Why tidy data enables analysis in R Programming - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a tidy data frame with columns 'name' and 'score'.

R Programming

data <- data.frame(name = c("Alice", "Bob"), score = c(85, [1]))

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

A95

B80

C75

D90

Attempts:

3 left

💡 Hint

Common Mistakes

Using a score lower than Alice's by mistake.

The score for Bob should be 90 to complete the data frame correctly.

2fill in blank

medium

Complete the code to select only the 'score' column from the tidy data frame.

R Programming

library(dplyr)
scores <- data %>% select([1])

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

Agender

Bscore

Cage

Dname

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting the 'name' column instead of 'score'.

We select the 'score' column to focus on the scores only.

3fill in blank

hard

Fix the error in the code to filter scores greater than 80.

R Programming

filtered <- data %>% filter(score [1] 80)

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

A>

B<

C==

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' which filters lower scores.

To get scores greater than 80, use the '>' operator.

4fill in blank

hard

Fill both blanks to create a summary of average scores by name.

R Programming

summary <- data %>% group_by([1]) %>% summarise(avg_score = mean([2]))

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Aname

Bscore

Cage

Dgender

Attempts:

3 left

💡 Hint

Common Mistakes

Grouping by wrong column or averaging wrong column.

Group by 'name' and calculate mean of 'score' to summarize average scores.

5fill in blank

hard

Fill all three blanks to filter scores above 80, select 'name' and 'score', and arrange by score descending.

R Programming

result <- data %>% filter(score [1] 80) %>% select([2], [3]) %>% arrange(desc(score))

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

A>

Bname

Cscore

Dage

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong filter operator or selecting wrong columns.

Filter scores greater than 80, select 'name' and 'score' columns, then arrange by descending score.