Adding and removing columns in Data Analysis Python - Mini Project: Build & Apply

Adding and removing columns

📖 Scenario: You work in a small grocery store. You have a table of products with their prices and quantities. You want to add a new column for the total value of each product (price times quantity). Later, you decide to remove the quantity column to keep the table simple.

🎯 Goal: Create a data table using a dictionary, add a new column for total value, then remove the quantity column, and finally display the updated table.

📋 What You'll Learn

Create a dictionary called products with keys 'Name', 'Price', and 'Quantity' and the exact values specified.

Create a new column 'TotalValue' by multiplying Price and Quantity for each product.

Remove the 'Quantity' column from the dictionary.

Print the final products dictionary.

💡 Why This Matters

🌍 Real World

Stores and businesses often keep product data in tables. Adding and removing columns helps update the data as needed.

💼 Career

Data analysts and scientists frequently manipulate tables by adding calculated columns and cleaning data by removing unnecessary columns.

1

Create the initial products dictionary

Create a dictionary called products with these exact keys and values: 'Name' with the list ['Apple', 'Banana', 'Carrot'], 'Price' with the list [0.5, 0.3, 0.2], and 'Quantity' with the list [10, 20, 15].

Data Analysis Python

# Create the products dictionary with Name, Price, and Quantity
# Your code here

Need a hint?

Use a dictionary with keys 'Name', 'Price', and 'Quantity'. Each key should have a list of values.

2

Add a new column for total value

Create a new key 'TotalValue' in the products dictionary. Set its value to a list where each element is the product of the corresponding Price and Quantity values.

Data Analysis Python

products = {
    'Name': ['Apple', 'Banana', 'Carrot'],
    'Price': [0.5, 0.3, 0.2],
    'Quantity': [10, 20, 15]
}
# Add the TotalValue column by multiplying Price and Quantity
# Your code here

Need a hint?

Use a list comprehension with zip(products['Price'], products['Quantity']) to multiply each pair.

3

Remove the Quantity column

Remove the 'Quantity' key and its values from the products dictionary using the del statement.

Data Analysis Python

products = {
    'Name': ['Apple', 'Banana', 'Carrot'],
    'Price': [0.5, 0.3, 0.2],
    'Quantity': [10, 20, 15]
}
products['TotalValue'] = [p * q for p, q in zip(products['Price'], products['Quantity'])]
# Remove the Quantity column from products
# Your code here

Need a hint?

Use del products['Quantity'] to remove the column.

4

Print the final products dictionary

Print the products dictionary to display the updated table with the 'Name', 'Price', and 'TotalValue' columns.

Data Analysis Python

products = {
    'Name': ['Apple', 'Banana', 'Carrot'],
    'Price': [0.5, 0.3, 0.2],
    'Quantity': [10, 20, 15]
}
products['TotalValue'] = [p * q for p, q in zip(products['Price'], products['Quantity'])]
del products['Quantity']
# Print the products dictionary
# Your code here

Need a hint?

Use print(products) to show the final dictionary.