A beautiful web app for automated data visualization and exploratory data analysis (EDA)
- Multi-format support: Upload CSV, Excel, JSON, or Parquet files
- Interactive Visualizations:
- Scatter, Line, Bar, Histogram, Box, Violin, and Pie charts
- Fully customizable axes and colors
- Zoom, pan, and hover interactions
- Automated EDA Reports:
- Complete statistical summary
- Correlation analysis
- Missing values detection
- Downloadable HTML report
- Beautiful UI:
- Modern, responsive design
- Dark/light mode compatible
- Informative data metrics cards
- Clone the repository:
git clone https://github.com/yourusername/data-viz-explorer.git
cd data-viz-explorer- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`- Install dependencies:
pip install -r requirements.txt streamlit run app.pyThe app will open in your default browser at http://localhost:8501
- Push your code to GitHub
- Sign up at Streamlit Sharing
- Click "New App" and connect your repository
heroku create your-app-name
git push heroku main| Data Preview | Interactive Visualization | EDA Report |
|---|---|---|
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- Frontend: Streamlit
- Backend: Python
- Data Processing: Pandas
- Visualization: Plotly, Altair
- EDA: Pandas-profiling
data-viz-explorer/
├── app.py # Main application code
├── style.css # Custom CSS styles
├── requirements.txt # Python dependencies
├── README.md # This file
└── .gitignore # Git ignore file
Contributions are welcome! Please follow these steps:
- Fork the project
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Dheeraj Kumar - 13kumardheeraj@gmail.com
Project Link: PROJECT LINK


