This project analyzes retail sales data using Python, SQL, and SQLite.
- Python
- SQL
- SQLite
- Pandas
- Matplotlib
- Seaborn
This project implements a simple data pipeline:
- Extract – Load retail sales CSV dataset
- Transform – Clean column names, remove duplicates, handle missing values
- Load – Store processed data in SQLite database
- Analyze – Execute SQL queries to extract insights
- Visualize – Generate charts using Python
• Revenue by product category
• Regional sales performance
• Top performing product sub-categories
Install dependencies
pip install pandas matplotlib seaborn
Load dataset
python load_data.py
Run analysis
python run_analysis.py