cupyx.scipy.stats.zscore(a, axis=0, ddof=0, nan_policy='propagate')[source]#

Compute the z-score.

Compute the z-score of each value in the sample, relative to the sample mean and standard deviation.

  • a (array-like) – An array like object containing the sample data

  • axis (int or None, optional) – Axis along which to operate. Default is 0. If None, compute over the whole arrsy a

  • ddof (int, optional) – Degrees of freedom correction in the calculation of the standard deviation. Default is 0

  • 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’. Note that when the value is ‘omit’, nans in the input also propagate to the output, but they do not affect the z-scores computed for the non-nan values


zscore – The z-scores, standardized by mean and standard deviation of input array a

Return type: