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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def describe(self, **kwargs):
 """Generates descriptive statistics. Returns: DataFrame object containing the descriptive statistics of the DataFrame. """

        # Use pandas to calculate the correct columns
        new_columns = (
            pandas.DataFrame(columns=self.columns)
            .astype(self.dtypes)
            .describe(**kwargs)
            .columns
        )

        def describe_builder(df, internal_indices=[], **kwargs):
            return df.iloc[:, internal_indices].describe(**kwargs)

        # Apply describe and update indices, columns, and dtypes
        func = self._prepare_method(describe_builder, **kwargs)
        new_data = self._full_axis_reduce_along_select_indices(func, 0, new_columns)
        new_index = self.compute_index(0, new_data, False)
        return self.__constructor__(new_data, new_index, new_columns)