scipy.stats.variation

scipy.stats.variation(a, axis=0, nan_policy='propagate', ddof=0)

Compute the coefficient of variation.

The coefficient of variation is the standard deviation divided by the mean. This function is equivalent to:

np.std(x, axis=axis, ddof=ddof) / np.mean(x)

The default for ddof is 0, but many definitions of the coefficient of variation use the square root of the unbiased sample variance for the sample standard deviation, which corresponds to ddof=1.

Parameters

aarray_like

Input array.

axisint or None, optional

Axis along which to calculate the coefficient of variation. Default is 0. If None, compute over the whole array a.

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

Defines how to handle when input contains nan. The following options are available (default is ‘propagate’):

• ‘propagate’: returns nan

• ‘raise’: throws an error

• ‘omit’: performs the calculations ignoring nan values

ddofint, optional

Delta degrees of freedom. Default is 0.

Returns

variationndarray

The calculated variation along the requested axis.

References

1

Zwillinger, D. and Kokoska, S. (2000). CRC Standard Probability and Statistics Tables and Formulae. Chapman & Hall: New York. 2000.

Examples

>>> from scipy.stats import variation
>>> variation([1, 2, 3, 4, 5])
0.47140452079103173

scipy.stats.tsem scipy.stats.find_repeats