binned_statistic_2d(x, y, values, statistic='mean', bins=10, range=None, expand_binnumbers=False)

Notes

Parameters

x : (N,) array_like

y : (N,) array_like

values : (N,) array_like or list of (N,) array_like

statistic : string or callable, optional

bins : int or [int, int] or array_like or [array, array], optional

range : (2,2) array_like, optional

expand_binnumbers : bool, optional

Returns

statistic : (nx, ny) ndarray

x_edge : (nx + 1) ndarray

y_edge : (ny + 1) ndarray

binnumber : (N,) array of ints or (2,N) ndarray of ints

See Also

binned_statistic

binned_statistic_dd

numpy.digitize

numpy.histogram2d

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.stats._binned_statistic:binned_statistic_dd scipy.stats._binned_statistic:binned_statistic

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

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GitHub : /scipy/stats/_binned_statistic.py#195
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