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