Description: Variable replacement is the process of substituting one variable for another in a dataset. This procedure is fundamental in data preprocessing, as it allows for the transformation and cleaning of information to facilitate analysis. By replacing variables, the aim is to improve data quality, eliminate redundancies or inconsistencies, and make the information more comprehensible and useful for analytical models. This process may include converting categorical variables into numerical variables, normalizing values, or substituting missing values with estimates based on other variables. Proper implementation of variable replacement is crucial, as poor substitution can lead to misinterpretations and affect the validity of the results obtained in data analysis. In summary, variable replacement is an essential technique in data preparation that optimizes the quality and utility of information for subsequent analysis.
