pandas.core.groupby.SeriesGroupBy.cov#

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

Compute covariance with Series, excluding missing values.

The two Series objects are not required to be the same length and will be aligned internally before the covariance is calculated.

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