In NumPy, the shape of an array describes how many elements are arranged along each dimension.

What is Array Shape ?

The shape of a NumPy array is a tuple of integers that indicates:

  • number of rows

  • number of columns

  • number of higher dimensions (if any)

Syntax :
Python 
array.shape

Shape of a 1D Array?
A 1D array has only one dimension.
Python 
import numpy as np arr = np.array([10, 20, 30, 40]) print(arr.shape) #output (4,)

Shape of a 2D Array?
A 2D array has rows and columns.
Python 
import numpy as np arr = np.array([[1, 2, 3], [4, 5, 6]]) print(arr.shape) #output (2,3)

Shape of a 3D Array?
A 3D array contains multiple 2D arrays.
Python 
import numpy as np arr = np.array([ [[1, 2], [3, 4]], [[5, 6], [7, 8]] ]) print(arr.shape) #output (2,2,2)

Shape vs Size vs Dimensions?
AttributeMeaning
shapeStructure of array
sizeTotal number of elements
ndimNumber of dimensions