pandas.core.window.rolling.Rolling.sem#
- Rolling.sem(ddof=1, numeric_only=False, *args, **kwargs)[source]#
- Calculate the rolling standard error of mean. - Parameters
- ddofint, default 1
- Delta Degrees of Freedom. The divisor used in calculations is - N - ddof, where- Nrepresents the number of elements.
- numeric_onlybool, default False
- Include only float, int, boolean columns. - New in version 1.5.0. 
- *args
- For NumPy compatibility and will not have an effect on the result. - Deprecated since version 1.5.0. 
- **kwargs
- For NumPy compatibility and will not have an effect on the result. - Deprecated since version 1.5.0. 
 
- Returns
- Series or DataFrame
- Return type is the same as the original object with - np.float64dtype.
 
 - See also - pandas.Series.rolling
- Calling rolling with Series data. 
- pandas.DataFrame.rolling
- Calling rolling with DataFrames. 
- pandas.Series.sem
- Aggregating sem for Series. 
- pandas.DataFrame.sem
- Aggregating sem for DataFrame. 
 - Notes - A minimum of one period is required for the calculation. - Examples - >>> s = pd.Series([0, 1, 2, 3]) >>> s.rolling(2, min_periods=1).sem() 0 NaN 1 0.707107 2 0.707107 3 0.707107 dtype: float64