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Module « scipy.stats.mstats »

Fonction variation - module scipy.stats.mstats

Signature de la fonction variation

def variation(a, axis=0, ddof=0) 

Description

help(scipy.stats.mstats.variation)

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
----------
a : array_like
    Input array.
axis : int or None, optional
    Axis along which to calculate the coefficient of variation. Default
    is 0. If None, compute over the whole array `a`.
ddof : int, optional
    Delta degrees of freedom.  Default is 0.

Returns
-------
variation : ndarray
    The calculated variation along the requested axis.

Notes
-----
For more details about `variation`, see `scipy.stats.variation`.

Examples
--------
>>> import numpy as np
>>> from scipy.stats.mstats import variation
>>> a = np.array([2,8,4])
>>> variation(a)
0.5345224838248487
>>> b = np.array([2,8,3,4])
>>> c = np.ma.masked_array(b, mask=[0,0,1,0])
>>> variation(c)
0.5345224838248487

In the example above, it can be seen that this works the same as
`scipy.stats.variation` except 'stats.mstats.variation' ignores masked
array elements.

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