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# Example 1: Simple arithmetic with numbers
total_sales = 150 + 300 + 450
print("Total Sales:", total_sales)  # Output: 900

# Example 2: Using variables in expressions
price = 50
quantity = 4
total_cost = price * quantity
print("Total Cost:", total_cost)  # Output: 200

# Example 3: Combining operations
discount = 20
final_price = (price * quantity) - discount
print("Final Price after Discount:", final_price)  # Output: 180

# Example 4: Average calculation
score1 = 80
score2 = 90
score3 = 70
average_score = (score1 + score2 + score3) / 3
print("Average Score:", average_score)  # Output: 80.0

# Expressions and Arithmetic

In data analysis, you often compute totals, differences, averages, and more.

Python does this through *expressions*, which are pieces of code that produce a result.

<br/>

## What Is an Expression?

An expression is any combination of *values*, *variables*, and *operators* that Python can evaluate to produce a result.

Some examples:

- `42`: a literal number
- `5 + 3`: an addition expression
- `price * quantity`: a multiplication using variables

If Python can run it and return a value, it's an expression.

<br/>

## Arithmetic in Data Analysis

Data analysts use arithmetic to:

- Add values (e.g., total sales)
- Calculate growth rates or discounts
- Find averages and differences

Learning to build expressions is the foundation for processing and analyzing real-world data.

<br/>

## What You'll Practice

In the code block below, you will:

- Add and multiply numbers
- Work with variables
- Use expressions to calculate useful results

Run the examples and try changing the values to see how the output changes.

To calculate total sales, you multiply the price of each item by the quantity sold. This gives you the total revenue generated from selling that number of items. Expressions like 'price * quantity' are essential for performing such calculations in data analysis.

### Use an arithmetic expression to calculate the total sales from price and quantity.