Multiple conditions with & and | in Pandas - Mini Project: Build & Apply

Filter Data with Multiple Conditions Using & and | in pandas

📖 Scenario: You work in a small online store. You have a list of products with their prices and stock counts. You want to find products that meet certain conditions to decide what to promote or reorder.

🎯 Goal: Build a pandas DataFrame with product data, set a price threshold, filter products using multiple conditions combined with & (and) and | (or), and display the filtered results.

📋 What You'll Learn

Create a pandas DataFrame named products with columns Product, Price, and Stock using the exact data provided.

Create a variable price_limit with the exact value 20.

Use multiple conditions combined with & and | to filter products where Price is less than price_limit and Stock is greater than 10, or where Product is exactly 'Notebook'.

Store the filtered DataFrame in a variable named filtered_products.

Print the filtered_products DataFrame.

💡 Why This Matters

🌍 Real World

Filtering data with multiple conditions is common in business to find products that meet specific criteria, like affordable price and enough stock.

💼 Career

Data analysts and scientists often filter datasets using multiple conditions to prepare data for reports, dashboards, or decision-making.

1

Create the products DataFrame

Create a pandas DataFrame called products with these exact columns and data: Product with values ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker'], Price with values [5, 25, 3, 2, 15], and Stock with values [50, 5, 100, 20, 0].

Pandas

import pandas as pd
# Create the products DataFrame with the exact data
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary where keys are column names and values are lists of data.

2

Set the price limit

Create a variable called price_limit and set it to the integer value 20.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker'],
    'Price': [5, 25, 3, 2, 15],
    'Stock': [50, 5, 100, 20, 0]
})
# Set price_limit to 20
# Your code here

Need a hint?

Just assign the number 20 to the variable price_limit.

3

Filter products with multiple conditions

Create a variable called filtered_products that filters products where Price is less than price_limit and Stock is greater than 10, or where Product is exactly 'Notebook'. Use parentheses and combine conditions with & and |.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker'],
    'Price': [5, 25, 3, 2, 15],
    'Stock': [50, 5, 100, 20, 0]
})
price_limit = 20
# Filter products with multiple conditions using & and |
# Your code here

Need a hint?

Use parentheses around each condition and combine them with & for AND and | for OR.

4

Print the filtered products

Print the filtered_products DataFrame to display the filtered results.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker'],
    'Price': [5, 25, 3, 2, 15],
    'Stock': [50, 5, 100, 20, 0]
})
price_limit = 20
filtered_products = products[((products['Price']  10)) | (products['Product'] == 'Notebook')]
# Print the filtered_products DataFrame
# Your code here

Need a hint?

Use print(filtered_products) to show the filtered DataFrame.