there is an array like:

```
array([
   [[X1, Y1, 80, 13, 14],
    [17, 54, 47, 67, 45],
    [11, 21, 67, 45, 11],
    [15, 75, 17, 69, 12]],

   [[X2, Y2, 94, 51, 10],
    [64, 81, 90, 80, 67],
    [78, 73, 19,  6, 57],
    [46, 18, 83, 26, 56]],

    ...

   [[Xn, Yn, 32,  3, 82],
    [47, 69, 63, 20, 10],
    [16, 48,  7, 96, 11],
    [95, 30, 45, 65, 42]] ])

```

the goal is to group by every X's and Y's then check a condition in every group.
to do this I write code:

```
x=npy.random.randint(100,size=(5,4,5))
array([[[36, 47, 80, 13, 14],
        [17, 54, 47, 67, 45],
        [11, 21, 67, 45, 11],
        [15, 75, 17, 69, 12]],

       [[50, 17, 94, 51, 10],
        [64, 81, 90, 80, 67],
        [78, 73, 19,  6, 57],
        [46, 18, 83, 26, 56]],

       [[37, 98, 32,  3, 82],
        [47, 69, 63, 20, 10],
        [16, 48,  7, 96, 11],
        [95, 30, 45, 65, 42]],

       [[59, 36, 38, 95,  3],
        [67, 62, 61, 64, 15],
        [49, 45, 24, 85, 24],
        [23, 89, 23, 63, 14]],

       [[49, 26, 70, 83, 99],
        [16, 94, 78, 43, 33],
        [95,  4, 39, 91, 56],
        [94, 26, 71, 32, 55]]])

for i in range(x.shape[1]):
  for j in range(x.shape[2]):
    npy.any(x[0:3,i,j]>80)

False
True
True
False
True
False
True
True
False
False
False
False
False
True
False
True
False
True
False
False

```

but because the array that I work with, is very big this way is not efficient to me.
is there any better way to write? is it possible to remove for loops? what is the fastest way to this ?