Creating new columns in Pandas - Try It Yourself

Creating new columns

📖 Scenario: You work in a small store that keeps track of products and their prices. You want to add new information to your data to help with sales.

🎯 Goal: Create a new column in a pandas DataFrame that shows the price after a 10% discount.

📋 What You'll Learn

Create a pandas DataFrame with product names and prices

Create a variable for the discount rate

Add a new column with discounted prices using the discount rate

Print the updated DataFrame

💡 Why This Matters

🌍 Real World

Stores often need to update prices with discounts or taxes to help customers and manage sales.

💼 Career

Data analysts and data scientists use pandas to prepare and analyze sales data, including creating new columns for calculations.

1

Create the initial DataFrame

Create a pandas DataFrame called products with two columns: 'Product' and 'Price'. The DataFrame should have these exact rows: 'Apple' with price 1.0, 'Banana' with price 0.5, and 'Cherry' with price 2.0.

Pandas

# Create the DataFrame called products with the given data
# Your code here

Need a hint?

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

2

Set the discount rate

Create a variable called discount_rate and set it to 0.10 to represent a 10% discount.

Pandas

import pandas as pd

products = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Cherry'],
    'Price': [1.0, 0.5, 2.0]
})

# Create the discount_rate variable and set it to 0.10
# Your code here

Need a hint?

Just assign 0.10 to the variable discount_rate.

3

Add a new column with discounted prices

Create a new column in the products DataFrame called 'Discounted Price'. Calculate it by subtracting the discount from the original 'Price' using the discount_rate variable.

Pandas

import pandas as pd

products = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Cherry'],
    'Price': [1.0, 0.5, 2.0]
})

discount_rate = 0.10

# Add the 'Discounted Price' column to products
# Your code here

Need a hint?

Multiply the 'Price' column by (1 - discount_rate) to get the discounted price.

4

Print the updated DataFrame

Print the products DataFrame to show the new 'Discounted Price' column.

Pandas

import pandas as pd

products = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Cherry'],
    'Price': [1.0, 0.5, 2.0]
})

discount_rate = 0.10

products['Discounted Price'] = products['Price'] * (1 - discount_rate)

# Print the products DataFrame
# Your code here

Need a hint?

Use print(products) to display the DataFrame.