# -*- coding: utf-8 -*-
"""
Created on Wed Feb 27 08:55:58 2019

@author: Ham

HackerRanch Challenge: Linear Algebra

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 NxN.
Your task is to find the determinant.

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.

Sample Input

2
1.1 1.1
1.1 1.1

Sample Output

0.0

"""

import io
import numpy

STDIN_SIO = io.StringIO("""
3
1 2 3
4 5 6
1 2 1
""".strip())

if __name__ == '__main__':
    #a = [list(map(float, input().split())) for _ in range(int(input()))]
    a = [list(map(float, STDIN_SIO.readline().strip().split()))
         for _ in range(int(STDIN_SIO.readline()))]
    print(a)
    print(round(numpy.linalg.det(a), 2))
