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
, whereN
represents 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.float64
dtype.
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