modin.pandas.Series.nsmallest¶
- Series.nsmallest(n=5, keep='first')[source]¶
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:
The n smallest values in the Series, sorted in increasing order.
- Return type:
See also
Series.nlargest
Get the n largest elements.
Series.sort_values
Sort Series by values.
Series.head
Return the first n rows.
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 ‘first’ 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