A substantial aspect of any robust data analysis pipeline is handling null values. These instances, often represented as NULL, can severely impact machine learning models and insights. Ignoring these values can lead to skewed results and incorrect conclusions. Strategies for addressing absent data include imputation with median values, deletion of