Filtering rows in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to filter rows where the column 'age' is greater than 30.

R Programming

filtered_data <- subset(data, age [1] 30)

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

A==

B<

C<=

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' will select rows with age less than 30.

Using '==' will select rows where age is exactly 30.

The operator > filters rows where 'age' is greater than 30.

2fill in blank

medium

Complete the code to filter rows where the 'score' column is equal to 100.

R Programming

filtered_data <- subset(data, score [1] 100)

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

A>=

B==

C<

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' instead of '==' causes assignment, not comparison.

Using '!=' selects rows not equal to 100.

The operator == checks for equality, selecting rows where 'score' is exactly 100.

3fill in blank

hard

Fix the error in the code to filter rows where 'height' is less than or equal to 170.

R Programming

filtered_data <- subset(data, height [1] 170)

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

A<=

B<

C>=

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' excludes rows where height equals 170.

Using '>=' selects rows with height greater than or equal to 170.

The operator <= correctly filters rows where 'height' is less than or equal to 170.

4fill in blank

hard

Fill both blanks to filter rows where 'weight' is greater than 60 and 'age' is less than 50.

R Programming

filtered_data <- subset(data, weight [1] 60 & age [2] 50)

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

A>

B<

C>=

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '>=' or '<=' changes the condition to include equal values.

Mixing up the operators reverses the intended filter.

Use > for weight greater than 60 and < for age less than 50.

5fill in blank

hard

Fill all three blanks to filter rows where 'score' is greater than 80, 'age' is less than 30, and 'height' is at least 160.

R Programming

filtered_data <- subset(data, score [1] 80 & age [2] 30 & height [3] 160)

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

A>

B<

C>=

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<=' instead of '>=' for height changes the condition.

Mixing up operators leads to wrong filtering.

Use > for score greater than 80, < for age less than 30, and >= for height at least 160.