Given a large sparse matrix in COO format, which conversion should you perform to efficiently execute repeated column slicing, and why?

hard📝 Application Q8 of 15

SciPy - Sparse Matrices (scipy.sparse)

AConvert to CSC format because it stores data column-wise enabling fast column slicing

BConvert to CSR format because it is optimized for fast row slicing

CConvert to DIA format because it is best for diagonal operations

DConvert to LIL format because it supports fast incremental matrix construction

Step-by-Step Solution

Solution:

Step 1: Analyze COO format
COO format is simple but inefficient for slicing operations.
Step 2: Identify best format for column slicing
CSC (Compressed Sparse Column) format stores data column-wise, making column slicing efficient.
Step 3: Choose conversion
Convert COO to CSC to enable fast repeated column slicing.
Final Answer:
Convert to CSC format because it stores data column-wise enabling fast column slicing -> Option A
Quick Check:
CSC is column-oriented, ideal for column slicing [OK]

Quick Trick: Use CSC for repeated column slicing [OK]

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