Python Basics Final Project

1. Project Dataset

Start with a list of sales transactions:

sales = [85000, 125000, 140000, 45000, 210000]

Each number represents the revenue generated by one transaction.

2. Calculate Total Revenue

total_revenue = sum(sales)

print(total_revenue)

The sum() function calculates the total of the numeric values.

3. Calculate Average Revenue

average_revenue = sum(sales) / len(sales)

print(average_revenue)

4. Find the Highest Sale

highest_sale = max(sales)

print(highest_sale)

5. Find the Lowest Sale

lowest_sale = min(sales)

print(lowest_sale)

6. Identify High-Value Sales

Management wants to know how many transactions are at least ₹100,000.

high_sales = []

for sale in sales:
    if sale >= 100000:
        high_sales.append(sale)

print(high_sales)

7. Count High-Value Sales

count = 0

for sale in sales:
    if sale >= 100000:
        count += 1

print(count)

8. Represent a Sales Record

sale = {
    "customer": "Aman",
    "region": "North",
    "revenue": 125000
}

print(sale["revenue"])

9. Work with Multiple Records

sales_data = [
    {"customer": "Aman", "region": "North", "revenue": 125000},
    {"customer": "Riya", "region": "South", "revenue": 85000},
    {"customer": "Karan", "region": "East", "revenue": 140000},
    {"customer": "Neha", "region": "West", "revenue": 210000}
]

for sale in sales_data:
    print(sale["customer"], sale["revenue"])

10. Create a Reusable Function

Instead of repeatedly writing the same calculation, create a function.

def calculate_profit(revenue, cost):
    return revenue - cost

profit = calculate_profit(125000, 75000)

print(profit)

11. Create a Function for Average Sales

def average_sales(values):
    return sum(values) / len(values)

sales = [100000, 120000, 80000]

print(average_sales(sales))

12. Debug the Project

Find the logical error:

def calculate_profit(revenue, cost):
    return revenue + cost

profit = calculate_profit(200000, 125000)

print(profit)

13. The Complete Analysis Workflow

1. Store the data.
2. Inspect the data.
3. Calculate totals and averages.
4. Filter important records.
5. Use functions for repeated calculations.
6. Check the results.
7. Debug incorrect calculations.

What Comes Next?

Python Basics is the foundation. The next courses can focus on specialized Python libraries and data analytics workflows.