Anonymous functions in R Programming - Mini Project: Build & Apply

Using Anonymous Functions in R

📖 Scenario: You are working with a list of numbers representing daily sales in a small shop. You want to quickly calculate the square of each sale amount without creating a separate named function.

🎯 Goal: Learn how to use anonymous functions in R to apply a quick calculation to each item in a list.

📋 What You'll Learn

Create a numeric vector called sales with the exact values: 10, 20, 30, 40, 50

Create a variable called square_sales that uses lapply() with an anonymous function to square each number in sales

Print the square_sales variable to display the squared values

💡 Why This Matters

🌍 Real World

Anonymous functions help quickly perform small tasks like calculations or filtering without cluttering your code with many named functions.

💼 Career

Data analysts and programmers often use anonymous functions to write concise and readable code for data transformations and analysis.

1

Create the sales data

Create a numeric vector called sales with these exact values: 10, 20, 30, 40, 50

R Programming

# Create the sales vector with the values 10, 20, 30, 40, 50
# Your code here

Hint

Use the c() function to create a vector with the given numbers.

2

Prepare to square the sales

Create a variable called square_sales and set it to lapply() applied on sales with an anonymous function that takes one argument and returns its square.

R Programming

sales <- c(10, 20, 30, 40, 50)
# Use lapply with an anonymous function to square each sale
# Your code here

Hint

Use function(x) x^2 inside lapply() to square each element.

3

Check the type of the result

Convert square_sales from a list to a numeric vector using unlist() and store it back in square_sales.

R Programming

sales <- c(10, 20, 30, 40, 50)
square_sales <- lapply(sales, function(x) x^2)
# Convert square_sales to a numeric vector
# Your code here

Hint

Use unlist() to convert the list to a vector for easier use.

4

Display the squared sales

Print the square_sales vector to show the squared sales values.

R Programming

sales <- c(10, 20, 30, 40, 50)
square_sales <- lapply(sales, function(x) x^2)
square_sales <- unlist(square_sales)
# Print the squared sales
# Your code here

Hint

Use print(square_sales) to display the vector.

Practice

1. What is an anonymous function in R?

easy

A. A function that must be saved to a variable

B. A function that always returns NULL

C. A function without a name, created on the spot

D. A function that can only be used once

Solution

1. Step 1: Understand the definition of anonymous functions

   Anonymous functions are functions created without giving them a name, used immediately.

2. Step 2: Compare options with the definition

   Only 'A function without a name, created on the spot' correctly describes an anonymous function.

3. Final Answer:

   A function without a name, created on the spot -> Option C

4. Quick Check:

   Anonymous function = unnamed function [OK]

Hint: Anonymous means no name, created instantly [OK]

Common Mistakes:

• Thinking anonymous functions must be saved to variables
• Believing anonymous functions always return NULL
• Confusing anonymous functions with one-time use functions

2. Which of the following is the correct syntax for an anonymous function in R?

easy

A. lambda x: x + 1

B. fun(x) { return x + 1 }

C. def(x) x + 1

D. function(x) x + 1

Solution

1. Step 1: Recall R syntax for anonymous functions

   In R, anonymous functions are written as function(arguments) expression.

2. Step 2: Check each option

   function(x) x + 1 matches R syntax. Options B, C, and D use syntax from other languages or incorrect forms.

3. Final Answer:

   function(x) x + 1 -> Option D

4. Quick Check:

   R anonymous function syntax = function(args) expr [OK]

Hint: R uses 'function' keyword for anonymous functions [OK]

Common Mistakes:

• Using 'def' or 'lambda' which are Python keywords
• Writing function name instead of 'function'
• Adding unnecessary return statements inside anonymous functions

3. What is the output of this R code?

lapply(1:3, function(x) x * 2)

medium

A. [[1]] 2 [[2]] 4 [[3]] 6

B. [1] 2 4 6

C. [1] 1 2 3

D. Error: object 'x' not found

Solution

1. Step 1: Understand lapply with anonymous function

   lapply applies the function to each element of 1:3, returning a list of results.

2. Step 2: Calculate each element

   For x=1,2,3, function(x) x*2 returns 2,4,6 respectively, stored as list elements.

3. Final Answer:

   [[1]] 2 [[2]] 4 [[3]] 6 -> Option A

4. Quick Check:

   lapply returns list of doubled values [OK]

Hint: lapply returns a list, not a vector [OK]

Common Mistakes:

• Expecting a vector output instead of a list
• Confusing lapply with sapply output
• Thinking anonymous function causes error

4. Identify the error in this R code using an anonymous function:

result <- lapply(1:3, function(x) { x + })

medium

A. Anonymous functions cannot be used inside lapply

B. Missing value after '+' operator

C. Incorrect use of curly braces

D. Variable 'result' is not defined

Solution

1. Step 1: Analyze the anonymous function body

   The function body has 'x +', which is incomplete because '+' needs a value after it.

2. Step 2: Identify the syntax error

   This causes a syntax error due to missing operand after '+'. Other options are incorrect because anonymous functions are valid in lapply, curly braces are correctly used, and 'result' is defined.

3. Final Answer:

   Missing value after '+' operator -> Option B

4. Quick Check:

   Incomplete operator usage = syntax error [OK]

Hint: Check operators have both operands [OK]

Common Mistakes:

• Assuming anonymous functions can't be used in lapply
• Ignoring incomplete expressions inside function
• Confusing variable definition errors with syntax errors

5. How can you use an anonymous function to filter even numbers from a vector v <- 1:6 using Filter() in R?

hard

A. Filter(function(x) x %% 2 == 0, v)

B. Filter(function(x) x / 2 == 0, v)

C. Filter(function(x) x %% 2 = 0, v)

D. Filter(function(x) x == 0, v)

Solution

1. Step 1: Understand filtering even numbers

   Even numbers have zero remainder when divided by 2, so condition is x %% 2 == 0.

2. Step 2: Check each option's condition

   Filter(function(x) x %% 2 == 0, v) correctly uses 'x %% 2 == 0'. Filter(function(x) x / 2 == 0, v) uses division instead of modulo, Filter(function(x) x %% 2 = 0, v) uses single '=', which is assignment not comparison, and Filter(function(x) x == 0, v) checks if x equals zero only.

3. Final Answer:

   Filter(function(x) x %% 2 == 0, v) -> Option A

4. Quick Check:

   Modulo equals zero filters even numbers [OK]

Hint: Use '%% 2 == 0' to check even numbers [OK]

Common Mistakes:

• Using single '=' instead of '==' for comparison
• Using division '/' instead of modulo '%%'
• Filtering for x == 0 instead of even numbers