pandas.Series.cov#
- Series.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
, whereN
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