pandas.core.window.rolling.Window.mean#
- Window.mean(numeric_only=False, **kwargs)[source]#
Calculate the rolling weighted window mean.
- Parameters:
- numeric_onlybool, default False
Include only float, int, boolean columns.
Added in version 1.5.0.
- **kwargs
Keyword arguments to configure the
SciPy
weighted window type.
- Returns:
- Series or DataFrame
Return type is the same as the original object with
np.float64
dtype.
See also
pandas.Series.rolling
Calling rolling with Series data.
pandas.DataFrame.rolling
Calling rolling with DataFrames.
pandas.Series.mean
Aggregating mean for Series.
pandas.DataFrame.mean
Aggregating mean 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').mean(std=3) 0 NaN 1 0.5 2 3.0 3 3.5 4 5.0 dtype: float64