Selecting rows by condition in Pandas - Mini Project: Build & Apply

Selecting rows by condition

📖 Scenario: You work in a small bookstore. You have a list of books with their prices and want to find which books cost more than $20.

🎯 Goal: Build a program that selects and shows only the books priced above $20 from the list.

📋 What You'll Learn

Create a pandas DataFrame with book titles and prices

Create a variable to hold the price threshold

Use a condition to select rows where price is greater than the threshold

Print the filtered DataFrame

💡 Why This Matters

🌍 Real World

Filtering data by conditions is common in business to find important items, like expensive products or customers with high spending.

💼 Career

Data analysts and scientists often filter datasets to focus on relevant information for reports and decisions.

1

Create the books DataFrame

Import pandas as pd. Create a DataFrame called books with these exact entries: titles 'Book A', 'Book B', 'Book C', and prices 15, 25, 30 respectively.

Pandas

import pandas as pd
# Create the DataFrame called books with titles and prices
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary containing lists for titles and prices.

2

Set the price threshold

Create a variable called price_threshold and set it to 20.

Pandas

import pandas as pd
books = pd.DataFrame({
    'title': ['Book A', 'Book B', 'Book C'],
    'price': [15, 25, 30]
})
# Create price_threshold variable and set it to 20
# Your code here

Need a hint?

Just assign the number 20 to the variable price_threshold.

3

Select books priced above the threshold

Create a new DataFrame called expensive_books by selecting rows from books where the price column is greater than price_threshold.

Pandas

import pandas as pd
books = pd.DataFrame({
    'title': ['Book A', 'Book B', 'Book C'],
    'price': [15, 25, 30]
})
price_threshold = 20
# Select rows where price > price_threshold into expensive_books
# Your code here

Need a hint?

Use books[books['price'] > price_threshold] to filter rows.

4

Print the filtered books

Print the expensive_books DataFrame to show the books priced above $20.

Pandas

import pandas as pd
books = pd.DataFrame({
    'title': ['Book A', 'Book B', 'Book C'],
    'price': [15, 25, 30]
})
price_threshold = 20
expensive_books = books[books['price'] > price_threshold]
# Print expensive_books
# Your code here

Need a hint?

Use print(expensive_books) to display the filtered DataFrame.