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A data scientist is tasked with preparing datasets for an ML project. The datasets contain missing values, duplicate records, and outliers. The data scientist must clean and consolidate these datasets into a single data frame, ensuring the data is properly prepared for training a machine learning model. What is the most efficient approach to address these requirements?