Programming 101: Types of Data in R

Overview

• Focus on five main types of data in R
• Discuss changing data types for variables
• Learn how to add levels to a factor

Major Types of Data

1. Nominal Data (Character)

   • Example: Name (text data)

2. Ordinal Data (Factor)

   • Example: Height (categorical data with order)
   • Levels need to be defined

3. Integer

   • Example: Age (whole number)

4. Numeric

   • Example: Weight (can be any number, including decimals)

5. Logical

   • Represents true/false conditions

Changing Data Types

• To check the structure of a data frame:
  • Use the command str(friends)
• Changing height from character to factor:
  • Use friends$height <- as.factor(friends$height)
• Changing age from numeric to integer:
  • Use friends$age <- as.integer(friends$age)

Understanding Factors

• Factors represent categorical data with levels
• By default, R orders factor levels alphabetically
• To change factor levels, use:
  • friends$height <- factor(friends$height, levels = c('short', 'medium', 'tall'))

Creating Logical Variables

• A logical variable can be created by comparing values:
  • Example:
    • old <- friends$age > 23
• This results in a logical vector of true/false values

Conclusion

• These five types of data are essential for data analysis in R
• Other types of data exist (e.g., date/time) but are less commonly used
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