Superstore Chain Data Analytics Dashboard

Overview:

The Superstore Chain Data Analytics Dashboard is a powerful tool for analyzing sales and profit data from the Superstore retail chain in the USA. This interactive dashboard is built using Plotly and Streamlit, providing users with an intuitive interface to explore and visualize various aspects of the Superstore's performance.

Key Features:

• Filter data by Region, State, and City.
• Region-wise and category-wise sales analysis.
• Time series analysis of sales data.
• Month-wise sales and category sales insights.
• Relationship between Profit and Sales using a scatter plot.

Table of Contents

• Installation
• Usage
• Screenshots
• Contributing
• License

Installation

• Clone the repository: https://github.com/hrishi483/SuperStore_Dashboard.git.
• access requirements.txt file from here https://github.com/hrishi483/SuperStore_Dashboard/blob/main/requirements.txt.

##Usage Usage Run the Streamlit app: streamlit run app.py

• Open your web browser and navigate to the URL provided by Streamlit.
• Use the dashboard to filter and analyze Superstore data as needed.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push your branch to your fork.
5. Submit a pull request.

About Me:

• Name: Hrishikesh Ravindra Karande
• Email: [email protected]
• LinkedIn Profile: https://www.linkedin.com/in/hrishikesh-karande-4029ab226/

Feel free to customize this README to better fit your project. Include links to a live demo (if available), screenshots, and any other relevant information that can help users understand and use your dashboard. Good luck with your GitHub repository!