pandas.core.window.rolling.Rolling.sem#

Rolling.sem(ddof=1, *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 N represents the number of elements.

*args

For NumPy compatibility and will not have an effect on the result.

**kwargs

For NumPy compatibility and will not have an effect on the result.

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

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