Sparse matrix file I/O in SciPy - Mini Project: Build & Apply

Sparse matrix file I/O

📖 Scenario: You work with large datasets that have many zero values. To save space, you use sparse matrices. You want to save your sparse matrix to a file and then load it back later.

🎯 Goal: Create a sparse matrix, save it to a file, load it back from the file, and print the loaded matrix.

📋 What You'll Learn

Use scipy.sparse to create a sparse matrix

Save the sparse matrix to a file using scipy.sparse.save_npz

Load the sparse matrix from the file using scipy.sparse.load_npz

Print the loaded sparse matrix

💡 Why This Matters

🌍 Real World

Sparse matrices are used in machine learning, scientific computing, and data storage when data has many zeros. Saving and loading them efficiently saves disk space and speeds up processing.

💼 Career

Data scientists and engineers often work with large sparse datasets. Knowing how to save and load sparse matrices is important for managing data pipelines and model training.

1

Create a sparse matrix

Import scipy.sparse and create a 3x3 sparse matrix called matrix with these values: 1 at (0,0), 2 at (1,1), and 3 at (2,2) using scipy.sparse.csr_matrix.

SciPy

# Import scipy.sparse and create the sparse matrix called matrix
# Your code here

Need a hint?

Use scipy.sparse.csr_matrix with a list of lists to create the sparse matrix.

2

Set the filename for saving

Create a variable called filename and set it to the string 'matrix.npz' to use as the file name for saving the sparse matrix.

SciPy

import scipy.sparse
matrix = scipy.sparse.csr_matrix([[1, 0, 0], [0, 2, 0], [0, 0, 3]])
# Create the filename variable
# Your code here

Need a hint?

Just assign the string 'matrix.npz' to the variable filename.

3

Save and load the sparse matrix

Use scipy.sparse.save_npz to save matrix to filename. Then use scipy.sparse.load_npz to load the matrix back into a variable called loaded_matrix.

SciPy

import scipy.sparse
matrix = scipy.sparse.csr_matrix([[1, 0, 0], [0, 2, 0], [0, 0, 3]])
filename = 'matrix.npz'
# Save matrix to filename and load it back into loaded_matrix
# Your code here

Need a hint?

Use scipy.sparse.save_npz(filename, matrix) to save and loaded_matrix = scipy.sparse.load_npz(filename) to load.

4

Print the loaded sparse matrix

Print the variable loaded_matrix to display the loaded sparse matrix.

SciPy

import scipy.sparse
matrix = scipy.sparse.csr_matrix([[1, 0, 0], [0, 2, 0], [0, 0, 3]])
filename = 'matrix.npz'
scipy.sparse.save_npz(filename, matrix)
loaded_matrix = scipy.sparse.load_npz(filename)
# Print the loaded_matrix
# Your code here

Need a hint?

Use print(loaded_matrix) to show the sparse matrix.