Categorical variables are types of data that represent distinct categories or groups. Unlike numerical variables, which can take on a wide range of values, categorical variables have a limited number of possible values. For example, survey responses about favorite colors or types of vehicles owned fall into specific categories such as “Red,” “Blue,” “Honda,” or “Toyota.” These variables are essential in data analysis and machine learning, as they help in classifying and understanding data patterns. However, they require preprocessing before being used in most machine learning models to avoid errors during analysis.