modin.pandas.Series.nlargest¶

Series.nlargest(n=5, keep='first')[source]¶

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:

Series

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

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The n largest elements where n=5 by default.

>>> s.nlargest()
France      65000000
Italy       59000000
Malta         434000
Maldives      434000
Brunei        434000
dtype: int64

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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

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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

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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

Copy