Pandas: Series - cov() function

Last update on September 15 2022 12:58:04 (UTC/GMT +8 hours)

Compute covariance with Pandas Series

The cov() function is used to compute covariance with Series, excluding missing values.

Syntax:

Series.cov(self, other, min_periods=None)

Parameters:

Name	Description	Type/Default Value	Required / Optional
other	Series with which to compute the covariance.	Series	Required
min_periods	Minimum number of observations needed to have a valid result.	int	optional

Returns: float
Covariance between Series and other normalized by N-1 (unbiased estimator).

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
s1 = pd.Series([0.90011105, 0.13494030, 0.62026040])
s2 = pd.Series([0.12630090, 0.26100470, 0.41111190])
s1.cov(s2)

Output:

-0.01832098497271333

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