Combining conditions in NumPy - Mini Project: Build & Apply

Filtering Data with Combined Conditions using NumPy

📖 Scenario: You work in a store and have a list of product prices. You want to find which products are both affordable and on sale.

🎯 Goal: Learn how to use NumPy to filter data by combining two conditions.

📋 What You'll Learn

Create a NumPy array with given prices

Create a price limit variable

Use combined conditions with NumPy to find affordable and on-sale products

Print the filtered prices

💡 Why This Matters

🌍 Real World

Filtering data with multiple conditions is common in sales, finance, and many other fields to find items that meet several criteria.

💼 Career

Data scientists and analysts often combine conditions to clean and analyze data efficiently using tools like NumPy.

1

Create the prices array

Create a NumPy array called prices with these exact values: 10, 25, 30, 45, 50, 60.

NumPy

import numpy as np
# Create the prices array with the exact values
# Your code here

Need a hint?

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

2

Set the price limit

Create a variable called price_limit and set it to 40.

NumPy

import numpy as np
prices = np.array([10, 25, 30, 45, 50, 60])
# Create price_limit variable and set it to 40
# Your code here

Need a hint?

Just assign the number 40 to the variable price_limit.

3

Filter prices with combined conditions

Create a variable called affordable_and_on_sale that selects prices from prices which are less than price_limit and also less than 50. Use combined conditions with & and parentheses.

NumPy

import numpy as np
prices = np.array([10, 25, 30, 45, 50, 60])
price_limit = 40
# Use combined conditions to filter prices less than price_limit and less than 50
# Your code here

Need a hint?

Use parentheses around each condition and combine them with & inside the brackets.

4

Print the filtered prices

Print the variable affordable_and_on_sale to see the filtered prices.

NumPy

import numpy as np
prices = np.array([10, 25, 30, 45, 50, 60])
price_limit = 40
affordable_and_on_sale = prices[(prices < price_limit) & (prices < 50)]
# Print the filtered prices
# Your code here

Need a hint?

Use print(affordable_and_on_sale) to show the result.