pandas.Series.nsmallest
-
Series.nsmallest(n=5, keep='first')[source] -
Return the smallest
nelements.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
nelements:-
first: take the first occurrences based on the index order -
last: take the last occurrences based on the index order -
-
all : keep all occurrences. This can result in a Series of - size larger than
n.
-
-
Returns: - Series
-
The
nsmallest values in the Series, sorted in increasing order.
See also
-
Series.nlargest - Get the
nlargest elements. -
Series.sort_values - Sort Series by values.
-
Series.head - Return the first
nrows.
Notes
Faster than
.sort_values().head(n)for smallnrelative to the size of theSeriesobject.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: int64The
nlargest elements wheren=5by default.>>> s.nsmallest() Monserat 5200 Nauru 11300 Tuvalu 11300 Anguilla 11300 Iceland 337000 dtype: int64
The
nsmallest elements wheren=3. Defaultkeepvalue is ‘first’ so Nauru and Tuvalu will be kept.>>> s.nsmallest(3) Monserat 5200 Nauru 11300 Tuvalu 11300 dtype: int64
The
nsmallest elements wheren=3and 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
nsmallest elements wheren=3with 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
-
© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.24.2/reference/api/pandas.Series.nsmallest.html