Ifelse vectorized function in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to use ifelse to assign 'pass' if score is 50 or more, else 'fail'.

R Programming

result <- ifelse(score [1] 50, 'pass', 'fail')

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

A==

B<

C>=

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>=' causes wrong results.

Using '==' only checks for exactly 50, not more.

The ifelse function checks if score is greater than or equal to 50 to assign 'pass'.

2fill in blank

medium

Complete the code to assign 'even' if number is divisible by 2, else 'odd'.

R Programming

result <- ifelse(number %% 2 [1] 0, 'even', 'odd')

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

A!=

B<

C>

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '!=' reverses the logic, marking even numbers as odd.

Using '>' or '<' does not correctly check divisibility.

The modulo operator %% returns 0 for even numbers, so we check if it equals 0.

3fill in blank

hard

Fix the error in the ifelse condition to correctly assign 'adult' if age is 18 or more.

R Programming

category <- ifelse(age [1] 18, 'adult', 'minor')

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

A>=

B!=

C==

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' assigns adults incorrectly.

Using '==' only matches exactly 18, missing older ages.

Adults are those with age greater than or equal to 18, so '>=' is correct.

4fill in blank

hard

Fill both blanks to create a vectorized ifelse that labels numbers as 'positive' if greater than zero, else 'non-positive'.

R Programming

labels <- ifelse(numbers [1] 0, 'positive', [2])

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A>

B'non-positive'

C'negative'

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<=' in the condition reverses logic.

Using 'negative' instead of 'non-positive' changes meaning.

The condition checks if numbers are greater than zero for 'positive', else assigns 'non-positive'.

5fill in blank

hard

Fill all three blanks to create a vectorized ifelse that labels temperatures as 'hot' if above 30, 'cold' if below 15, else 'warm'.

R Programming

labels <- ifelse(temp [1] 30, 'hot', ifelse(temp [2] 15, 'cold', [3]))

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

A>

B<

C'warm'

D>=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '>=' instead of '>' changes the boundary.

Using wrong labels in the else part.

The first condition checks if temp is greater than 30 for 'hot'. The nested ifelse checks if temp is less than 15 for 'cold'. Otherwise, it assigns 'warm'.