CSC format (Compressed Sparse Column) in SciPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does CSC stand for in sparse matrix storage?

CSC stands for Compressed Sparse Column. It is a way to store sparse matrices efficiently by compressing data column-wise.

intermediate

How does CSC format store the matrix data?

CSC stores three arrays: one for non-zero values, one for row indices of those values, and one for column pointers that mark where each column starts in the values array.

beginner

Why is CSC format useful in data science?

CSC format saves memory and speeds up column-based operations like matrix-vector multiplication, which is common in data science tasks.

beginner

Show a simple example of creating a CSC matrix using scipy.

You can create a CSC matrix with scipy.sparse.csc_matrix. For example:<br><pre>from scipy.sparse import csc_matrix
import numpy as np

# Create a dense matrix
dense = np.array([[0, 0, 1], [1, 0, 0], [0, 2, 0]])

# Convert to CSC format
csc = csc_matrix(dense)
print(csc)</pre>

intermediate

What is the difference between CSC and CSR formats?

CSC compresses columns and is efficient for column slicing and operations. CSR (Compressed Sparse Row) compresses rows and is better for row slicing and row-based operations.

What does the 'indptr' array in CSC format represent?

A Values of non-zero elements

B Column pointers marking start of each column in data array

C Row indices of non-zero elements

D Total number of non-zero elements

The 'indptr' array in CSC format shows where each column starts in the data array.

Which operation is CSC format especially efficient for?

A Row slicing and row-based matrix operations

B Dense matrix multiplication

C Column slicing and column-based matrix operations

D Sorting matrix elements

CSC format is designed to speed up column slicing and column-based operations.

In scipy, which function creates a CSC sparse matrix?

A scipy.sparse.lil_matrix()

B scipy.sparse.csr_matrix()

C scipy.sparse.dok_matrix()

D scipy.sparse.csc_matrix()

The function scipy.sparse.csc_matrix() creates a CSC format sparse matrix.

What is stored in the 'data' array of a CSC matrix?

A Non-zero values of the matrix

B Row indices of non-zero values

C Column pointers

D Zero values

The 'data' array holds the actual non-zero values of the sparse matrix.

Which format is better for fast row slicing?

A CSR (Compressed Sparse Row)

B CSC (Compressed Sparse Column)

C Dense matrix

D Diagonal matrix

CSR format compresses rows and is optimized for fast row slicing.

Explain how the CSC format stores a sparse matrix and why it is useful.

Think about how columns are compressed and what arrays are needed.

Describe the difference between CSC and CSR formats and when to use each.

Focus on which dimension is compressed and the typical operations.