with Multiple Parameters

# 1. Calculate rectangle area
calculate_rectangle_area <- function(length, width) {
  area <- length * width
  return(area)
}

# Try it out
calculate_rectangle_area(5, 3)  # Returns 15

## [1] 15

# 2. Create a personalized message
create_message <- function(name, age, hobby) {
  message <- paste(name, "is", age, "years old and loves", hobby)
  return(message)
}

# Try it out
create_message("Sarah", 25, "painting")

## [1] "Sarah is 25 years old and loves painting"

Functions for Data Manipulation

Let’s create some functions that work with data:

# Create sample data
student_scores <- data.frame(
  name = c("Alice", "Bob", "Charlie", "Diana"),
  math = c(85, 92, 78, 95),
  science = c(92, 88, 85, 90),
  history = c(88, 85, 82, 87)
)

# 1. Function to calculate average score for a student
calculate_average <- function(math, science, history) {
  avg <- (math + science + history) / 3
  return(round(avg, 1))
}

# Apply to our data
student_scores$average <- with(student_scores, 
                             calculate_average(math, science, history))

# Show results
student_scores

##      name math science history average
## 1   Alice   85      92      88    88.3
## 2     Bob   92      88      85    88.3
## 3 Charlie   78      85      82    81.7
## 4   Diana   95      90      87    90.7

# 2. Function to determine grade based on score
determine_grade <- function(score) {
  if (score >= 90) {
    return("A")
  } else if (score >= 80) {
    return("B")
  } else if (score >= 70) {
    return("C")
  } else {
    return("D")
  }
}

# Apply to our average scores
student_scores$grade <- sapply(student_scores$average, determine_grade)

# Show results
student_scores

##      name math science history average grade
## 1   Alice   85      92      88    88.3     B
## 2     Bob   92      88      85    88.3     B
## 3 Charlie   78      85      82    81.7     B
## 4   Diana   95      90      87    90.7     A

Functions with Default Values

Sometimes we want functions to have default values for parameters:

# Function to calculate tip
calculate_tip <- function(bill_amount, tip_percentage = 15) {
  tip <- bill_amount * (tip_percentage / 100)
  return(round(tip, 2))
}

# Try it out
calculate_tip(50)  # Uses default 15% tip

## [1] 7.5

calculate_tip(50, 20)  # Specifies 20% tip

## [1] 10

Functions That Return Multiple Values

Functions can return multiple values using a list:

# Function to analyze a numeric vector
analyze_numbers <- function(numbers) {
  result <- list(
    mean = mean(numbers),
    median = median(numbers),
    std_dev = sd(numbers),
    range = max(numbers) - min(numbers)
  )
  return(result)
}

# Try it out with some numbers
test_scores <- c(85, 92, 78, 95, 88, 90)
analysis <- analyze_numbers(test_scores)

# Access individual results
analysis$mean

## [1] 88

analysis$median

## [1] 89

analysis$std_dev

## [1] 5.966574

analysis$range

## [1] 17

Practice Exercises

Try creating these functions on your own:

Create a function that converts temperature from Fahrenheit to Celsius
Create a function that takes a vector of numbers and returns both the sum and the product
Create a function that takes a student’s name and scores and returns a formatted report

Here are the solutions:

# 1. Temperature conversion
fahrenheit_to_celsius <- function(fahrenheit) {
  celsius <- (fahrenheit - 32) * (5/9)
  return(round(celsius, 1))
}

# Test it
fahrenheit_to_celsius(72)

## [1] 22.2

# 2. Sum and product function
calculate_sum_product <- function(numbers) {
  list(
    sum = sum(numbers),
    product = prod(numbers)
  )
}

# Test it
calculate_sum_product(c(2, 3, 4))

## $sum
## [1] 9
## 
## $product
## [1] 24

# 3. Student report function
create_student_report <- function(name, scores) {
  avg_score <- mean(scores)
  max_score <- max(scores)
  min_score <- min(scores)
  
  report <- paste(
    "Student Report for", name, "\n",
    "Average Score:", round(avg_score, 1), "\n",
    "Highest Score:", max_score, "\n",
    "Lowest Score:", min_score
  )
  
  return(report)
}

# Test it
test_scores <- c(85, 92, 78, 95)
create_student_report("Alice", test_scores)

## [1] "Student Report for Alice \n Average Score: 87.5 \n Highest Score: 95 \n Lowest Score: 78"

Tips for Writing Good Functions

Use Clear Names: Function names should describe what they do
Document Your Functions: Add comments explaining what the function does
Keep Functions Simple: Each function should do one thing well
Test Your Functions: Always test with different inputs
Handle Errors: Consider what happens with unexpected inputs

Common Mistakes to Avoid

Forgetting to return a value
Not checking input validity
Using global variables instead of parameters
Making functions too complex
Not testing edge cases

Try modifying these examples and creating your own functions to get more practice!

Introduction to Functions in R

Eren Ada

2025-02-14