A significant aspect of any effective data analysis pipeline is managing absent values. These situations, often represented as N/A, can severely impact machine learning models and data visualization. Ignoring these values can lead to inaccurate results and incorrect conclusions. Strategies for addressing absent data include imputation with mean val