pandas.core.window.rolling.Rolling.cov¶
- Rolling.cov(other=None, pairwise=None, ddof=1, **kwargs)[source]¶
Calculate the rolling sample covariance.
- Parameters
- otherSeries, DataFrame, or ndarray, optional
If not supplied then will default to self and produce pairwise output.
- pairwisebool, default None
If False then only matching columns between self and other will be used and the output will be a DataFrame. If True then all pairwise combinations will be calculated and the output will be a MultiIndexed DataFrame in the case of DataFrame inputs. In the case of missing elements, only complete pairwise observations will be used.
- ddofint, default 1
Delta Degrees of Freedom. The divisor used in calculations is
N - ddof
, whereN
represents the number of elements.- **kwargs
Keyword arguments to be passed into func.
- Returns
- Series or DataFrame
Return type is determined by the caller.
See also
pandas.Series.rolling
Calling object with Series data.
pandas.DataFrame.rolling
Calling object with DataFrame data.
pandas.Series.cov
Similar method for Series.
pandas.DataFrame.cov
Similar method for DataFrame.