Boolean filtering in Data Analysis Python - Mini Project: Build & Apply

Boolean Filtering

📖 Scenario: You work in a small store and have a list of products with their prices. You want to find which products are affordable for customers who want to spend less than a certain amount.

🎯 Goal: Build a program that filters products based on a price limit using boolean filtering.

📋 What You'll Learn

Create a dictionary with product names as keys and prices as values

Create a variable for the price limit

Use boolean filtering to select products cheaper than the price limit

Print the filtered products

💡 Why This Matters

🌍 Real World

Filtering data based on conditions is common in stores, websites, and apps to show users only relevant items within their budget.

💼 Career

Data filtering is a basic skill for data analysts and scientists to prepare and analyze data efficiently.

1

Create the product price dictionary

Create a dictionary called products with these exact entries: 'apple': 120, 'banana': 80, 'cherry': 150, 'date': 60, 'elderberry': 200.

Data Analysis Python

# Create the products dictionary with given prices
# Your code here

Need a hint?

Use curly braces to create a dictionary with product names as keys and prices as values.

2

Set the price limit

Create a variable called price_limit and set it to 100.

Data Analysis Python

products = {'apple': 120, 'banana': 80, 'cherry': 150, 'date': 60, 'elderberry': 200}
# Set the price_limit variable to 100
# Your code here

Need a hint?

Just assign the number 100 to the variable price_limit.

3

Filter products cheaper than the price limit

Create a dictionary called affordable_products using a dictionary comprehension that includes only products from products with prices less than price_limit. Use for product, price in products.items() in your comprehension.

Data Analysis Python

products = {'apple': 120, 'banana': 80, 'cherry': 150, 'date': 60, 'elderberry': 200}
price_limit = 100
# Create affordable_products dictionary with products cheaper than price_limit
# Your code here

Need a hint?

Use a dictionary comprehension with an if condition to filter products.

4

Print the affordable products

Print the affordable_products dictionary.

Data Analysis Python

products = {'apple': 120, 'banana': 80, 'cherry': 150, 'date': 60, 'elderberry': 200}
price_limit = 100
affordable_products = {product: price for product, price in products.items() if price < price_limit}
# Print the affordable_products dictionary
# Your code here

Need a hint?

Use print(affordable_products) to show the filtered dictionary.