code: def drop_duplicates(self, keep='first', inplace=False):
          
          return super().drop_duplicates(keep=keep, inplace=inplace)
docs: 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