lapply and sapply in R Programming - Mini Project: Build & Apply

Using lapply and sapply in R

📖 Scenario: You are working with a list of numeric vectors representing daily sales for different stores. You want to calculate the total sales and average sales for each store using R.

🎯 Goal: Build a small R script that uses lapply and sapply to calculate total and average sales for each store from a list of sales data.

📋 What You'll Learn

Create a list called store_sales with three numeric vectors named store1, store2, and store3 with exact values

Create a variable called sales_threshold set to 100

Use lapply to calculate total sales for each store

Use sapply to calculate average sales for each store

Print the total sales list and average sales vector

💡 Why This Matters

🌍 Real World

Analyzing sales data from multiple stores to quickly calculate totals and averages helps businesses make informed decisions.

💼 Career

Data analysts and R programmers often use <code>lapply</code> and <code>sapply</code> to efficiently process lists of data without writing loops.

1

Create the sales data list

Create a list called store_sales with three numeric vectors: store1 with values c(120, 130, 110), store2 with values c(90, 100, 95), and store3 with values c(150, 160, 170).

R Programming

# Create the list store_sales with three stores and their sales
# Your code here

Hint

Use the list() function to create store_sales with named vectors for each store.

2

Set the sales threshold

Create a variable called sales_threshold and set it to 100.

R Programming

store_sales <- list(
  store1 = c(120, 130, 110),
  store2 = c(90, 100, 95),
  store3 = c(150, 160, 170)
)
# Create sales_threshold variable and set it to 100
# Your code here

Hint

Just assign the number 100 to the variable sales_threshold.

3

Calculate total and average sales

Use lapply on store_sales with the function sum to calculate total sales for each store and save it in total_sales. Then use sapply on store_sales with the function mean to calculate average sales for each store and save it in average_sales.

R Programming

store_sales <- list(
  store1 = c(120, 130, 110),
  store2 = c(90, 100, 95),
  store3 = c(150, 160, 170)
)
sales_threshold <- 100
# Use lapply to calculate total_sales
# Use sapply to calculate average_sales
# Your code here

Hint

Use lapply(store_sales, sum) and sapply(store_sales, mean) to get totals and averages.

4

Print the results

Print the total_sales list and the average_sales vector using two separate print() statements.

R Programming

store_sales <- list(
  store1 = c(120, 130, 110),
  store2 = c(90, 100, 95),
  store3 = c(150, 160, 170)
)
sales_threshold <- 100
total_sales <- lapply(store_sales, sum)
average_sales <- sapply(store_sales, mean)
# Print total_sales
# Print average_sales
# Your code here

Hint

Use print(total_sales) and print(average_sales) to show the results.

Practice

1. What is the main difference between lapply and sapply in R?

easy

A. lapply modifies the original list, sapply does not.

B. lapply works only on vectors, sapply works only on lists.

C. lapply always returns a list, while sapply tries to simplify the result.

D. lapply is faster than sapply in all cases.

Solution

1. Step 1: Understand return types of lapply and sapply

   lapply always returns a list regardless of the function applied.

2. Step 2: Understand simplification behavior of sapply

   sapply tries to simplify the output to a vector or matrix if possible, otherwise returns a list.

3. Final Answer:

   lapply always returns a list, while sapply tries to simplify the result. -> Option C

4. Quick Check:

   Return type difference = lapply always returns a list, while sapply tries to simplify the result. [OK]

Hint: Remember: lapply = list output, sapply = simpler output if possible [OK]

Common Mistakes:

• Thinking lapply works only on vectors
• Believing sapply always returns a list
• Assuming lapply modifies original data

2. Which of the following is the correct syntax to apply the function sqrt to each element of a list my_list using lapply?

easy

A. lapply(my_list, sqrt)

B. lapply(my_list, sqrt())

C. lapply(sqrt, my_list)

D. lapply(my_list sqrt)

Solution

1. Step 1: Identify correct function call syntax

   The function name should be passed without parentheses to lapply, so sqrt not sqrt().

2. Step 2: Confirm argument order

   The first argument is the list, second is the function to apply: lapply(my_list, sqrt).

3. Final Answer:

   lapply(my_list, sqrt) -> Option A

4. Quick Check:

   Function without () and correct order = lapply(my_list, sqrt) [OK]

Hint: Pass function name without () as second argument in lapply [OK]

Common Mistakes:

• Using parentheses after function name inside lapply
• Swapping argument order
• Missing comma between arguments

3. What will be the output of the following R code?

nums <- list(a = 1:3, b = 4:6)
lapply(nums, sum)
sapply(nums, sum)

medium

A. Both return a list with sums: list(a=6, b=15)

B. lapply returns list(a=6, b=15), sapply returns numeric vector c(a=6, b=15)

C. lapply returns numeric vector, sapply returns list

D. Both return numeric vector c(6, 15)

Solution

1. Step 1: Calculate sums for each list element

   Sum of 1:3 is 6, sum of 4:6 is 15.

2. Step 2: Understand output types of lapply and sapply

   lapply returns a list with sums named by list elements; sapply simplifies to a numeric vector with names.

3. Final Answer:

   lapply returns list(a=6, b=15), sapply returns numeric vector c(a=6, b=15) -> Option B

4. Quick Check:

   lapply = list, sapply = vector if possible [OK]

Hint: lapply always list; sapply tries vector or matrix [OK]

Common Mistakes:

• Confusing output types of lapply and sapply
• Assuming both return same structure
• Ignoring named elements in output

4. Consider this code snippet:

my_list <- list(1, 2, 3)
lapply(my_list, function(x) x^2)

What is wrong with this code if the goal is to get a numeric vector of squared values?

medium

A. Nothing is wrong; it returns a numeric vector.

B. The anonymous function is incorrect; it should use x*x instead of x^2.

C. The list elements should be named for lapply to work.

D. Using lapply returns a list, not a numeric vector.

Solution

1. Step 1: Understand output type of lapply

   lapply always returns a list, even if function returns single values.

2. Step 2: Identify how to get numeric vector output

   To get a numeric vector, sapply should be used instead of lapply.

3. Final Answer:

   Using lapply returns a list, not a numeric vector. -> Option D

4. Quick Check:

   lapply output is list, not vector [OK]

Hint: Use sapply for vector output, lapply always returns list [OK]

Common Mistakes:

• Thinking lapply returns vector
• Believing function syntax is wrong
• Assuming names are required for lapply

5. You have a list of numeric vectors: data_list <- list(c(1,2), c(3,4,5), c(6)). You want to create a numeric vector of the means of each vector, but if a vector is empty, return NA for that element. Which code correctly does this using lapply or sapply?

hard

A. sapply(data_list, function(x) if(length(x) == 0) NA else mean(x))

B. lapply(data_list, function(x) if(length(x) == 0) NA else mean(x))

C. sapply(data_list, mean, na.rm=TRUE)

D. lapply(data_list, mean, na.rm=TRUE)

Solution

1. Step 1: Handle empty vectors with conditional inside function

   The function checks if length is zero, returns NA; else returns mean.

2. Step 2: Use sapply to get numeric vector output

   Using sapply simplifies the result to a numeric vector, which is desired.

3. Final Answer:

   sapply(data_list, function(x) if(length(x) == 0) NA else mean(x)) -> Option A

4. Quick Check:

   Conditional function + sapply for vector output [OK]

Hint: Use sapply with if-else inside function for conditional output [OK]

Common Mistakes:

• Using lapply and expecting vector output
• Not handling empty vectors explicitly
• Passing na.rm=TRUE without checking empty vectors