Example Concept: Imputation is a common method for handling missing data, where missing values are filled in using statistical techniques. Simple imputation methods include filling with the mean, median, or mode of the column, while more sophisticated methods involve using predictive models like k-nearest neighbors or regression to estimate missing values. These approaches help retain the dataset's size and can improve model accuracy if done correctly.