def unique(self):
result = super().unique()<EOL>return result<EOL>
Return unique values of Series object.

Uniques are returned in order of appearance. Hash table-based unique,
therefore does NOT sort.

Returns
-------
ndarray or ExtensionArray
    The unique values returned as a NumPy array. See Notes.

See Also
--------
unique : Top-level unique method for any 1-d array-like object.
Index.unique : Return Index with unique values from an Index object.

Notes
-----
Returns the unique values as a NumPy array. In case of an
extension-array backed Series, a new
:class:`~api.extensions.ExtensionArray` of that type with just
the unique values is returned. This includes

    * Categorical
    * Period
    * Datetime with Timezone
    * Interval
    * Sparse
    * IntegerNA

See Examples section.

Examples
--------
>>> pd.Series([2, 1, 3, 3], name='A').unique()
array([2, 1, 3])

>>> pd.Series([pd.Timestamp('2016-01-01') for _ in range(3)]).unique()
array(['2016-01-01T00:00:00.000000000'], dtype='datetime64[ns]')

>>> pd.Series([pd.Timestamp('2016-01-01', tz='US/Eastern')
...            for _ in range(3)]).unique()
<DatetimeArray>
['2016-01-01 00:00:00-05:00']
Length: 1, dtype: datetime64[ns, US/Eastern]

An unordered Categorical will return categories in the order of
appearance.

>>> pd.Series(pd.Categorical(list('baabc'))).unique()
[b, a, c]
Categories (3, object): [b, a, c]

An ordered Categorical preserves the category ordering.

>>> pd.Series(pd.Categorical(list('baabc'), categories=list('abc'),
...                          ordered=True)).unique()
[b, a, c]
Categories (3, object): [a < b < c]