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Pandas DataFrame std() Method

❮ DataFrame Reference


Example

Return the variance for each column:

import pandas as pd

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

df = pd.DataFrame(data)

print(df.var())
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Definition and Usage

The var() method calculates the variance for each column.

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


Syntax

dataframe.var(axis, skipna, level, 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
level Number
level name
Optional, default None. Specifies which level ( in a hierarchical multi index) to check along
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 variances.

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