pandas.Series.cov

Series.cov(self, other: 'Series', min_periods: Union[int, NoneType] = None, ddof: Union[int, NoneType] = 1) → float[source]

Compute covariance with Series, excluding missing values.

Parameters
otherSeries

Series with which to compute the covariance.

min_periodsint, optional

Minimum number of observations needed to have a valid result.

ddofint, 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
pandas.Series.count pandas.Series.cummax