ExploreMyData

Automated Exploratory Data Analysis (EDA) for your datasets. Upload a CSV file, select your ML task, and get comprehensive insights in seconds.

https://www.exploremydata.xyz/

Features

Data Processing

• Drag and drop CSV file upload
• Automatic data cleaning and preprocessing
• Missing value detection and imputation
• Duplicate row detection
• Data type inference

ML Task Support

• Classification - Class distribution, imbalance detection, feature-target correlations
• Regression - Target distribution, linearity analysis, residual patterns
• NLP / Text Analysis - Text statistics, vocabulary analysis, label distribution
• Computer Vision - Image path detection, class balance, augmentation suggestions

Comprehensive EDA

• Data quality reports with actionable insights
• Statistical summaries (describe, dtypes, info)
• Missing value patterns and heatmaps
• Outlier detection using IQR method
• Feature correlations and multicollinearity (VIF)
• Target leakage detection
• Baseline model performance estimates
• Text feature analysis for ML engineers

Export Options

• Save individual charts as PNG images
• Export full EDA report as PDF
• Copy Python code snippets to reproduce analysis

Getting Started

Installation

# Clone the repository
git clone https://github.com/kavyachouhan/ExploreMyData.git
cd ExploreMyData

# Install dependencies
pnpm install

# Run development server
pnpm dev

Open http://localhost:3000 to view the application.

Environment Variables

Create a .env.local file in the root directory:

# Appwrite Configuration (Optional - for upload logging)
NEXT_PUBLIC_APPWRITE_ENDPOINT=https://cloud.appwrite.io/v1
NEXT_PUBLIC_APPWRITE_PROJECT_ID=your_project_id
NEXT_PUBLIC_APPWRITE_DATABASE_ID=your_database_id
NEXT_PUBLIC_APPWRITE_UPLOAD_LOGS_COLLECTION_ID=upload_logs

Project Structure

├── app/                    # Next.js App Router pages
│   ├── explore/           # Main explore flow
│   │   ├── insight/       # EDA results page
│   │   └── questions/     # Task selection page
│   ├── privacy/           # Privacy policy
│   └── terms/             # Terms of service
├── components/
│   ├── charts/            # Chart components
│   ├── eda/               # EDA analysis components
│   ├── explore/           # Upload and navigation
│   ├── layout/            # Header, Footer
│   ├── report/            # PDF export
│   └── ui/                # Reusable UI components
├── context/               # React Context providers
├── lib/                   # Utility functions
│   ├── dataUtils.ts       # Data cleaning utilities
│   └── edaUtils.ts        # EDA analysis functions
└── public/                # Static assets

.M

Scripts

pnpm dev          # Start development server
pnpm build        # Build for production
pnpm start        # Start production server
pnpm lint         # Run ESLint

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License.

Contact

For questions or feedback, please open an issue on GitHub.