scipy.stats.variation¶
- scipy.stats.variation(a, axis=0, nan_policy='propagate', ddof=0)[source]¶
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 toddof=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