Table of Contents

    Mastering Array Representation with NumPy in Python: A Complete Guide

    Representation of Array Using numpy

    
    array1d = np.array([1,2,3,4])
    print("shape of array1d before reshaping: ", array1d.shape)
    array1d = array1d.reshape(1,4)
    print("shape of array1d after reshaping: ", array1d.shape)
    #rank of matrix can be found using np.linalg.matrix_rank() function
    print("array1d is a martrix of rank {}".format(np.linalg.matrix_rank(array1d)))
    output:
    shape of array1d before reshaping:  (4,)
    shape of array1d after reshaping:  (1, 4)
    array1d is a martrix of rank 1
    
    • The shape (4,) just represents that the array has 4 elements.

    • The shape (1, 4) represents that array has 4 elements with one row and four columns.

    What Have You learned till now?
    • In this topic, you have read:

      • How to represent matrices using numpy?

      • How to perform dot product and element-wise product using numpy?

      • The concept of broadcasting and its implementation in Python.