modin.pandas.Series.nlargest¶
- Series.nlargest(n=5, keep='first') Series [source] (https://github.com/snowflakedb/snowpark-python/blob/v1.26.0/snowpark-python/.tox/docs/lib/python3.9/site-packages/modin/pandas/series.py#L1445-L1456)¶
Return the largest n elements.
- Parameters:
n (int, default 5) – Return this many descending 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 largest values in the Series, sorted in decreasing order.
- Return type:
See also
Series.nsmallest
Get the n smallest elements.
Series.sort_values
Sort Series by values.
Series.head
Return the first n rows.
Examples
>>> countries_population = {"Italy": 59000000, "France": 65000000, ... "Malta": 434000, "Maldives": 434000, ... "Brunei": 434000, "Iceland": 337000, ... "Nauru": 11300, "Tuvalu": 11300, ... "Anguilla": 11300, "Montserrat": 5200} >>> s = pd.Series(countries_population) >>> s Italy 59000000 France 65000000 Malta 434000 Maldives 434000 Brunei 434000 Iceland 337000 Nauru 11300 Tuvalu 11300 Anguilla 11300 Montserrat 5200 dtype: int64
The n largest elements where
n=5
by default.>>> s.nlargest() France 65000000 Italy 59000000 Malta 434000 Maldives 434000 Brunei 434000 dtype: int64
The n largest elements where
n=3
. Default keep value is ‘first’ so Malta will be kept.>>> s.nlargest(3) France 65000000 Italy 59000000 Malta 434000 dtype: int64
The n largest elements where
n=3
and keeping the last duplicates. Brunei will be kept since it is the last with value 434000 based on the index order.>>> s.nlargest(3, keep='last') France 65000000 Italy 59000000 Brunei 434000 dtype: int64
The n largest elements where
n=3
with all duplicates kept. Note that the returned Series has five elements due to the three duplicates.>>> s.nlargest(3, keep='all') France 65000000 Italy 59000000 Malta 434000 Maldives 434000 Brunei 434000 dtype: int64