**Linear Algebra python**

### Problem Statement :

The NumPy module also comes with a number of built-in routines for linear algebra calculations. These can be found in the sub-module linalg. linalg.det The linalg.det tool computes the determinant of an array. print numpy.linalg.det([[1 , 2], [2, 1]]) #Output : -3.0 linalg.eig The linalg.eig computes the eigenvalues and right eigenvectors of a square array. vals, vecs = numpy.linalg.eig([[1 , 2], [2, 1]]) print vals #Output : [ 3. -1.] print vecs #Output : [[ 0.70710678 -0.70710678] # [ 0.70710678 0.70710678]] linalg.inv The linalg.inv tool computes the (multiplicative) inverse of a matrix. print numpy.linalg.inv([[1 , 2], [2, 1]]) #Output : [[-0.33333333 0.66666667] # [ 0.66666667 -0.33333333]] Other routines can be found here Task You are given a square matrix A with dimensions N X N. Your task is to find the determinant. Note: Round the answer to 2 places after the decimal. Input Format The first line contains the integer N. The next N lines contains the N space separated elements of array A. Output Format Print the determinant of A.

### Solution :

` ````
Solution in C :
import numpy
N = int(input())
A = numpy.array([input().split() for _ in range(N)], float)
print(numpy.linalg.det(A))
```

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