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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 validate_data_columns(self, data_columns, min_itemsize):
 """take the input data_columns and min_itemize and create a data columns spec """


        if not len(self.non_index_axes):
            return []

        axis, axis_labels = self.non_index_axes[0]
        info = self.info.get(axis, dict())
        if info.get('type') == 'MultiIndex' and data_columns:
            raise ValueError("cannot use a multi-index on axis [{0}] with "
                             "data_columns {1}".format(axis, data_columns))

        # evaluate the passed data_columns, True == use all columns
        # take only valide axis labels
        if data_columns is True:
            data_columns = list(axis_labels)
        elif data_columns is None:
            data_columns = []

        # if min_itemsize is a dict, add the keys (exclude 'values')
        if isinstance(min_itemsize, dict):

            existing_data_columns = set(data_columns)
            data_columns.extend([
                k for k in min_itemsize.keys()
                if k != 'values' and k not in existing_data_columns
            ])

        # return valid columns in the order of our axis
        return [c for c in data_columns if c in axis_labels]