pandas 1.4.2

ParametersReturns
generate_numba_table_func(kwargs: 'dict[str, Any]', func: 'Callable[..., np.ndarray]', engine_kwargs: 'dict[str, bool] | None', name: 'str')

Func will be passed a M window size x N number of columns array, and must return a 1 x N number of columns array. Func is intended to operate row-wise, but the result will be transposed for axis=1.

  1. jit the user's function

  2. Return a rolling apply function with the jitted function inline

Parameters

kwargs : dict

**kwargs to be passed into the function

func : function

function to be applied to each window and will be JITed

engine_kwargs : dict

dictionary of arguments to be passed into numba.jit

name : str

caller (Rolling/Expanding) and original method name for numba cache key

Returns

Numba function

Generate a numba jitted function to apply window calculations table-wise.

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/window/numba_.py#186
type: <class 'function'>
Commit: