📊 Mobile Sales Data Pipeline

📋 Project Description

This project focuses on cleaning and analyzing sales data of mobile phones from different regions.
Main tasks include:

• Filling missing values in Quantity, Price, and Order ID.
• Converting Date to the standard YYYY-MM-DD format.
• Checking for duplicate Order IDs.
• Calculating Total Sales for each order.
• Summarizing sales by region.

🏗️ Steps Performed

1. Load data from data/sales_data.csv.
2. Check for duplicate Order IDs and print warnings.
3. Handle missing values:
   • Fill Quantity and Price with their column averages.
   • Drop rows missing Order ID.
4. Format Date to YYYY-MM-DD.
5. Compute Total Sales = Quantity * Price.
6. Group and sum sales by region.
7. Save the cleaned data to the output/ folder.

🚨 Notes

• Duplicate Order IDs are only printed, not removed (can be enabled in code).
• NumPy is used for basic validation tasks.

🖥️ Requirements

• Python 3.x
• pandas
• numpy

Install dependencies with:

pip install -r requirements.txt

🧑‍💻 Author

Kavin Kishore
B.Tech Student, DTU
Built as a real-time data engineering mini project.