Slicing a NumPy array within a loop

I need a good explanation (reference) to explain NumPy slicing within (for) loops. I have three cases.

def example1(array):
    for row in array:
        row = row + 1
    return array

def example2(array):
    for row in array:
        row += 1
    return array

def example3(array):
    for row in array:
        row[:] = row + 1
    return array

A simple case:

ex1 = np.arange(9).reshape(3, 3)
ex2 = ex1.copy()
ex3 = ex1.copy()

returns:

>>> example1(ex1)
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])

>>> example2(ex2)
array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])

>>> example3(ex3)
array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])

It can be seen that the first result differs from the second and third.