A $3\times 4 \times 4$ array is created with:

a = np.linspace(1,48,48).reshape(3,4,4)

Index or slice this array to obtain the following

(a)

20.0

(b)

[  9.  10.  11.  12.]

(c) The $4 \times 4$ array:

[[ 33.  34.  35.  36.]
     [ 37.  38.  39.  40.]
 [ 41.  42.  43.  44.]
 [ 45.  46.  47.  48.]]

(d) The $3 \times 2$ array:

[[  5.   6.]
 [ 21.  22.]
 [ 37.  38.]]

(e) The $4 \times 2$ array:

[[ 36.  35.]
 [ 40.  39.]
 [ 44.  43.]
 [ 48.  47.]]

(f) The $3 \times 4$ array:

[[ 13.   9.   5.   1.]
 [ 29.  25.  21.  17.]
 [ 45.  41.  37.  33.]]

(g) (Harder) Using an array of indexes, the $2 \times 2$ array:

[[  1.   4.]
 [ 45.  48.]]

ia = np.array([[0, 0], [2, 2]])
ja = np.array([[0, 0], [3, 3]])
ka = np.array([[0, 3], [0, 3]])