What does the Command 'imputer.fit(doubles_df)' accomplish in a machine learning context?

The command 'imputer.fit(doubles_df)' is used to apply the imputer to the specified dataset, in this case, 'doubles_df'. The purpose of this command is to learn the parameters necessary for handling missing values in the dataset. During the fitting process, the imputer examines the data in 'doubles_df' to determine how to replace or fill in the missing values. This could involve calculating the mean, median, or mode of each column (depending on the strategy employed by the imputer) and storing this information for later transformation of the dataset.

Once the imputer has been fitted, it can then be used to transform the dataset by applying the learned parameters to replace the missing values, effectively enabling a more complete dataset for further analysis or model training. Thus, the action of fitting the imputer is a crucial step in preparing the data for use in machine learning workflows. This step precedes any transformations, which would happen afterward with a ‘transform’ method.