lue can be one of:

            ``'table'``
                Table format. Write as a PyTables Table structure which may perform
                worse but allow more flexible operations like searching / selecting
                subsets of the data.
        index : bool, default True
            Write DataFrame index as a column.
        append       : bool, default True
            Append the input data to the existing.
        data_columns : list of columns, or True, default None
            List of columns to create as indexed data columns for on-disk
            queries, or True to use all columns. By default only the axes
            of the object are indexed. See `here
            <https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#query-via-data-columns>`__.
        min_itemsize : dict of columns that specify minimum str sizes
        nan_rep      : str to use as str nan representation
        chunksize    : size to chunk the writing
        expectedrows : expected TOTAL row size of this table
        encoding     : default None, provide an encoding for str
        dropna : bool, default False, optional
            Do not write an ALL nan row to the store settable
            by the option 'io.hdf.dropna_table'.

        Notes
        -----
        Does *not* check if data being appended overlaps with existing
        data in the table, so be careful
        Nz>columns is not a supported keyword in append, try data_columnsz