# pingouin.circ_r

pingouin.circ_r(alpha, w=None, d=None, axis=0)[source]

Mean resultant vector length for circular data.

Parameters
alphaarray

warray

Number of incidences in case of binned angle data

dfloat

Spacing (in radians) of bin centers for binned data. If supplied, a correction factor is used to correct for bias in the estimation of r.

axisint

Compute along this dimension

Returns
rfloat

Mean resultant length

Notes

The length of the mean resultant vector is a crucial quantity for the measurement of circular spread or hypothesis testing in directional statistics. The closer it is to one, the more concentrated the data sample is around the mean direction (Berens 2009).

Examples

Mean resultant vector length of circular data

>>> from pingouin import circ_r
>>> x = [0.785, 1.570, 3.141, 0.839, 5.934]
>>> circ_r(x)
0.49723034495605356