[Solved] What will be the output of this code snippet?from scipy.sparse import coo_matrix row = [0, 0, 1] col = [0, 2, 1] data = [1, 2, 3] matrix = coo_matrix((data, (row, col)), shape=(2, 3)) print(matrix.... | SciPy

SciPy - Sparse Matrices (scipy.sparse)

What will be the output of this code snippet?

from scipy.sparse import coo_matrix
row = [0, 0, 1]
col = [0, 2, 1]
data = [1, 2, 3]
matrix = coo_matrix((data, (row, col)), shape=(2, 3))
print(matrix.toarray())

A[[1 2 0] [0 0 3]]

B[[1 0 2] [0 0 3]]

C[[1 0 2] [0 3 0]]

D[[1 0 0] [0 2 3]]

Step-by-Step Solution

Solution:

Step 1: Map data to matrix positions
Data 1 at (0,0), 2 at (0,2), 3 at (1,1) in a 2x3 matrix.
Step 2: Construct dense array
Row 0: positions 0 and 2 filled with 1 and 2, position 1 zero. Row 1: position 1 filled with 3, others zero.
Final Answer:
[[1 0 2] [0 3 0]] -> Option C
Quick Check:
Data placed by (row, col) indices in array [OK]

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

Common Mistakes:

MISTAKES

Mixing row and column indices
Misplacing data values in output
Ignoring zeros in sparse matrix

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What will be the output of this code snippet?

Step 1: Map data to matrix positions

Step 2: Construct dense array

Final Answer:

Quick Check:

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