def duplicated(self, keep='<STR_LIT>'):
return super().duplicated(keep=keep)<EOL>
Indicate duplicate index values.

Duplicated values are indicated as ``True`` values in the resulting
array. Either all duplicates, all except the first, or all except the
last occurrence of duplicates can be indicated.

Parameters
----------
keep : {'first', 'last', False}, default 'first'
    The value or values in a set of duplicates to mark as missing.

    - 'first' : Mark duplicates as ``True`` except for the first
      occurrence.
    - 'last' : Mark duplicates as ``True`` except for the last
      occurrence.
    - ``False`` : Mark all duplicates as ``True``.

Returns
-------
numpy.ndarray

See Also
--------
Series.duplicated : Equivalent method on pandas.Series.
DataFrame.duplicated : Equivalent method on pandas.DataFrame.
Index.drop_duplicates : Remove duplicate values from Index.

Examples
--------
By default, for each set of duplicated values, the first occurrence is
set to False and all others to True:

>>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama'])
>>> idx.duplicated()
array([False, False,  True, False,  True])

which is equivalent to

>>> idx.duplicated(keep='first')
array([False, False,  True, False,  True])

By using 'last', the last occurrence of each set of duplicated values
is set on False and all others on True:

>>> idx.duplicated(keep='last')
array([ True, False,  True, False, False])

By setting keep on ``False``, all duplicates are True:

>>> idx.duplicated(keep=False)
array([ True, False,  True, False,  True])