Pandas Series: nlargest() function

Last update on September 15 2022 12:54:14 (UTC/GMT +8 hours)

Get the largest n elements in Pandas

The nlargest() function is used to get the largest n elements.

Syntax:

Series.nlargest(self, n=5, keep='first')

Parameters:

Name	Description	Type/Default Value	Required / Optional
n	Return this many descending sorted values.	int Default Value: 5	Required
keep	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.	{‘first’, ‘last’, ‘all’} Default Value: ‘first’	Required

Returns: Series
The n largest values in the Series, sorted in decreasing order.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
countries_population = {"Italy": 60550000, "France": 65130728,
                        "Russia": 435000, "Iceland": 435000,
                        "Palau": 435000, "Brazil": 21104900,
                        "Nauru": 11600, "Tuvalu": 11600,
                        "Bermuda": 11600, "Tokelau": 1440}
s = pd.Series(countries_population)
s

Output:

Italy      60550000
France     65130728
Russia       435000
Iceland      435000
Palau        435000
Brazil     21104900
Nauru         11600
Tuvalu        11600
Bermuda       11600
Tokelau        1440
dtype: int64

Example - The n largest elements where n=5 by default:

Python-Pandas Code:

import numpy as np
import pandas as pd
countries_population = {"Italy": 60550000, "France": 65130728,
                        "Russia": 435000, "Iceland": 435000,
                        "Palau": 435000, "Brazil": 21104900,
                        "Nauru": 11600, "Tuvalu": 11600,
                        "Bermuda": 11600, "Tokelau": 1440}
s = pd.Series(countries_population)
s.nlargest()

Output:

France     65130728
Italy      60550000
Brazil     21104900
Russia       435000
Iceland      435000
dtype: int64

Example - The n largest elements where n=4. Default keep value is ‘first’ so Russia will be kept:

Python-Pandas Code:

import numpy as np
import pandas as pd
countries_population = {"Italy": 60550000, "France": 65130728,
                        "Russia": 435000, "Iceland": 435000,
                        "Palau": 435000, "Brazil": 21104900,
                        "Nauru": 11600, "Tuvalu": 11600,
                        "Bermuda": 11600, "Tokelau": 1440}
s = pd.Series(countries_population)
s.nlargest(4)

Output:

France    65130728
Italy     60550000
Brazil    21104900
Russia      435000
dtype: int64

Example - The n largest elements where n=4 and keeping the last duplicates. Palau will be kept since it is the last with value 435000 based on the index order:

Python-Pandas Code:

import numpy as np
import pandas as pd
countries_population = {"Italy": 60550000, "France": 65130728,
                        "Russia": 435000, "Iceland": 435000,
                        "Palau": 435000, "Brazil": 21104900,
                        "Nauru": 11600, "Tuvalu": 11600,
                        "Bermuda": 11600, "Tokelau": 1440}
s = pd.Series(countries_population)
s.nlargest(4, keep='last')

Output:

France    65130728
Italy     60550000
Brazil    21104900
Palau       435000
dtype: int64

Example - The n largest elements where n=5 with all duplicates kept. Note that the returned Series has five elements due to the three duplicates:

Python-Pandas Code:

import numpy as np
import pandas as pd
countries_population = {"Italy": 60550000, "France": 65130728,
                        "Russia": 435000, "Iceland": 435000,
                        "Palau": 435000, "Brazil": 21104900,
                        "Nauru": 11600, "Tuvalu": 11600,
                        "Bermuda": 11600, "Tokelau": 1440}
s = pd.Series(countries_population)
s.nlargest(5, keep='all')

Output:

France     65130728
Italy      60550000
Brazil     21104900
Russia       435000
Iceland      435000
Palau        435000
dtype: int64

Previous: Minimum values in Pandas requested axis
Next: Get the smallest n elements in Pandas