Calculate the rolling weighted window standard deviation.
Include only float, int, boolean columns.
Added in version 1.5.0.
Keyword arguments to configure the SciPy weighted window type.
Return type is the same as the original object with np.float64 dtype.
See also
pandas.Series.rollingCalling rolling with Series data.
pandas.DataFrame.rollingCalling rolling with DataFrames.
pandas.Series.stdAggregating std for Series.
pandas.DataFrame.stdAggregating std for DataFrame.
Examples
>>> ser = pd.Series([0, 1, 5, 2, 8])
To get an instance of Window we need to pass the parameter win_type.
>>> type(ser.rolling(2, win_type='gaussian'))
<class 'pandas.core.window.rolling.Window'>
In order to use the SciPy Gaussian window we need to provide the parameters M and std. The parameter M corresponds to 2 in our example. We pass the second parameter std as a parameter of the following method:
>>> ser.rolling(2, win_type='gaussian').std(std=3)
0 NaN
1 0.707107
2 2.828427
3 2.121320
4 4.242641
dtype: float64
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https://pandas.pydata.org/pandas-docs/version/2.3.0/reference/api/pandas.core.window.rolling.Window.std.html