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NumPy: Compute the determinant of a given square array

NumPy: Linear Algebra Exercise-4 with Solution

Write a NumPy program to compute the determinant of a given square array.

From Wikipedia: In linear algebra, the determinant is a value that can be computed from the elements of a square matrix. The determinant of a matrix A is denoted det(A), det A, or |A|. Geometrically, it can be viewed as the scaling factor of the linear transformation described by the matrix.

In the case of a 2 × 2 matrix the determinant may be defined as:

NumPy Linear algebra: Compute the determinant of a given square array

Sample Solution :

Python Code :

import numpy as np
from numpy import linalg as LA
a = np.array([[1, 0], [1, 2]])
print("Original 2-d array")
print(a)
print("Determinant of the said 2-D array:")
print(np.linalg.det(a))

Sample Output:

Original 2-d array
[[1 0]
 [1 2]]
Determinant of the said 2-D array:
2.0

Python Code Editor:


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Python: Tips of the Day

Getting the last element of a list:

some_list[-1] is the shortest and most Pythonic.

In fact, you can do much more with this syntax. The some_list[-n] syntax gets the nth-to-last element. So some_list[-1] gets the last element, some_list[-2] gets the second to last, etc, all the way down to some_list[-len(some_list)], which gives you the first element.

You can also set list elements in this way. For instance:

>>> some_list = [1, 2, 3]
>>> some_list[-1] = 5 # Set the last element
>>> some_list[-2] = 3 # Set the second to last element
>>> some_list
[1, 3, 5]

Note that getting a list item by index will raise an IndexError if the expected item doesn't exist. This means that some_list[-1] will raise an exception if some_list is empty, because an empty list can't have a last element.

Ref: https://bit.ly/3d8TfFP