pandas 1.4.2

ParametersReturns
std(self, ddof: 'int' = 1, engine: 'str | None' = None, engine_kwargs: 'dict[str, bool] | None' = None)

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

Parameters

ddof : int, default 1

Degrees of freedom.

engine : str, default None
engine_kwargs : dict, 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}}

versionadded

Returns

Series or DataFrame

Standard deviation of values within each group.

Compute standard deviation of groups, excluding missing values.

See Also

DataFrame.groupby

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

Series.groupby

Apply a function groupby to a Series.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


File: /pandas/core/groupby/groupby.py#1992
type: <class 'function'>
Commit: