[Solved] What will be the output of this code?import numpy as np from scipy.sparse import csr_matrix arr = np.array([[0, 0, 3], [4, 0, 0]]) sparse_mat = csr_matrix(arr) print(sparse_mat.data) | SciPy

SciPy - Sparse Matrices (scipy.sparse)

What will be the output of this code?

import numpy as np
from scipy.sparse import csr_matrix

arr = np.array([[0, 0, 3], [4, 0, 0]])
sparse_mat = csr_matrix(arr)
print(sparse_mat.data)

A[0 0 3 4 0 0]

B[0 3 4]

C[3 4 0]

D[3 4]

Step-by-Step Solution

Solution:

Step 1: Understand csr_matrix data attribute
The 'data' attribute stores only the non-zero elements of the sparse matrix in row-major order.
Step 2: Identify non-zero elements in the array
In arr, non-zero elements are 3 (at position [0,2]) and 4 (at position [1,0]).
Final Answer:
[3 4] -> Option D
Quick Check:
csr_matrix.data shows only non-zero values [OK]

Quick Trick: csr_matrix.data shows only non-zero values [OK]

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What will be the output of this code?