Categorical Variable

In data science, a categorical variable is a variable that can take on one of a limited, and usually fixed, number of possible values, known as categories or levels. These categories can be nominal, ordinal, or binary. Nominal categories are those that do not have any inherent order or ranking, such as colors or types of animals. Ordinal categories have a natural order or ranking, such as education level or income bracket. Binary categories have only two possible values, such as yes/no or true/false. Categorical variables are often used in statistical analysis to group data into meaningful subsets based on shared characteristics. They can also be used as predictors in machine learning models, where they are typically converted into numerical values through a process called encoding.
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