Solving linear systems (solve) in SciPy - Mini Project: Build & Apply

Solving linear systems (solve)

📖 Scenario: You work as a data analyst for a small company. You need to solve a system of linear equations to find unknown values that represent quantities of products sold.

🎯 Goal: Build a Python program that uses scipy.linalg.solve to find the solution of a system of linear equations.

📋 What You'll Learn

Create a 2D list called A representing the coefficients matrix of the system

Create a list called b representing the constants vector

Use scipy.linalg.solve to solve the system Ax = b

Print the solution vector

💡 Why This Matters

🌍 Real World

Solving linear systems is common in engineering, physics, and economics to find unknown quantities from known relationships.

💼 Career

Data scientists and analysts often solve linear systems when working with models, optimizations, and simulations.

1

Create the coefficients matrix A

Create a 2D list called A with these exact rows: [3, 1] and [1, 2].

SciPy

# Create the coefficients matrix A
# Your code here

Need a hint?

Think of A as a list of lists, where each inner list is a row of numbers.

2

Create the constants vector b

Create a list called b with these exact values: 9 and 8.

SciPy

A = [[3, 1], [1, 2]]
# Create the constants vector b
# Your code here

Need a hint?

b is a list with the numbers on the right side of the equations.

3

Use scipy.linalg.solve to solve the system

Import solve from scipy.linalg and create a variable called solution by calling solve(A, b).

SciPy

A = [[3, 1], [1, 2]]
b = [9, 8]
# Import solve and solve the system
# Your code here

Need a hint?

Use from scipy.linalg import solve to import the function.

4

Print the solution vector

Print the variable solution to display the solution of the system.

SciPy

from scipy.linalg import solve

A = [[3, 1], [1, 2]]
b = [9, 8]

solution = solve(A, b)
# Print the solution
# Your code here

Need a hint?

Use print(solution) to show the answer.