Return Series with duplicate values removed.

        Parameters
        ----------
        keep : {'first', 'last', ``False``}, default 'first'
            - 'first' : Drop duplicates except for the first occurrence.
            - 'last' : Drop duplicates except for the last occurrence.
            - ``False`` : Drop all duplicates.
        inplace : bool, default ``False``
            If ``True``, performs operation inplace and returns None.

        Returns
        -------
        Series
            Series with duplicates dropped.

        See Also
        --------
        Index.drop_duplicates : Equivalent method on Index.
        DataFrame.drop_duplicates : Equivalent method on DataFrame.
        Series.duplicated : Related method on Series, indicating duplicate
            Series values.

        Examples
        --------
        Generate an Series with duplicated entries.

        >>> s = pd.Series(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'],
        ...               name='animal')
        >>> s
        0      lama
        1       cow
        2      lama
        3    beetle
        4      lama
        5     hippo
        Name: animal, dtype: object

        With the 'keep' parameter, the selection behaviour of duplicated values
        can be changed. The value 'first' keeps the first occurrence for each
        set of duplicated entries. The default value of keep is 'first'.

        >>> s.drop_duplicates()
        0      lama
        1       cow
        3    beetle
        5     hippo
        Name: animal, dtype: object

        The value 'last' for parameter 'keep' keeps the last occurrence for
        each set of duplicated entries.

        >>> s.drop_duplicates(keep='last')
        1       cow
        3    beetle
        4      lama
        5     hippo
        Name: animal, dtype: object

        The value ``False`` for parameter 'keep' discards all sets of
        duplicated entries. Setting the value of 'inplace' to ``True`` performs
        the operation inplace and returns ``None``.

        >>> s.drop_duplicates(keep=False, inplace=True)
        >>> s
        1       cow
        3    beetle
        5     hippo
        Name: animal, dtype: object

def drop_duplicates(self, keep='first', inplace=False):
        """
        Return Series with duplicate values removed.

        Parameters
        ----------
        keep : {'first', 'last', ``False``}, default 'first'
            - 'first' : Drop duplicates except for the first occurrence.
            - 'last' : Drop duplicates except for the last occurrence.
            - ``False`` : Drop all duplicates.
        inplace : bool, default ``False``
            If ``True``, performs operation inplace and returns None.

        Returns
        -------
        Series
            Series with duplicates dropped.

        See Also
        --------
        Index.drop_duplicates : Equivalent method on Index.
        DataFrame.drop_duplicates : Equivalent method on DataFrame.
        Series.duplicated : Related method on Series, indicating duplicate
            Series values.

        Examples
        --------
        Generate an Series with duplicated entries.

        >>> s = pd.Series(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'],
        ...               name='animal')
        >>> s
        0      lama
        1       cow
        2      lama
        3    beetle
        4      lama
        5     hippo
        Name: animal, dtype: object

        With the 'keep' parameter, the selection behaviour of duplicated values
        can be changed. The value 'first' keeps the first occurrence for each
        set of duplicated entries. The default value of keep is 'first'.

        >>> s.drop_duplicates()
        0      lama
        1       cow
        3    beetle
        5     hippo
        Name: animal, dtype: object

        The value 'last' for parameter 'keep' keeps the last occurrence for
        each set of duplicated entries.

        >>> s.drop_duplicates(keep='last')
        1       cow
        3    beetle
        4      lama
        5     hippo
        Name: animal, dtype: object

        The value ``False`` for parameter 'keep' discards all sets of
        duplicated entries. Setting the value of 'inplace' to ``True`` performs
        the operation inplace and returns ``None``.

        >>> s.drop_duplicates(keep=False, inplace=True)
        >>> s
        1       cow
        3    beetle
        5     hippo
        Name: animal, dtype: object
        """
        return super().drop_duplicates(keep=keep, inplace=inplace)