为numpy数组中的整个行分配一个值

Question

I have the following example of an array with grades:

grades = np.array([[ 1,  1,  2,  -3],[ 4,  5,  6,  7],[ 8,  9, -3, 11],[12, 13, 14, 15]])

I would like to identify the elements with "-3" and change their entire row to that number, for example the result:

grades = np.array([[ -3,  -3,  -3,  -3],[ 4,  5,  6,  7],[ -3,  -3, -3, -3],[12, 13, 14, 15]])

So far I tried:

grades[np.argwhere(grades==-3)]=-3

but i get the following result, where the there are other rows affected as well:

array([[-3, -3, -3, -3],[ 4,  5,  6,  7],[-3, -3, -3, -3],[-3, -3, -3, -3],[16, 17, 18, 19]])

Any Idea please? Thanks!

Answer 1

First find which of the rows contain a -3 using simple == and numpy.any . Now index on this boolean array and assign -3 to it, broadcasting will take care of the rest.

>>> grades = np.array([[ 1,  1,  2,  -3],[ 4,  5,  6,  7],[ 8,  9, -3, 11],[12, 13, 14, 15]])
>>> grades[np.any(grades == -3, axis=1)] = -3
>>> grades
array([[-3, -3, -3, -3],
       [ 4,  5,  6,  7],
       [-3, -3, -3, -3],
       [12, 13, 14, 15]])