Creating sparse matrices in SciPy - Quick Revision & Summary

Recall & Review

beginner

What is a sparse matrix?

A sparse matrix is a matrix mostly filled with zeros. It saves memory by only storing the non-zero values and their positions.

beginner

Name two common formats for sparse matrices in SciPy.

Two common formats are CSR (Compressed Sparse Row) and COO (Coordinate list). CSR is good for fast row slicing, COO is easy to create.

beginner

How do you create a COO sparse matrix in SciPy?

Use scipy.sparse.coo_matrix with three arrays: data (values), row indices, and column indices.

beginner

Why use sparse matrices instead of regular dense matrices?

Sparse matrices save memory and speed up calculations when most values are zero, like in large graphs or text data.

intermediate

What function creates a CSR sparse matrix from dense data?

Use scipy.sparse.csr_matrix with a dense matrix or arrays. It converts dense data into compressed sparse row format.

Which SciPy function creates a sparse matrix from data, row, and column arrays?

A scipy.sparse.dense_matrix

B scipy.sparse.coo_matrix

C scipy.sparse.array_matrix

D scipy.sparse.full_matrix

The coo_matrix function creates a sparse matrix using data, row, and column arrays.

What is the main benefit of using sparse matrices?

A They use less memory for mostly zero data

B They are easier to read

C They always run faster than dense matrices

D They store all values including zeros

Sparse matrices save memory by storing only non-zero values.

Which sparse matrix format is best for fast row slicing?

A COO

B LIL

C CSR

D DOK

CSR (Compressed Sparse Row) format is optimized for fast row slicing.

How do you convert a dense matrix to a CSR sparse matrix?

A Use csr_matrix with the dense matrix as input

B Use coo_matrix with zeros

C Use dense_matrix function

D Use toarray() method

csr_matrix can take a dense matrix and convert it to CSR format.

Which of these is NOT a sparse matrix format in SciPy?

A COO

B CSR

C DOK

D XYZ

XYZ is not a recognized sparse matrix format in SciPy.

Explain how to create a sparse matrix using the COO format in SciPy.

Think about what information you need to specify the non-zero values and their positions.

Describe why sparse matrices are useful and when you would use them.

Consider situations with many zeros in data.