Apply functions on matrices in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the sum of each row in the matrix.

R Programming

row_sums <- apply(matrix_data, [1], sum)

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

A1

B2

C3

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using margin 2 sums columns instead of rows.

Using margin 0 or 3 causes errors.

The apply function with margin 1 applies the function to rows.

2fill in blank

medium

Complete the code to calculate the mean of each column in the matrix.

R Programming

col_means <- apply(matrix_data, [1], mean)

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

A3

B1

C2

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using margin 1 sums rows instead of columns.

Using margin 0 or 3 causes errors.

The apply function with margin 2 applies the function to columns.

3fill in blank

hard

Fix the error in the code to calculate the maximum value in each row.

R Programming

max_values <- apply(matrix_data, [1], max)

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

A1

B0

C3

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Using margin 2 returns max per column instead.

Using margin 0 or 3 causes errors.

Margin 1 applies the function to rows, so use 1 to get max per row.

4fill in blank

hard

Fill both blanks to create a matrix of logical values where each element is TRUE if greater than 5.

R Programming

result <- apply(matrix_data, [1], function(x) x [2] 5)

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A2

B>

C<

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using margin 2 applies function column-wise, which is not intended here.

Using < or other operators changes the logic.

Margin 1 applies function to rows, and > checks if elements are greater than 5.

5fill in blank

hard

Fill all three blanks to create a named logical vector indicating which column sums are greater than 10.

R Programming

result <- sapply(colnames(matrix_data), function([1]) sum(matrix_data[ , [2]]) [3] 10)

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

Acol

B>

C<

Drow

Attempts:

3 left

💡 Hint

Common Mistakes

Using < instead of > changes the condition.

Using row instead of col causes indexing errors.

Use col as the variable name, > to check sums greater than 10, and col again to index columns.

Practice

1. In R, what does the apply() function do when used on a matrix?

easy

A. It creates a new matrix with doubled values.

B. It converts the matrix into a vector.

C. It sorts the matrix elements in ascending order.

D. It applies a function to each row or column of the matrix.

Solution

1. Step 1: Understand the purpose of apply()

   The apply() function is designed to run a function on margins of an array or matrix.

2. Step 2: Identify what margins mean in a matrix

   Margin 1 means rows, margin 2 means columns. So apply() runs the function on each row or column.

3. Final Answer:

   It applies a function to each row or column of the matrix. -> Option D

4. Quick Check:

   apply() = function on rows/columns [OK]

Hint: Remember: MARGIN=1 rows, MARGIN=2 columns in apply() [OK]

Common Mistakes:

• Thinking apply() changes matrix shape automatically
• Confusing apply() with sorting or vector conversion
• Using apply() without specifying margin

2. Which of the following is the correct syntax to calculate the sum of each column in a matrix m using apply() in R?

easy

A. apply(m, 2, sum)

B. apply(m, sum, 2)

C. apply(m, 1, sum)

D. apply(sum, m, 2)

Solution

1. Step 1: Identify margin for columns

   In apply(), margin 2 means columns.

2. Step 2: Check function placement

   The function to apply (sum) is the third argument, so syntax is apply(m, 2, sum).

3. Final Answer:

   apply(m, 2, sum) -> Option A

4. Quick Check:

   sum columns = apply(m, 2, sum) [OK]

Hint: Use margin=2 for columns in apply() [OK]

Common Mistakes:

• Using margin=1 for columns instead of 2
• Swapping function and margin arguments
• Missing the function argument

3. What is the output of the following R code?

m <- matrix(1:6, nrow=2)
apply(m, 1, max)

medium

A. [1] 3 6

B. [1] 4 5

C. [1] 5 6

D. [1] 2 4

Solution

1. Step 1: Understand the matrix structure

   The matrix m is created with values 1 to 6, 2 rows: Row 1: 1, 3, 5 Row 2: 2, 4, 6

2. Step 2: Apply max function on rows (margin=1)

   Max of row 1 is 5, max of row 2 is 6.

3. Final Answer:

   [1] 5 6 -> Option C

4. Quick Check:

   max per row = 5, 6 [OK]

Hint: Check matrix layout before applying functions [OK]

Common Mistakes:

• Confusing rows and columns in margin
• Misreading matrix values
• Assuming apply returns matrix instead of vector

4. Identify the error in this R code snippet:

m <- matrix(1:9, nrow=3)
apply(m, 3, mean)

medium

A. apply() cannot be used with mean.

B. Margin 3 is invalid for a 2D matrix.

C. Matrix m is not created properly.

D. The function mean is not defined.

Solution

1. Step 1: Check matrix dimensions

   The matrix m has 2 dimensions (rows and columns).

2. Step 2: Validate margin argument

   Margin 3 refers to a third dimension, which does not exist in a 2D matrix.

3. Final Answer:

   Margin 3 is invalid for a 2D matrix. -> Option B

4. Quick Check:

   Margin must be 1 or 2 for matrices [OK]

Hint: Use only 1 or 2 as margin for 2D matrices [OK]

Common Mistakes:

• Using margin > 2 for 2D matrices
• Assuming apply works on non-existent dimensions
• Confusing apply() with array functions

5. You have a matrix m of numeric values. You want to create a new vector that contains the mean of each row but only for rows where the sum is greater than 10. Which R code correctly does this using apply()?

hard

A. apply(m, 1, function(x) if(sum(x) > 10) mean(x) else NA)[!is.na(.)]

B. apply(m, 1, function(x) if(sum(x) > 10) mean(x))

C. apply(m, 1, function(x) mean(x[sum(x) > 10]))

D. apply(m, 2, function(x) if(sum(x) > 10) mean(x))

Solution

1. Step 1: Understand the requirement

   We want mean of each row only if that row's sum is > 10, else exclude it.

2. Step 2: Analyze each option

   A returns NA for rows not >10 but does not remove them. C incorrectly filters inside mean. D uses margin=2 (columns) instead of rows.

3. Step 3: Correct approach

   apply(m, 1, function(x) if(sum(x) > 10) mean(x) else NA)[!is.na(.)] returns NA for rows with sum ≤ 10, then removes NAs with [!is.na(.)], giving only desired means.

4. Final Answer:

   apply(m, 1, function(x) if(sum(x) > 10) mean(x) else NA)[!is.na(.)] -> Option A

5. Quick Check:

   Filter rows by sum > 10, then mean [OK]

Hint: Use if-else inside apply and remove NA after [OK]

Common Mistakes:

• Using margin=2 instead of 1 for rows
• Not handling rows with sum ≤ 10 properly
• Trying to filter inside mean() incorrectly