Negative indexing for exclusion in R Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does negative indexing do in R when used with vectors?

Negative indexing in R excludes elements at the specified positions from a vector. For example, x[-2] returns all elements except the second one.

beginner

How do you exclude multiple elements from a vector using negative indexing?

You provide a vector of negative indices. For example, x[-c(1,3)] excludes the first and third elements from x.

intermediate

What happens if you mix positive and negative indices in R when subsetting a vector?

R will give an error because you cannot mix positive and negative indices in the same subset operation.

beginner

Example: Given x <- c(10, 20, 30, 40), what is the result of x[-2]?

The result is c(10, 30, 40) because the second element (20) is excluded.

beginner

Why is negative indexing useful in data manipulation?

It allows you to quickly remove unwanted elements without creating a new vector or using complex functions.

What does x[-1] do in R if x is a vector?

A Causes an error

B Returns only the first element

C Returns the vector unchanged

D Returns all elements except the first one

Negative indexing excludes the element at that position, so x[-1] excludes the first element.

Which of these is a valid way to exclude the 2nd and 4th elements from a vector x?

A x[-c(2,4)]

B x[c(-2,-4)]

C x[c(2,4)]

D x[-2,4]

Only C: x[-c(2,4)] is a valid way to exclude the 2nd and 4th elements. A selects them instead. B is invalid because mixing negative indices inside c() is not allowed. D is invalid syntax for vector indexing.

What happens if you try x[c(1, -2)] in R?

A Returns elements 1 and excludes 2

B Gives an error

C Returns all elements

D Returns elements 1 and 2

Mixing positive and negative indices in the same subset causes an error.

If x <- c(5, 10, 15, 20), what is x[-3]?

A c(5, 10, 20)

B c(5, 10, 15)

C c(15, 20)

D c(10, 15, 20)

x[-3] excludes the third element (15), so the result is c(5, 10, 20).

Why might you use negative indexing instead of positive indexing?

A To reverse the vector

B To select only the first element

C To exclude unwanted elements easily

D To sort the vector

Negative indexing is a quick way to exclude elements without specifying all the ones you want.

Explain how negative indexing works in R and give an example.

Think about removing elements by position.

What error occurs if you mix positive and negative indices in R? Why?

Consider how R expects indexing to be consistent.

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