[Solved] What will be the output of this code?from scipy.sparse import csr_matrix import numpy as np mat = csr_matrix(np.array([[0, 1], [2, 0]])) print(mat.toarray()) | SciPy

SciPy - Sparse Matrices (scipy.sparse)

What will be the output of this code?

from scipy.sparse import csr_matrix
import numpy as np
mat = csr_matrix(np.array([[0, 1], [2, 0]]))
print(mat.toarray())

A[[0 1] [2 0]]

B[[1 0] [0 2]]

C[[0 0] [0 0]]

D[[1 2] [0 0]]

Step-by-Step Solution

Solution:

Step 1: Convert numpy array to CSR sparse matrix
The matrix is [[0,1],[2,0]] converted to sparse format.
Step 2: Use toarray() to get dense matrix back
Calling toarray() returns the original dense matrix.
Final Answer:
[[0 1] [2 0]] -> Option A
Quick Check:
toarray() returns original matrix [OK]

Quick Trick: toarray() converts sparse back to dense matrix [OK]

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What will be the output of this code?