Get n-largest values from a particular column in Pandas DataFrame

nlargest() function returns the top n rows with the largest values in the specified column(s).

Syntax:

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

Parameters:

• n: number of top rows you want to return
• columns: column (or list of columns) you want to check for the largest values.
• keep: Decides what to do if there are duplicate values:
  'first': keeps the first occurrence (default).
  'last': keeps the last occurrence.
  'all': keeps all duplicates.

To download the dataset used in this article, click here.

Loading the Dataset

import pandas as pd
df=pd.read_csv(r'enter the path to dataset here')

df.head(10)

Output

Explanation:

• pd.read_csv(): loads the dataset as a pandas dataframe
• df.head(10): prints the top 10 rows of the dataframe.

Example 1: Getting 5 Largest Ages

df.nlargest(5, ['Age'])

Output

Example 2: Getting 10 maximum weights

df.nlargest(10, ['Weight'])

Output

Example 3: Getting 5 Largest Salaries

df.nlargest(5, ['Salary'])

Output

Example 4: Getting the 5 Largest Rows by Age and Weight Together

Retrieve the rows with the largest values in a Pandas DataFrame based on multiple columns, such as Age and Weight.

df.nlargest(5, ['Age', 'Weight'])

Output

Related Articles:

• Pandas Tutorial
• Pandas DataFrame.nsmallest()