Matrix creation and operations in SciPy - Mini Project: Build & Apply

Matrix creation and operations

📖 Scenario: You are working as a data analyst and need to create and manipulate matrices to analyze data patterns. Matrices are like grids of numbers, similar to tables you see in spreadsheets.

🎯 Goal: Build a small project where you create a matrix using scipy, set a configuration value for matrix size, perform a matrix operation (like addition), and then display the result.

📋 What You'll Learn

Use scipy to create matrices

Create a matrix with exact values

Set a configuration variable for matrix size

Perform matrix addition using scipy

Print the resulting matrix

💡 Why This Matters

🌍 Real World

Matrices are used in data science to represent data tables, images, and networks. Sparse matrices help save memory when data has many zeros.

💼 Career

Understanding matrix operations is essential for roles in data analysis, machine learning, and scientific computing.

1

Create a 2x2 matrix using scipy

Import scipy.sparse and create a 2x2 matrix called matrix_a with these exact values: [[1, 2], [3, 4]] using scipy.sparse.csr_matrix.

SciPy

# Your code here

Need a hint?

Use csr_matrix from scipy.sparse to create the matrix.

2

Set matrix size configuration

Create a variable called matrix_size and set it to 2 to represent the size of the matrix.

SciPy

from scipy.sparse import csr_matrix
matrix_a = csr_matrix([[1, 2], [3, 4]])
# Your code here

Need a hint?

Just create a variable matrix_size and assign it the value 2.

3

Create another matrix and add it to the first

Create another 2x2 matrix called matrix_b with values [[5, 6], [7, 8]] using csr_matrix. Then create a new matrix called matrix_sum by adding matrix_a and matrix_b.

SciPy

from scipy.sparse import csr_matrix
matrix_a = csr_matrix([[1, 2], [3, 4]])
matrix_size = 2
# Your code here

Need a hint?

Create matrix_b like matrix_a but with new values, then add them with matrix_sum = matrix_a + matrix_b.

4

Print the resulting matrix

Print the dense array form of matrix_sum using the .toarray() method inside a print() statement.

SciPy

from scipy.sparse import csr_matrix
matrix_a = csr_matrix([[1, 2], [3, 4]])
matrix_size = 2
matrix_b = csr_matrix([[5, 6], [7, 8]])
matrix_sum = matrix_a + matrix_b
# Your code here

Need a hint?

Use print(matrix_sum.toarray()) to see the full matrix.