Menu
×
   ❮     
HTML CSS JAVASCRIPT SQL PYTHON JAVA PHP HOW TO W3.CSS C C++ C# BOOTSTRAP REACT MYSQL JQUERY EXCEL XML DJANGO NUMPY PANDAS NODEJS R TYPESCRIPT ANGULAR GIT POSTGRESQL MONGODB ASP AI GO KOTLIN SASS VUE DSA GEN AI SCIPY AWS CYBERSECURITY DATA SCIENCE
     ❯   

Pandas DataFrame std() Method

❮ DataFrame Reference


Example

Return the standard deviation for each column:

import pandas as pd

data = [[10, 18, 11], [13, 15, 8], [9, 20, 3]]

df = pd.DataFrame(data)

print(df.std())
Try it Yourself »

Definition and Usage

The std() method calculates the standard deviation for each column.

By specifying the column axis (axis='columns'), the std() method searches column-wise and returns the standard deviation for each row.


Syntax

dataframe.std(axis, skipna, ddof, numeric_only)

Parameters

The parameters are keyword arguments.

Parameter Value Description
axis 0
1
'index'
'columns'
Optional, Which axis to check, default 0.
skip_na True
False
Optional, default True. Set to False if the result should NOT skip NULL values
ddof Number
Optional, default 1. Specifies the Delta Degrees of Freedom
numeric_only None
True
False
Optional. Specifies whether to only check numeric values. Default None

Return Value

A Series with the standard deviations.

If the level argument is specified, this method will return a DataFrame object.

This function does NOT make changes to the original DataFrame object.


❮ DataFrame Reference

×

Contact Sales

If you want to use W3Schools services as an educational institution, team or enterprise, send us an e-mail:
[email protected]

Report Error

If you want to report an error, or if you want to make a suggestion, send us an e-mail:
[email protected]

W3Schools is optimized for learning and training. Examples might be simplified to improve reading and learning. Tutorials, references, and examples are constantly reviewed to avoid errors, but we cannot warrant full correctness of all content. While using W3Schools, you agree to have read and accepted our terms of use, cookie and privacy policy.

Copyright 1999-2024 by Refsnes Data. All Rights Reserved. W3Schools is Powered by W3.CSS.