SciPy - Sparse Matrices (scipy.sparse)
What will be the memory size difference when converting a 1000x1000 dense matrix with 99% zeros to a CSR sparse matrix?
What will be the memory size difference when converting a 1000x1000 dense matrix with 99% zeros to a CSR sparse matrix?
medium📝 Predict Output Q4 of 15
Step-by-Step Solution
Solution:
Step 1: Understand data sparsity
A 1000x1000 matrix with 99% zeros has only 1% non-zero elements, about 10,000 values.Step 2: Compare memory usage
CSR sparse matrix stores only non-zero elements and their indices, using much less memory than dense storing 1,000,000 elements.Final Answer:
Sparse matrix uses significantly less memory -> Option AQuick Check:
Memory difference = sparse stores fewer elements [OK]
Quick Trick: Sparse matrices save memory when zeros are many [OK]
Common Mistakes:
MISTAKES- Assuming sparse always uses more memory
- Ignoring index storage in sparse format
- Thinking sparse size depends only on rows
Master "Sparse Matrices (scipy.sparse)" in SciPy
Want More Practice?
15+ quiz questions · All difficulty levels · Free
Free Signup - Practice All QuestionsMore SciPy Quizzes