def nlargest(self, n=<NUM_LIT:5>, keep='<STR_LIT>'):
return algorithms.SelectNSeries(self, n=n, keep=keep).nlargest()<EOL>
Return the largest `n` elements.

Parameters
----------
n : int, default 5
    Return this many descending sorted values.
keep : {'first', 'last', 'all'}, default 'first'
    When there are duplicate values that cannot all fit in a
    Series of `n` elements:

    - ``first`` : return the first `n` occurrences in order
        of appearance.
    - ``last`` : return the last `n` occurrences in reverse
        order of appearance.
    - ``all`` : keep all occurrences. This can result in a Series of
        size larger than `n`.

Returns
-------
Series
    The `n` largest values in the Series, sorted in decreasing order.

See Also
--------
Series.nsmallest: Get the `n` smallest elements.
Series.sort_values: Sort Series by values.
Series.head: Return the first `n` rows.

Notes
-----
Faster than ``.sort_values(ascending=False).head(n)`` for small `n`
relative to the size of the ``Series`` object.

Examples
--------
>>> countries_population = {"Italy": 59000000, "France": 65000000,
...                         "Malta": 434000, "Maldives": 434000,
...                         "Brunei": 434000, "Iceland": 337000,
...                         "Nauru": 11300, "Tuvalu": 11300,
...                         "Anguilla": 11300, "Monserat": 5200}
>>> s = pd.Series(countries_population)
>>> s
Italy       59000000
France      65000000
Malta         434000
Maldives      434000
Brunei        434000
Iceland       337000
Nauru          11300
Tuvalu         11300
Anguilla       11300
Monserat        5200
dtype: int64

The `n` largest elements where ``n=5`` by default.

>>> s.nlargest()
France      65000000
Italy       59000000
Malta         434000
Maldives      434000
Brunei        434000
dtype: int64

The `n` largest elements where ``n=3``. Default `keep` value is 'first'
so Malta will be kept.

>>> s.nlargest(3)
France    65000000
Italy     59000000
Malta       434000
dtype: int64

The `n` largest elements where ``n=3`` and keeping the last duplicates.
Brunei will be kept since it is the last with value 434000 based on
the index order.

>>> s.nlargest(3, keep='last')
France      65000000
Italy       59000000
Brunei        434000
dtype: int64

The `n` largest elements where ``n=3`` with all duplicates kept. Note
that the returned Series has five elements due to the three duplicates.

>>> s.nlargest(3, keep='all')
France      65000000
Italy       59000000
Malta         434000
Maldives      434000
Brunei        434000
dtype: int64