Task 7: Basic Sales Summary using SQLite and Python

Objective

Use SQL inside Python to pull sales info (like total quantity sold, total revenue) and visualize it.

Tools Used

• Python (sqlite3, pandas, matplotlib)
• SQLite (built into Python, no setup required)

Steps

1. Created a SQLite database sales_data.db with a sales table.
2. Inserted sample sales records (products, quantity, price).
3. Ran SQL queries inside Python using sqlite3.
4. Loaded results into pandas DataFrame.
5. Printed the sales summary.
6. Visualized revenue by product using matplotlib.

Example Output

Sales Summary:

Product	Total Quantity	Revenue
Laptop	8	474000
Mobile	18	274000
Tablet	10	206000
Headphones	19	43500

Bar Chart: Revenue by Product (saved as sales_chart.png)

Interview Questions

• How did you connect Python to a database?
• What SQL query did you run?
• What does GROUP BY do?
• How did you calculate revenue?
• How did you visualize the result?
• What does pandas do in your code?
• What’s the benefit of using SQL inside Python?

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✅ Submission ready!