scipy.stats.contingency.margins#

scipy.stats.contingency.margins(a)[source]#

Return a list of the marginal sums of the array a.

Parameters

andarray: The array for which to compute the marginal sums.

Returns

margsumslist of ndarrays: A list of length a.ndim. margsums[k] is the result of summing a over all axes except k; it has the same number of dimensions as a, but the length of each axis except axis k will be 1.

Examples

>>> a = np.arange(12).reshape(2, 6)
>>> a
array([[ 0,  1,  2,  3,  4,  5],
       [ 6,  7,  8,  9, 10, 11]])
>>> from scipy.stats.contingency import margins
>>> m0, m1 = margins(a)
>>> m0
array([[15],
       [51]])
>>> m1
array([[ 6,  8, 10, 12, 14, 16]])

>>> b = np.arange(24).reshape(2,3,4)
>>> m0, m1, m2 = margins(b)
>>> m0
array([[[ 66]],
       [[210]]])
>>> m1
array([[[ 60],
        [ 92],
        [124]]])
>>> m2
array([[[60, 66, 72, 78]]])

scipy.stats.contingency.expected_freq

scipy.stats.contingency.relative_risk