pandas.core.groupby.SeriesGroupBy.std#

SeriesGroupBy.std(ddof=1, engine=None, engine_kwargs=None, numeric_only=False)[source]#

Compute standard deviation of groups, excluding missing values.

For multiple groupings, the result index will be a MultiIndex.

Parameters
ddofint, default 1

Degrees of freedom.

enginestr, default None

  • '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

New in version 1.4.0.

engine_kwargsdict, default None

  • 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}}

New in version 1.4.0.

numeric_onlybool, default False

Include only float, int or boolean data.

New in version 1.5.0.

Changed in version 2.0.0: numeric_only now defaults to False.

Returns
Series or DataFrame

Standard deviation of values within each group.

See also

Series.groupby

Apply a function groupby to a Series.

DataFrame.groupby

Apply a function groupby to each row or column of a DataFrame.