Python | Pandas DataFrame.nlargest() (original) (raw)

Last Updated : 11 Jul, 2025

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas nlargest() method is used to get n largest values from a data frame or a series.
Syntax:

DataFrame.nlargest(n, columns, keep='first')

Parameters:

n: int, Number of values to selectcolumns: Column to check for values or user can select column while calling too. [For example: data["age"].nsmallest(3) OR data.nsmallest(3, "age")]keep: object to set which value to select if duplicates exit. Options are 'first' or 'last'

To download the CSV file used, Click Here.
Code #1: Extracting Largest 5 values In this example, Largest 5 values are extracted and then compared to the other sorted by the sort_values() function. NaN values are removed before trying this method. Refer sort_values and dropna() function.

Python 1== `

importing pandas package

import pandas as pd

making data frame from csv file

data = pd.read_csv("employees.csv")

removing null values

data.dropna(inplace = True)

extracting greatest 5

large5 = data.nlargest(5, "Salary")

display

large5

`

Output: Code #2: Sorting by sort_values()

Python 1== `

importing pandas package

import pandas as pd

making data frame from csv file

data = pd.read_csv("employees.csv")

removing null values

data.dropna(inplace = True)

sorting in descending order

data.sort_values("Salary", ascending = False, inplace = True)

displaying top 5 values

data.head()

`

**Output:**As shown in the output image, the values returned by both functions is similar.