Mastering Array Representation with NumPy in Python: A Complete Guide

Rumman Ansari   Software Engineer   2024-07-31 10:12:02   147  Share
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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.