SeriesGroupBy.nsmallest Return the smallest n elements.
| Parameters: | 
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| Returns: | 
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See also
Series.nlargest n largest elements.Series.sort_values Series.head n rows.Faster than .sort_values().head(n) for small n relative to the size of the Series object.
>>> 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
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    https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.core.groupby.SeriesGroupBy.nsmallest.html