outer() for outer operations in NumPy - Mini Project: Build & Apply

Using numpy.outer() for Outer Product Calculation

📖 Scenario: Imagine you are working in a small business that sells two types of products: pens and notebooks. You want to find out all possible combinations of quantities of pens and notebooks to prepare bundles for sale.

🎯 Goal: Learn how to use numpy.outer() to calculate the outer product of two arrays representing quantities of pens and notebooks. This will help you see all possible combinations of these quantities.

📋 What You'll Learn

Create two numpy arrays with exact values for pens and notebooks quantities

Create a variable to hold the result of the outer product using numpy.outer()

Print the resulting matrix showing all combinations

💡 Why This Matters

🌍 Real World

Businesses often need to find all possible combinations of product quantities to create bundles or offers. Using outer product helps quickly calculate these combinations.

💼 Career

Data analysts and scientists use numpy's outer product to perform matrix operations and combinatorial calculations efficiently in many industries.

1

Create numpy arrays for pens and notebooks quantities

Import numpy as np. Create a numpy array called pens with values [1, 2, 3] and another numpy array called notebooks with values [4, 5].

NumPy

import numpy as np
# Create numpy arrays pens and notebooks
# Your code here

Need a hint?

Use np.array() to create arrays with the exact values given.

2

Create a variable for the outer product

Create a variable called combinations and assign to it the outer product of pens and notebooks using np.outer().

NumPy

import numpy as np
pens = np.array([1, 2, 3])
notebooks = np.array([4, 5])
# Calculate the outer product and store in combinations
# Your code here

Need a hint?

Use np.outer(pens, notebooks) to get all quantity combinations.

3

Print the combinations matrix

Use print() to display the variable combinations.

NumPy

import numpy as np
pens = np.array([1, 2, 3])
notebooks = np.array([4, 5])
combinations = np.outer(pens, notebooks)
# Print the combinations matrix
# Your code here

Need a hint?

Just print the combinations variable to see the matrix.

4

Interpret the output matrix

Print a message explaining that each row corresponds to a pen quantity and each column corresponds to a notebook quantity, showing all possible bundles.

NumPy

import numpy as np
pens = np.array([1, 2, 3])
notebooks = np.array([4, 5])
combinations = np.outer(pens, notebooks)
print(combinations)
# Print explanation message
# Your code here

Need a hint?

Use print() to show the explanation message exactly as given.