Logical operations (and, or, not) in NumPy - Mini Project: Build & Apply

Logical Operations with NumPy Arrays

📖 Scenario: Imagine you work in a store that tracks daily sales of two products. You want to find days when certain sales conditions are met using logical operations.

🎯 Goal: You will create two NumPy arrays representing daily sales of two products. Then, you will use logical and, or, and not operations to find days matching specific sales conditions.

📋 What You'll Learn

Create two NumPy arrays named product_a_sales and product_b_sales with exact daily sales values.

Create a threshold variable named threshold with the exact value 50.

Use logical operations np.logical_and, np.logical_or, and np.logical_not on the sales arrays.

Print the final results arrays exactly as specified.

💡 Why This Matters

🌍 Real World

Stores and businesses often analyze sales data to find days when multiple products perform well or need attention.

💼 Career

Data analysts and scientists use logical operations on arrays to filter and analyze large datasets efficiently.

1

Create sales data arrays

Import NumPy as np. Create two NumPy arrays called product_a_sales and product_b_sales with these exact values: [30, 60, 45, 80, 55] and [20, 70, 50, 40, 65] respectively.

NumPy

import numpy as np
# Create product_a_sales and product_b_sales arrays with given values
# Your code here

Need a hint?

Use np.array([...]) to create the arrays with the exact numbers given.

2

Set sales threshold

Create a variable called threshold and set it to the integer value 50.

NumPy

import numpy as np
product_a_sales = np.array([30, 60, 45, 80, 55])
product_b_sales = np.array([20, 70, 50, 40, 65])
# Create threshold variable with value 50
# Your code here

Need a hint?

Just assign the number 50 to the variable named threshold.

3

Apply logical operations

Create three variables: both_above using np.logical_and to find days when both products have sales above threshold, either_above using np.logical_or to find days when either product has sales above threshold, and not_a_above using np.logical_not to find days when product A sales are NOT above threshold.

NumPy

import numpy as np
product_a_sales = np.array([30, 60, 45, 80, 55])
product_b_sales = np.array([20, 70, 50, 40, 65])
threshold = 50
# Create both_above, either_above, and not_a_above using logical operations
# Your code here

Need a hint?

Use comparisons like product_a_sales > threshold inside the logical functions.

4

Print the results

Print the variables both_above, either_above, and not_a_above each on a separate line in this order.

NumPy

import numpy as np
product_a_sales = np.array([30, 60, 45, 80, 55])
product_b_sales = np.array([20, 70, 50, 40, 65])
threshold = 50
both_above = np.logical_and(product_a_sales > threshold, product_b_sales > threshold)
either_above = np.logical_or(product_a_sales > threshold, product_b_sales > threshold)
not_a_above = np.logical_not(product_a_sales > threshold)
# Print both_above, either_above, and not_a_above
# Your code here

Need a hint?

Use three separate print() statements for each variable in the order given.