🧹 Data Duster – The Ultimate Data Cleaning & Processing Tool

🚀 Introduction

Data Duster is an intelligent web application developed by SMAASU Corporation to simplify data cleaning and processing. Whether you’re dealing with messy datasets in CSV or XLSX format, Data Duster ensures clean, structured, and optimized data in just a few clicks.

✨ Key Features

• 📂 Upload Dataset – Supports CSV and XLSX files.
• 🧹 Smart Cleaning – Remove duplicates, handle null values, and fill missing data.
• 📊 Selective Processing – Choose specific columns for refinement.
• 📈 Data Visualization – Generate insightful graphs for better analysis.
• 🔄 Format Conversion – Convert files into different formats effortlessly.
• 💾 Download Processed Data – Get the refined dataset instantly.

🛠️ Installation

To run Data Duster locally, follow these steps:

# Clone the repository
git clone https://github.com/smaasui/Data-Duster.git

# Navigate to the project directory
cd Data-Duster

# Install dependencies
pip install -r requirements.txt

# Run the Streamlit app
streamlit run app.py

📌 Usage

1. Upload a dataset in CSV or XLSX format.
2. Select cleaning options (remove duplicates, fill missing values, etc.).
3. Choose specific columns for processing.
4. Visualize data insights using charts.
5. Download the refined dataset in the desired format.
6. Check password security and get recommendations.

🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the repository
2. Create a new branch (feature-branch)
3. Commit your changes (git commit -m "Added a new feature")
4. Push to the branch (git push origin feature-branch)
5. Open a pull request

📜 License

This project is licensed under the MIT License.

💬 Contact

For any queries or suggestions, reach out to us at smaasu01@gmail.com or visit SMAASU Corporation.

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🌟 Enjoy seamless data cleaning and thanks to SMAASU I ! 🌟