Releveling factors in R Programming - Mini Project: Build & Apply

Releveling Factors in R

📖 Scenario: Imagine you have survey data where people's favorite fruits are recorded as categories. You want to change the order of these categories to make "Banana" the first choice for analysis.

🎯 Goal: You will create a factor variable with fruit names, then relevel it so that "Banana" is the first level.

📋 What You'll Learn

Create a factor variable called fruits with the values: "Apple", "Banana", "Cherry", "Date", "Banana"

Create a variable called new_first_level and set it to "Banana"

Use the relevel() function to create a new factor called fruits_releveled with new_first_level as the first level

Print the levels of fruits_releveled to show the new order

💡 Why This Matters

🌍 Real World

Releveling factors is useful when you want to change the reference category in surveys, experiments, or any categorical data analysis.

💼 Career

Data analysts and statisticians often need to reorder factor levels to control how models interpret categorical variables or how plots display categories.

1

Create the factor variable

Create a factor variable called fruits with these exact values in order: "Apple", "Banana", "Cherry", "Date", "Banana"

R Programming

# Create the factor variable fruits with the specified values
# Your code here

Hint

Use the factor() function with a vector of fruit names.

2

Set the new first level

Create a variable called new_first_level and set it to the string "Banana"

R Programming

fruits <- factor(c("Apple", "Banana", "Cherry", "Date", "Banana"))
# Create new_first_level variable and assign "Banana"
# Your code here

Hint

Just assign the string "Banana" to the variable new_first_level.

3

Relevel the factor

Use the relevel() function to create a new factor called fruits_releveled by releveling fruits with the first level set to new_first_level

R Programming

fruits <- factor(c("Apple", "Banana", "Cherry", "Date", "Banana"))
new_first_level <- "Banana"
# Create fruits_releveled by releveling fruits with new_first_level
# Your code here

Hint

Use relevel(fruits, ref = new_first_level) to change the first level.

4

Print the new levels

Print the levels of fruits_releveled using the levels() function

R Programming

fruits <- factor(c("Apple", "Banana", "Cherry", "Date", "Banana"))
new_first_level <- "Banana"
fruits_releveled <- relevel(fruits, ref = new_first_level)
# Print the levels of fruits_releveled
# Your code here

Hint

Use print(levels(fruits_releveled)) to see the new order of levels.

Practice

1. What does the relevel() function do in R when working with factors?

easy

A. It changes the reference level of a factor to a specified category.

B. It converts a factor into a numeric vector.

C. It sorts the levels of a factor alphabetically.

D. It removes unused levels from a factor.

Solution

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

   The relevel() function is used to set a new baseline or reference level for a factor in R.

2. Step 2: Identify what changing the reference level means

   Changing the reference level means selecting which category is treated as the baseline for comparisons or modeling.

3. Final Answer:

   It changes the reference level of a factor to a specified category. -> Option A

4. Quick Check:

   relevel() sets new baseline [OK]

Hint: Remember: relevel() sets the baseline category [OK]

Common Mistakes:

• Thinking relevel() converts factor to numeric
• Confusing relevel() with sorting levels
• Assuming relevel() removes unused levels

2. Which of the following is the correct syntax to set the reference level of a factor f to "Control" using relevel()?

easy

A. relevel(f, reference = "Control")

B. relevel(f, level = "Control")

C. relevel(f, base = "Control")

D. relevel(f, ref = "Control")

Solution

1. Step 1: Recall the argument name for reference level in relevel()

   The correct argument to specify the new reference level is ref.

2. Step 2: Match the syntax with the argument

   Only relevel(f, ref = "Control") uses the correct argument name and syntax.

3. Final Answer:

   relevel(f, ref = "Control") -> Option D

4. Quick Check:

   Argument for reference is ref = "Control" [OK]

Hint: Use ref= to set new baseline in relevel() [OK]

Common Mistakes:

• Using incorrect argument names like level or base
• Forgetting quotes around the reference level
• Using assignment instead of argument syntax

3. Given the code:

f <- factor(c("Low", "Medium", "High", "Low"))
f_new <- relevel(f, ref = "High")
levels(f_new)

What is the output of levels(f_new)?

medium

A. ["High", "Low", "Medium"]

B. ["Low", "Medium", "High"]

C. ["Medium", "Low", "High"]

D. ["High", "Medium", "Low"]

Solution

1. Step 1: Understand original factor levels

   Original levels are in alphabetical order: "High", "Low", "Medium".

2. Step 2: Effect of relevel(f, ref = "High")

   Relevel moves "High" to be the first (reference) level, keeping others in original order after it.

3. Final Answer:

   ["High", "Low", "Medium"] -> Option A

4. Quick Check:

   Reference level first = ["High", "Low", "Medium"] [OK]

Hint: Reference level appears first in levels() output [OK]

Common Mistakes:

• Assuming levels reorder alphabetically after relevel
• Confusing order of levels after relevel
• Expecting levels to be unchanged

4. Consider this code snippet:

f <- factor(c("A", "B", "C"))
f_new <- relevel(f, ref = "D")
levels(f_new)

What will happen when this code runs?

medium

A. ["A", "B", "C"] unchanged because "D" is ignored.

B. ["D", "A", "B", "C"] as new levels with "D" added.

C. An error because "D" is not a level in the factor.

D. Levels reordered alphabetically without error.

Solution

1. Step 1: Check if "D" is a level in factor f

   Levels are "A", "B", "C"; "D" is not present.

2. Step 2: Behavior of relevel() with invalid ref

   relevel() throws an error if the reference level is not in the factor levels.

3. Final Answer:

   An error because "D" is not a level in the factor. -> Option C

4. Quick Check:

   Invalid ref level causes error [OK]

Hint: Reference must exist in levels or error occurs [OK]

Common Mistakes:

• Assuming relevel adds new levels automatically
• Expecting no error and unchanged levels
• Thinking levels reorder alphabetically silently

5. You have a factor f with levels "Red", "Green", "Blue". You want to set "Green" as the reference level and then create a summary table counting each level's occurrences using the summary() function. Which code correctly does this?

hard

A. f_new <- relevel(f, ref = "Green")
table(f_new)

B. f_new <- relevel(f, ref = "Green")
summary(f_new)

C. f_new <- relevel(f, ref = "Green")
table(f)

D. f_new <- relevel(f, ref = "Green")
summary(f)

Solution

1. Step 1: Relevel factor to set "Green" as reference

   Use f_new <- relevel(f, ref = "Green") to create a new factor with "Green" first.

2. Step 2: Use summary() on the re-leveled factor

   Calling summary(f_new) counts occurrences of each level in the updated factor.

3. Final Answer:

   f_new <- relevel(f, ref = "Green") summary(f_new) -> Option B

4. Quick Check:

   summary() on re-leveled factor gives counts [OK]

Hint: Use summary() on re-leveled factor for counts [OK]

Common Mistakes:

• Using summary() on original factor after relevel
• Using table() on original factor instead of new
• Not assigning relevel result to new variable