# scipy.stats.circstd

scipy.stats.circstd(samples, high=6.283185307179586, low=0, axis=None, nan_policy='propagate')

  Compute the circular standard deviation for samples assumed to be in the range [low to high].

  Parameters
    samples array_like

      Input array.

    high float or int, optional

      High boundary for circular standard deviation range. Default is `2*pi`.

    low float or int, optional

      Low boundary for circular standard deviation range. Default is 0.

    axis int, optional

      Axis along which standard deviations are computed. The default is to compute the standard deviation of the flattened array.

    nan_policy{‘propagate’, ‘raise’, ‘omit’}, optional

      Defines how to handle when input contains nan. ‘propagate’ returns nan, ‘raise’ throws an error, ‘omit’ performs the calculations ignoring nan values. Default is ‘propagate’.

  Returns
    circstd float

      Circular standard deviation.

  Notes

  This uses a definition of circular standard deviation that in the limit of small angles returns a number close to the ‘linear’ standard deviation.

  Examples

      >>> from scipy.stats import circstd
      >>> circstd([0, 0.1*np.pi/2, 0.001*np.pi, 0.03*np.pi/2])
      0.063564063306

scipy.stats.circvar scipy.stats.chi2_contingency