dask_expr._collection.Index.cov
dask_expr._collection.Index.cov¶
- Index.cov(other, min_periods=None, split_every=False)¶
Compute covariance with Series, excluding missing values.
This docstring was copied from pandas.core.series.Series.cov.
Some inconsistencies with the Dask version may exist.
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 (Not supported in Dask)
Delta degrees of freedom. The divisor used in calculations is
N - ddof
, whereN
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