Pipe operator (%>% and |>) in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of pipe with dplyr and base R

What is the output of this R code using the pipe operator %>% from dplyr?

R Programming

library(dplyr)
result <- mtcars %>%
  filter(cyl == 6) %>%
  summarise(avg_mpg = mean(mpg)) %>%
  pull(avg_mpg)
print(round(result, 2))

A 19.74

B 20.57

C 21.00

D 18.50

💡 Hint

Look at the cars with 6 cylinders and calculate their average mpg.

The code filters mtcars for 6-cylinder cars, then calculates the mean mpg, which is approximately 19.74.

❓ Predict Output

intermediate

Output of base R pipe |> with nested functions

What is the output of this R code using the base pipe operator |>?

R Programming

result <- 1:5 |> sum() |> sqrt()
print(round(result, 3))

A 2.236

B 5.477

C 15.000

D 3.873

💡 Hint

Sum 1 to 5, then take the square root.

Sum of 1 to 5 is 15, square root of 15 is approximately 3.873.

🔧 Debug

advanced

Identify the error in pipe usage

What error does this R code produce when using the pipe operator %>%?

R Programming

library(dplyr)
result <- mtcars %>%
  filter(cyl == 4) %>%
  summarise(avg_hp = mean(hp)) %>%
  select(avg_hp) %>%
  mean()
print(result)

A Error: no applicable method for 'mean' applied to an object of class 'data.frame'

B Error: argument is not numeric or logical: returning NA

C Error: object of type 'closure' is not subsettable

D No error, prints average horsepower

💡 Hint

Check what class the object is before calling mean().

select(avg_hp) returns a data frame, mean() expects a numeric vector, so it produces "Error: no applicable method for 'mean' applied to an object of class 'data.frame'".

🧠 Conceptual

advanced

Understanding pipe operator behavior

Which statement best describes the difference between %>% and |> in R?

A %>% is deprecated and replaced by |> in all R versions.

B %>% is from magrittr and allows placeholder .; |> is base R pipe introduced in R 4.1 without placeholder support.

C %>% is base R pipe; |> is from magrittr package with more features.

D Both %>% and |> are identical in syntax and behavior.

💡 Hint

Think about package origin and placeholder usage.

%>% comes from magrittr and supports the dot placeholder for the left-hand side; |> is a base R pipe introduced in R 4.1 and does not support the dot placeholder.

❓ Predict Output

expert

Output of complex pipe with anonymous function

What is the output of this R code using the base pipe |> with an anonymous function?

R Programming

result <- 1:4 |> ((x) x * 2)() |> sum()
print(result)

A Error: unexpected '()' in expression

B 10

C 20

D 30

💡 Hint

Anonymous function doubles each element, then sum them.

1:4 is doubled to 2,4,6,8; sum is 20.

Practice

1. What does the pipe operator %>% do in R?

easy

A. It creates a new variable in the environment.

B. It passes the result of one function as the first argument to the next function.

C. It comments out the following line of code.

D. It repeats a function multiple times automatically.

Solution

1. Step 1: Understand the pipe operator purpose

   The pipe operator %>% takes the output of the left side and sends it as the first argument to the function on the right side.

2. Step 2: Compare with other options

   Options B, C, and D describe unrelated actions like creating variables, commenting, or repeating functions, which are not what pipes do.

3. Final Answer:

   It passes the result of one function as the first argument to the next function. -> Option B

4. Quick Check:

   Pipe operator = passes output to next function [OK]

Hint: Pipes send output forward as input to next function [OK]

Common Mistakes:

• Thinking pipe creates variables
• Confusing pipe with comment symbol
• Assuming pipe repeats functions

2. Which of the following is the correct syntax to use the native R pipe operator introduced in R 4.1?

easy

A. data |> filter(value > 10)

B. data %>% filter(value > 10)

C. data ->| filter(value > 10)

D. data |-> filter(value > 10)

Solution

1. Step 1: Identify native pipe syntax

   The native pipe operator in R 4.1+ is |>, used as data |> function().

2. Step 2: Check other options

   data %>% filter(value > 10) uses %>% which is from dplyr, not native. Options A and D are invalid syntax.

3. Final Answer:

   data |> filter(value > 10) -> Option A

4. Quick Check:

   Native pipe = |> [OK]

Hint: Native pipe uses |> without percent signs [OK]

Common Mistakes:

• Using %>% as native pipe
• Typing invalid pipe symbols like ->|
• Confusing pipe with assignment operators

3. What is the output of this R code?

library(dplyr)
data <- tibble(x = 1:3)
data %>% mutate(y = x * 2) %>% pull(y)

medium

A. [1, 2, 3]

B. Error: object 'y' not found

C. [1, 3, 5]

D. [2, 4, 6]

Solution

1. Step 1: Understand the pipe steps

   The data tibble has x = 1, 2, 3. The mutate(y = x * 2) adds y as double x: 2, 4, 6.

2. Step 2: Extract the y column

   pull(y) extracts the y column as a vector: 2, 4, 6.

3. Final Answer:

   [2, 4, 6] -> Option D

4. Quick Check:

   Mutate doubles x, pull extracts y [OK]

Hint: Mutate adds column, pull extracts it [OK]

Common Mistakes:

• Forgetting mutate creates y
• Thinking pull returns whole data frame
• Confusing x and y values

4. Identify the error in this R code using the native pipe operator:

data <- data.frame(a = 1:3)
data |> filter(a > 1)

medium

A. filter() is not found because dplyr is not loaded

B. Native pipe operator |> is invalid syntax here

C. data.frame cannot be piped

D. No error, code runs fine

Solution

1. Step 1: Check package usage

   The function filter() is from dplyr. If dplyr is not loaded, filter() is not available.

2. Step 2: Validate pipe and data

   The native pipe |> works fine with data frames. The error is due to missing dplyr, not pipe or data type.

3. Final Answer:

   filter() is not found because dplyr is not loaded -> Option A

4. Quick Check:

   Missing dplyr causes filter error [OK]

Hint: Load dplyr before using filter() [OK]

Common Mistakes:

• Assuming pipe syntax is wrong
• Thinking data.frame can't be piped
• Ignoring missing library calls

5. Using the native pipe operator, how would you transform a numeric vector v <- c(1, 2, 3, 4) to get the sum of squares of even numbers only?

hard

A. v %>% subset(v %% 2 == 0) %>% sum()^2

B. v |> filter(v %% 2 == 0) |> sum()^2

C. v |> \(x) x[x %% 2 == 0] |> \(x) sum(x^2)

D. v |> map(~ .x^2) |> sum()

Solution

1. Step 1: Filter even numbers using native pipe and anonymous function

   The expression \(x) x[x %% 2 == 0] selects even numbers from vector v.

2. Step 2: Sum squares of filtered numbers

   The next pipe applies \(x) sum(x^2) to calculate sum of squares of those even numbers.

3. Final Answer:

   v |> \(x) x[x %% 2 == 0] |> \(x) sum(x^2) -> Option C

4. Quick Check:

   Filter evens then sum squares [OK]

Hint: Use anonymous functions with |> for complex steps [OK]

Common Mistakes:

• Using filter() without loading dplyr
• Squaring sum instead of summing squares
• Using %>% with native pipe syntax