dentify each element of the
        underlying data. The index can be thought of as an immutable ordered set
        (technically a multi-set, as it may contain duplicate labels), and is
        used to index and align data in pandas.

        Returns
        -------
        Index
            The index labels of the Series.

        See Also
        --------
        Series.reindex : Conform Series to new index.
        Series.set_index : Set Series as DataFrame index.
        Index : The base pandas index type.

        Notes
        -----
        For more information on pandas indexing, see the `indexing user guide
        <https://pandas.pydata.org/docs/user_guide/indexing.html>`__.

        Examples
        --------
        To create a Series with a custom index and view the index labels:

        >>> cities = ['Kolkata', 'Chicago', 'Toronto', 'Lisbon']
        >>> populations = [14.85, 2.71, 2.93, 0.51]
        >>> city_series = pd.Series(populations, index=cities)
        >>> city_series.index
        Index(['Kolkata', 'Chicago', 'Toronto', 'Lisbon'], dtype='object')

        To change the index labels of an existing Series:

        >>> city_series.index = ['KOL', 'CHI', 'TOR', 'LIS']
        >>> city_series.index
        Index(['KOL', 'CHI', 'TOR', 'LIS'], dtype='object')
        )