Pipe chaining operations in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to chain the operations using the pipe operator.

R Programming

library(dplyr)
data <- data.frame(x = 1:5, y = 6:10)
result <- data [1] filter(x > 2)

Drag options to blanks, or click blank then click option'

A%$%

B%>%

C%T>%

D%<>%

Attempts:

3 left

💡 Hint

Common Mistakes

Using other pipe operators like %$% or %T>% which have different purposes.

The pipe operator %>% passes the data to the next function.

2fill in blank

medium

Complete the code to select column 'y' after filtering.

R Programming

library(dplyr)
data <- data.frame(x = 1:5, y = 6:10)
result <- data %>% filter(x > 2) [1] select(y)

Drag options to blanks, or click blank then click option'

A%>%

B%$%

C%T>%

D%<>%

Attempts:

3 left

💡 Hint

Common Mistakes

Using different pipe operators that do not chain functions properly.

Use %>% again to continue chaining operations.

3fill in blank

hard

Fix the error in the pipe chain to calculate the mean of column 'y'.

R Programming

library(dplyr)
data <- data.frame(x = 1:5, y = 6:10)
mean_y <- data %>% filter(x > 2) [1] summarise(mean_y = mean(y))

Drag options to blanks, or click blank then click option'

A%T>%

B%$%

C%>%

D%<>%

Attempts:

3 left

💡 Hint

Common Mistakes

Using %$% which exposes variables but does not chain properly here.

The pipe operator %>% correctly passes the filtered data to summarise.

4fill in blank

hard

Fill both blanks to create a pipe chain that filters and then mutates a new column.

R Programming

library(dplyr)
data <- data.frame(x = 1:5, y = 6:10)
result <- data [1] filter(x >= 3) [2] mutate(z = y * 2)

Drag options to blanks, or click blank then click option'

A%>%

B%T>%

C%<>%

D%$%

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing different pipe operators in the same chain.

Use %>% to chain both filter and mutate operations.

5fill in blank

hard

Fill all three blanks to chain filter, mutate, and then select columns.

R Programming

library(dplyr)
data <- data.frame(x = 1:5, y = 6:10)
result <- data [1] filter(x < 5) [2] mutate(z = y + 1) [3] select(x, z)

Drag options to blanks, or click blank then click option'

A%$%

B%>%

C%<>%

D%T>%

Attempts:

3 left

💡 Hint

Common Mistakes

Using different pipe operators that break the chain.

Use %>% consistently to chain all operations in order.