pandas.core.window.ewm.ExponentialMovingWindow.cov¶
- ExponentialMovingWindow.cov(other=None, pairwise=None, bias=False, **kwargs)[source]¶
Calculate the ewm (exponential weighted moment) sample covariance.
- Parameters
- otherSeries or DataFrame , 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 MultiIndex DataFrame in the case of DataFrame inputs. In the case of missing elements, only complete pairwise observations will be used.
- biasbool, default False
Use a standard estimation bias correction.
- **kwargs
For NumPy compatibility and will not have an effect on the result.
- Returns
- Series or DataFrame
Return type is the same as the original object with
np.float64
dtype.
See also
pandas.Series.ewm
Calling ewm with Series data.
pandas.DataFrame.ewm
Calling ewm with DataFrames.
pandas.Series.cov
Aggregating cov for Series.
pandas.DataFrame.cov
Aggregating cov for DataFrame.