>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])

>>> np.shape(a)

(2,)

>>> a.shape

(2,)

​

>>> np.shape(np.eye(3))

(3, 3)

>>> np.shape([[1, 2]])

(1, 2)

>>> np.shape([0])

(1,)

>>> np.shape(0)

()

​

import numpy as np

arr = np.array([1,2,3])

arr.shape

​

import numpy as np

​

data = np.arange(2*3*4*5).reshape(2, 3, 4, 5)

print(data)

​

this is the breakdown : 

{ [()()(a,a,a,a,a)()] [()()()()] [()()()()] } { [()()()()] [()()()()] [()()()()] } 

tow of {}                       ^5 items inside each            

three of [] 

four of ()

each (a,a,a,a,a) has 5 items                 

​

example will be like this

​

[[[[ 0  1  2  3  4]

   [ 5  6  7  8  9]

   [10 11 12 13 14]

   [15 16 17 18 19]]

​

  [[20 21 22 23 24]

   [25 26 27 28 29]

   [30 31 32 33 34]

   [35 36 37 38 39]]

​

  [[40 41 42 43 44]

   [45 46 47 48 49]

   [50 51 52 53 54]

   [55 56 57 58 59]]]

                    ^two

                   ^three

                  ^four  , five items in each   

 [[[60 61 62 63 64]

   [65 66 67 68 69]

   [70 71 72 73 74]

   [75 76 77 78 79]]

​

  [[80 81 82 83 84]

   [85 86 87 88 89]

   [90 91 92 93 94]

   [95 96 97 98 99]]

​

  [[100 101 102 103 104]

   [105 106 107 108 109]

   [110 111 112 113 114]

   [115 116 117 118 119]]]]

a = np.arange(3)

b = np.arange(12).reshape((3, 4))

c = np.arange(24).reshape((2, 3, 4))

​

# it returns the length of each dimension (=size function of MATLAB)

print(a.shape) # (3,)

print(b.shape) # (3, 4)

print(c.shape) # (2, 3, 4)

numpy.shape(array_name)

import numpy as np

​

# Assuming 'arr' is the numpy array whose shape needs to be determined

arr = np.array([[1, 2, 3], [4, 5, 6]])

shape = arr.shape

​

print(shape)