pyspark.pandas.Series.cov#
- Series.cov(other, min_periods=None, ddof=1)[source]#
- Compute covariance with Series, excluding missing values. - New in version 3.3.0. - 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- Nrepresents the number of elements.- New in version 3.4.0. 
 
- Returns
- float
- Covariance between Series and other 
 
 - Examples - >>> from pyspark.pandas.config import set_option, reset_option >>> s1 = ps.Series([0.90010907, 0.13484424, 0.62036035]) >>> s2 = ps.Series([0.12528585, 0.26962463, 0.51111198]) >>> with ps.option_context("compute.ops_on_diff_frames", True): ... s1.cov(s2) -0.016857... >>> with ps.option_context("compute.ops_on_diff_frames", True): ... s1.cov(s2, ddof=2) -0.033715...