Compute the min, max and median for all columns in the DataFrame. For more information,
            please see the :func:`~tsfresh.utilities.dataframe_functions.get_range_values_per_column` function.

            :param X: DataFrame to calculate min, max and median values on
            :type X: pandas.DataFrame
            :param y: Unneeded.
            :type y: Any

            :return: the estimator with the computed min, max and median values
            :rtype: Imputer

def fit(self, X, y=None):
            """
            Compute the min, max and median for all columns in the DataFrame. For more information,
            please see the :func:`~tsfresh.utilities.dataframe_functions.get_range_values_per_column` function.

            :param X: DataFrame to calculate min, max and median values on
            :type X: pandas.DataFrame
            :param y: Unneeded.
            :type y: Any

            :return: the estimator with the computed min, max and median values
            :rtype: Imputer
            """
            if not isinstance(X, pd.DataFrame):
                X = pd.DataFrame(X)

            col_to_max, col_to_min, col_to_median = get_range_values_per_column(X)

            if self.col_to_NINF_repl_preset is not None:
                if not set(X.columns) >= set(self.col_to_NINF_repl_preset.keys()):
                    raise ValueError("Preset dictionary 'col_to_NINF_repl_preset' contain more keys "
                                     "than the column names in X")
                col_to_min.update(self.col_to_NINF_repl_preset)
            self._col_to_NINF_repl = col_to_min

            if self.col_to_PINF_repl_preset is not None:
                if not set(X.columns) >= set(self.col_to_PINF_repl_preset.keys()):
                    raise ValueError("Preset dictionary 'col_to_PINF_repl_preset' contain more keys "
                                     "than the column names in X")
                col_to_max.update(self.col_to_PINF_repl_preset)
            self._col_to_PINF_repl = col_to_max

            if self.col_to_NAN_repl_preset is not None:
                if not set(X.columns) >= set(self.col_to_NAN_repl_preset.keys()):
                    raise ValueError("Preset dictionary 'col_to_NAN_repl_preset' contain more keys "
                                     "than the column names in X")
                col_to_median.update(self.col_to_NAN_repl_preset)
            self._col_to_NAN_repl = col_to_median

            return self