Return the smallest n elements.
Return this many ascending sorted values.
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.
The n smallest values in the Series, sorted in increasing order.
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, "Montserrat": 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
Montserrat 5200
dtype: int64
The n smallest elements where n=5 by default.
>>> s.nsmallest() Montserrat 5200 Nauru 11300 Tuvalu 11300 Anguilla 11300 Iceland 337000 dtype: int64
The n smallest elements where n=3. Default keep value is âfirstâ so Nauru and Tuvalu will be kept.
>>> s.nsmallest(3) Montserrat 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') Montserrat 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') Montserrat 5200 Nauru 11300 Tuvalu 11300 Anguilla 11300 dtype: int64
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