Skip to content
Related Articles

Related Articles

Python | Pandas DataFrame.nsmallest()
  • Last Updated : 17 Sep, 2018

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 nsmallest() method is used to get n least values from a data frame or a series.

Syntax: DataFrame.nsmallest(n, columns, keep=’first’)

Parameters:
n: int, Number of values to select
columns: Column to check for least 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.



Example #1: Extracting Least 5 values
In this example least 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().




# 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 least 5
least5 = data.nsmallest(5, "Salary")
  
# display
least5


Output:

 
Eample #2: Sorting by sort_values()




# 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 ascending order
data.sort_values("Salary", ascending = True, inplace = True)
  
# displaying top 5 values
data.head()


Output:

As shown in the output image, the values returned by both functions are similar.

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

My Personal Notes arrow_drop_up
Recommended Articles
Page :