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.

New 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