get the index of the last negative value in a 2d array per column

I'm trying to get the index of the last negative value of an array per column (in order to slice it after). a simple working example on a 1d vector is :

import numpy as np

A = np.arange(10) - 5
A[2] = 2
print A # [-5 -4  2 -2 -1  0  1  2  3  4]

idx = np.max(np.where(A <= 0)[0])
print idx # 5

A[:idx] = 0
print A # [0 0 0 0 0 0 1 2 3 4]

Now I wanna do the same thing on each column of a 2D array :

A = np.arange(10) - 5
A[2] = 2
A2 = np.tile(A, 3).reshape((3, 10)) - np.array([0, 2, -1]).reshape((3, 1))
print A2
# [[-5 -4  2 -2 -1  0  1  2  3  4]
#  [-7 -6  0 -4 -3 -2 -1  0  1  2]
#  [-4 -3  3 -1  0  1  2  3  4  5]]

And I would like to obtain :

print A2
# [[0 0 0 0 0 0 1 2 3 4]
#  [0 0 0 0 0 0 0 0 1 2]
#  [0 0 0 0 0 1 2 3 4 5]]

but I can't manage to figure out how to translate the max/where statement to the this 2d array...