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

Parameters
----------
n : int, default 5
    Return this many ascending 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` smallest values in the Series, sorted in increasing order.

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

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

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

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

>>> s.nsmallest()
Monserat      5200
Nauru        11300
Tuvalu       11300
Anguilla     11300
Iceland     337000
dtype: int64

The `n` smallest elements where ``n=3``. Default `keep` value is
'first' so Nauru and Tuvalu will be kept.

>>> s.nsmallest(3)
Monserat     5200
Nauru       11300
Tuvalu      11300
dtype: int64

The `n` smallest elements where ``n=3`` and keeping the last
duplicates. Anguilla and Tuvalu will be kept since they are the last
with value 11300 based on the index order.

>>> s.nsmallest(3, keep='last')
Monserat     5200
Anguilla    11300
Tuvalu      11300
dtype: int64

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

>>> s.nsmallest(3, keep='all')
Monserat     5200
Nauru       11300
Tuvalu      11300
Anguilla    11300
dtype: int64