29 Mar NumPy Array Shape

In Python Numpy, the number of elements in each dimension of an array is called the shape. To get the shape of a Numpy array, use the numpy.shape attribute in Python.

In this lesson, we have covered the following examples:

• Check the shape of a Zero-Dimensional NumPy array
• Check the shape of a One-Dimensional NumPy array
• Check the shape of a Two-Dimensional NumPy array
• Check the shape of a Three-Dimensional NumPy array

Check the shape of a Zero-Dimensional NumPy array

Let us see an example and create a Zero-Dimensional NumPy array to check the shape:

import numpy as np

n = np.array(10)

print(n)
print(n.dim)
print(n.shape)

Output

10
0
()

Check the shape of a One-Dimensional NumPy array

Let us see an example and create a One-Dimensional NumPy array to check the shape:

import numpy as np

n = np.array([10, 20, 30])

print(n)
print(n.ndim)
print(n.shape)

Output

[10 20 30]
1
(3,)

Checking the shape of a Two-Dimensional NumPy array

Let us see an example and create a Two-Dimensional NumPy array to check the shape:

import numpy as np

n = np.array([[1, 3, 5], [4, 8, 12]])

print(n)
print(n.ndim)
print(n.shape)

Output

[[ 1  3  5]
 [ 4  8 12]]
2
(2, 3)

Check the shape of a Three-Dimensional NumPy array

Let us see an example and create a Three-Dimensional NumPy array to check the shape:

# Check the shape of a Three-Dimensional (3D) array

import numpy as np

n = np.array([
             [[10, 20, 30, 40, 50],
             [40, 60, 76, 88, 99]],

             [[25, 20, 30, 40, 50],
             [50, 60, 76, 88, 99]],

             [[35, 20, 30, 40, 50],
             [50, 60, 76, 88, 99]],

             [[60, 20, 30, 40, 50],
             [90, 60, 76, 88, 99]]
             ])

print(n)
print(n.ndim)
print(n.shape)

Output

[[[10 20 30 40 50]
  [40 60 76 88 99]]

 [[25 20 30 40 50]
  [50 60 76 88 99]]

 [[35 20 30 40 50]
  [50 60 76 88 99]]

 [[60 20 30 40 50]
  [90 60 76 88 99]]]
3
(4, 2, 5)

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