Negative indexing for exclusion in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to exclude the second element from the vector.

R Programming

vec <- c(10, 20, 30, 40)
result <- vec[[1]]
print(result)

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

A-2

B2

C-1

Dc(2)

Attempts:

3 left

💡 Hint

Common Mistakes

Using positive index includes the element instead of excluding it.

Using -2 excludes the second element from the vector.

2fill in blank

medium

Complete the code to exclude the first and third elements from the vector.

R Programming

vec <- c(5, 15, 25, 35)
result <- vec[[1]]
print(result)

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A-c(1, 3)

Bc(1, 3)

C-c(2, 4)

Dc(2, 4)

Attempts:

3 left

💡 Hint

Common Mistakes

Using positive indices includes those elements instead of excluding them.

Using -c(1, 3) excludes the first and third elements from the vector.

3fill in blank

hard

Fix the error in the code to exclude the last element from the vector.

R Programming

vec <- c(2, 4, 6, 8)
result <- vec[[1]]
print(result)

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Ac(length(vec))

Blength(vec)

C-length(vec)

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using positive length(vec) includes only the last element instead of excluding it.

Using -length(vec) excludes the last element by negative indexing with the vector length.

4fill in blank

hard

Fill both blanks to exclude the second and fourth elements from the vector.

R Programming

vec <- c(3, 6, 9, 12, 15)
result <- vec[[1]([2])]
print(result)

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

A-c

Bc

C2, 4

D1, 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using positive indices includes elements instead of excluding them.

Using -c(2, 4) excludes the second and fourth elements from the vector.

5fill in blank

hard

Fill all three blanks to exclude the first, third, and fifth elements from the vector.

R Programming

vec <- c(7, 14, 21, 28, 35, 42)
result <- vec[[1]([2])]
print(result)

# The excluded elements are [3].

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

A-c

Bc

C1, 3, 5

D7, 21, 35

Attempts:

3 left

💡 Hint

Common Mistakes

Using positive indices includes elements instead of excluding them.

Using -c(1, 3, 5) excludes the first, third, and fifth elements, which are 7, 21, and 35.

Practice

1. In R, what does negative indexing like x[-2] do to the vector x?

easy

A. It returns the vector x with the second element doubled.

B. It returns only the second element of x.

C. It returns the vector x without the second element.

D. It causes an error because negative indexes are not allowed.

Solution

1. Step 1: Understand negative indexing in R

   Negative indexing excludes elements at the specified positions from the result.

2. Step 2: Apply negative index to x[-2]

   This means the second element is removed from the vector x, returning all others.

3. Final Answer:

   It returns the vector x without the second element. -> Option C

4. Quick Check:

   Negative index excludes elements [OK]

Hint: Negative index removes elements by position [OK]

Common Mistakes:

• Thinking negative index selects elements
• Confusing negative index with subtraction
• Assuming negative index causes error

2. Which of the following is the correct syntax to exclude the 1st and 3rd elements from a vector v in R?

easy

A. v[-c(1, 3)]

B. v[c(-1, 3)]

C. v[c(1, -3)]

D. v[-1, -3]

Solution

1. Step 1: Recall syntax for excluding multiple elements

   Use negative indexing with a vector of positions inside c(), like -c(1, 3).

2. Step 2: Check each option

   v[-c(1, 3)] correctly uses v[-c(1, 3)] to exclude 1st and 3rd elements. Others misuse negative signs or commas.

3. Final Answer:

   v[-c(1, 3)] -> Option A

4. Quick Check:

   Negative vector inside c() excludes multiple elements [OK]

Hint: Use negative vector inside c() to exclude multiple elements [OK]

Common Mistakes:

• Placing negative signs inside c() incorrectly
• Using commas instead of c() for multiple indexes
• Mixing positive and negative indexes in one vector

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

vec <- c(10, 20, 30, 40, 50)
result <- vec[-c(2, 4)]
print(result)

medium

A. [1] 20 40

B. [1] 10 30 50

C. [1] 10 20 30 40 50

D. [1] 30 50

Solution

1. Step 1: Identify elements to exclude

   Negative indexing -c(2, 4) removes elements at positions 2 and 4, which are 20 and 40.

2. Step 2: List remaining elements

   Remaining elements are at positions 1, 3, and 5: 10, 30, and 50.

3. Final Answer:

   [1] 10 30 50 -> Option B

4. Quick Check:

   Exclude 2nd and 4th elements [OK]

Hint: Remove elements at given positions with negative c() [OK]

Common Mistakes:

• Including excluded elements by mistake
• Confusing element values with positions
• Expecting only excluded elements as output

4. Consider this R code snippet:

nums <- c(5, 10, 15, 20)
new_nums <- nums[-2, 3]
print(new_nums)

What is the error in this code?

medium

A. Incorrect use of comma in negative indexing causing subscript error.

B. Negative indexing cannot be used with numeric vectors.

C. The vector nums is empty, so indexing fails.

D. The code runs without error and prints the vector.

Solution

1. Step 1: Analyze the indexing syntax

   Negative indexing uses a single vector inside brackets. Using a comma like nums[-2, 3] implies matrix indexing, which is invalid for a vector.

2. Step 2: Identify the error type

   This causes a subscript error because nums is a vector, not a matrix or data frame.

3. Final Answer:

   Incorrect use of comma in negative indexing causing subscript error. -> Option A

4. Quick Check:

   Comma in vector indexing causes error [OK]

Hint: No commas in vector negative indexing [OK]

Common Mistakes:

• Using commas like in matrices for vectors
• Assuming negative indexing works with multiple arguments
• Ignoring error messages about subscripts

5. You have a vector data <- c(3, 6, 9, 12, 15, 18). You want to create a new vector excluding all elements at even positions using negative indexing. Which code correctly achieves this?

hard

A. new_data <- data[-seq(1, length(data), by=2)]

B. new_data <- data[-c(2, 4, 6, 8)]

C. new_data <- data[-c(1, 3, 5)]

D. new_data <- data[-seq(2, length(data), by=2)]

Solution

1. Step 1: Identify even positions in the vector

   Even positions are 2, 4, 6. Using seq(2, length(data), by=2) generates these positions dynamically.

2. Step 2: Use negative indexing to exclude these positions

   Applying negative indexing with -seq(2, length(data), by=2) removes elements at even positions.

3. Final Answer:

   new_data <- data[-seq(2, length(data), by=2)] -> Option D

4. Quick Check:

   Negative seq() excludes even positions [OK]

Hint: Use seq() with negative index to exclude positions [OK]

Common Mistakes:

• Hardcoding indexes without checking vector length
• Excluding odd positions instead of even
• Using indexes outside vector length