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
, 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
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/api/pandas.Series.cov.html