pandas.Series.cov

Series.cov(other, min_periods=None, ddof=1)[source]

Compute covariance with Series, excluding missing values.

Parameters
other:Series

Series with which to compute the covariance.

min_periods:int, optional

Minimum number of observations needed to have a valid result.

ddof:int, default 1

Delta degrees of freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.

New in version 1.1.0.

Returns
float

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

See also

DataFrame.cov

Compute pairwise covariance of columns.

Examples

>>> s1 = pd.Series([0.90010907, 0.13484424, 0.62036035])
>>> s2 = pd.Series([0.12528585, 0.26962463, 0.51111198])
>>> s1.cov(s2)
-0.01685762652715874

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https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/api/pandas.Series.cov.html