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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 __add_target_data(self, transformed_data, original_data):
 """ Picks up the target data from the original_data and appends it as a column to the transformed_data. Both arguments are expected to be np.array's. """

        model = self.__config.get_data_model()
        target_feature = model.find_target_feature()
        name = target_feature.get_name()

        if target_feature.is_categorical():
            target_row = original_data[name]
            target = self.__label_encoder_adapter.transform(target_row)
        else:
            target = original_data[name].values.astype(type_name_to_data_type("float"))

        target = target[..., None]

        return np.hstack((transformed_data, target))