pandas.core.groupby.SeriesGroupBy.cov — pandas 3.0.0.dev0+2099.g3832e85779 documentation (original) (raw)
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.
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