xorbits.pandas.window.Rolling.std#

Rolling.std(ddof=1, *args, **kwargs)[源代码]#

Calculate the rolling standard deviation.

参数

  • ddof (int, default 1) – Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.

  • numeric_only (bool, default False (Not supported yet)) –

    Include only float, int, boolean columns.

    1.5.0(pandas) 新版功能.

  • engine (str, default None (Not supported yet)) –

    • 'cython' : Runs the operation through C-extensions from cython.

    • 'numba' : Runs the operation through JIT compiled code from numba.

    • None : Defaults to 'cython' or globally setting compute.use_numba

      1.4.0(pandas) 新版功能.

  • engine_kwargs (dict, default None (Not supported yet)) –

    • For 'cython' engine, there are no accepted engine_kwargs

    • For 'numba' engine, the engine can accept nopython, nogil and parallel dictionary keys. The values must either be True or False. The default engine_kwargs for the 'numba' engine is {'nopython': True, 'nogil': False, 'parallel': False}

      1.4.0(pandas) 新版功能.

返回

Return type is the same as the original object with np.float64 dtype.

返回类型

Series or DataFrame

参见

numpy.std

Equivalent method for NumPy array.

pandas.Series.rolling

Calling rolling with Series data.

pandas.DataFrame.rolling

Calling rolling with DataFrames.

pandas.Series.std

Aggregating std for Series.

pandas.DataFrame.std

Aggregating std for DataFrame.

提示

The default ddof of 1 used in Series.std() is different than the default ddof of 0 in numpy.std().

A minimum of one period is required for the rolling calculation.

实际案例

>>> s = pd.Series([5, 5, 6, 7, 5, 5, 5])  
>>> s.rolling(3).std()  
0         NaN
1         NaN
2    0.577350
3    1.000000
4    1.000000
5    1.154701
6    0.000000
dtype: float64

This docstring was copied from pandas.core.window.rolling.Rolling.