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numpy.linalg.det() Method in Python
• Last Updated : 10 Aug, 2020

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
```

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