R Tutorial

Factors in R

Factors are used to handle categorical data in R. They are stored as vectors of integers with labels. Factors are useful for representing variables like gender, status, category, grade, etc., which have a fixed number of possible values (called levels).

Creating Factors

# Create a factor for gender
gender <- factor(c("Male", "Female", "Female", "Male", "Male"))

# Display factor
print(gender)
  

Output:

[1] Male   Female Female Male   Male  
Levels: Female Male
  

Checking Levels

You can view the levels of a factor using:

levels(gender)
  

Setting Order of Levels

Some categories are ordered (e.g., grades or sizes). You can define that using ordered = TRUE:

grades <- factor(c("B", "A", "C", "A", "B"), 
                 levels = c("C", "B", "A"),
                 ordered = TRUE)

print(grades)
  

Comparing Ordered Factors

You can compare ordered factors:

grades[2] > grades[1]   # TRUE because A > B in defined order
  

Converting to Factor

x <- c("yes", "no", "yes", "yes", "no")
f <- as.factor(x)
  

Converting Factor to Character or Numeric

as.character(f)   # Convert to text
as.numeric(f)     # Convert to level index (e.g., 2 1 2 2 1)
  

Why Use Factors?

• Efficient storage of categorical data.
• Useful for statistical modeling and plotting.
• Enforces valid category values via levels.

Practice Exercises

• Create a factor of "Yes" and "No" survey responses.
• Create an ordered factor of sizes: "Small", "Medium", "Large".
• Check the number of levels using nlevels().
• Compare two values from an ordered factor.
• Convert a factor into a character vector.