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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 get_data(self):
 """Get the raw data of the Dataset. Returns ------- data : string, numpy array, pandas DataFrame, H2O DataTable's Frame, scipy.sparse, list of numpy arrays or None Raw data used in the Dataset construction. """

        if self.handle is None:
            raise Exception("Cannot get data before construct Dataset")
        if self.data is not None and self.used_indices is not None and self.need_slice:
            if isinstance(self.data, np.ndarray) or scipy.sparse.issparse(self.data):
                self.data = self.data[self.used_indices, :]
            elif isinstance(self.data, DataFrame):
                self.data = self.data.iloc[self.used_indices].copy()
            elif isinstance(self.data, DataTable):
                self.data = self.data[self.used_indices, :]
            else:
                warnings.warn("Cannot subset {} type of raw data.\n"
                              "Returning original raw data".format(type(self.data).__name__))
            self.need_slice = False
        return self.data