# numpy.linalg.det() Method in Python

In NumPy, we can compute the determinant of the given square array with the help of numpy.linalg.det(). It will take the given square array as a parameter and return the determinant of that.

Syntax: numpy.linalg.det()

Parameter: An square array.

Return: The deteminant of that square array.

Example 1:

## Python

 `import` `numpy as np ` `from` `numpy ``import` `linalg as LA ` ` `  ` `  `array1 ``=` `np.array([[``1``, ``2``], [``3``, ``4``]]) ` ` `  `# Original 2-d array ` `print``(array1) ` ` `  `# Determinant of the said 2-D array ` `print``(np.linalg.det(array1)) `

Output:

```[[1 2]
[3 4]]
-2.0000000000000004
```

Example 2:

## Python

 `import` `numpy as np ` `from` `numpy ``import` `linalg as LA ` ` `  ` `  `array1 ``=` `np.array([[``1``, ``2``, ``3``], [``3``, ``4``, ``1``], [``3``, ``2``, ``1``]]) ` ` `  `# Original 2-d array ` `print``(array1) ` ` `  `# Determinant of the said 2-D array ` `print``(np.linalg.det(array1)) `

Output:

```[[1 2 3]
[3 4 1]
[3 2 1]]
-15.999999999999998
```
My Personal Notes arrow_drop_up Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.

Article Tags :

Be the First to upvote.

Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.