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pandas.core.window.rolling.Rolling.sem
- Rolling.sem(ddof=1, numeric_only=False, *args, **kwargs)[source]
-
Calculate the rolling standard error of mean.
- Parameters
-
- ddof:int, default 1
-
Delta Degrees of Freedom. The divisor used in calculations is
N - ddof
, whereN
represents the number of elements. - numeric_only:bool, 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
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/1.5.0/reference/api/pandas.core.window.rolling.Rolling.sem.html