This project analyzes retail sales data to extract actionable business insights. It answers key questions such as the best month for sales, top-performing cities, optimal advertisement timing, and most frequently sold product combinations.
The analysis is done using Python, with Pandas for data manipulation and Matplotlib/Seaborn for visualization.
git clone https://github.com/Gireeshs02/sales-data-analysis.git
cd sales-data-analysis
pip install -r requirements.txt
jupyter notebook
Open the notebook file and run all the cells to see the analysis.
Contributions are welcome! Feel free to open issues, submit pull requests, or suggest improvements.
This project is licensed under the MIT License - see the LICENSE file for details.