If there are missing values and outliers in the data, firstly, we'll take care of the outliers by applying various methods to make them lie within the range and not make them an outlier. And secondly, we're going to find the mean of all the data in the datasets and then fill them in the gaps of the missing values in the dataset and the table. That is how I would approach it if I was in a scenario like that.
