## Jupyter Integration

This project includes Jupyter notebook support for interactive development and data analysis. Jupyter provides an interactive computing environment that combines code, visualizations, and documentation.

### Features

- **Interactive Notebooks**: Create and run `.ipynb` notebooks
- **Rich Output**: Support for code, markdown, equations, and visualizations
- **Kernel Management**: Multiple Python kernels support
- **Extension System**: Extensible through Jupyter extensions

### Common Commands

```bash
# Start Jupyter Notebook
jupyter notebook

# Start Jupyter Lab
jupyter lab

# List installed kernels
jupyter kernelspec list

# Install a new kernel
python -m ipykernel install --user --name=myenv
```

### Project Structure

The project includes:
- `notebooks/`: Directory containing Jupyter notebooks
- `.ipynb` files: Interactive notebooks
- `ipython_config.py`: IPython configuration (if present)

### Development

To start using Jupyter:
1. Ensure Jupyter is installed in your environment
2. Run `jupyter notebook` or `jupyter lab` to start the server
3. Create new notebooks or open existing ones
4. Use the notebook interface for interactive development

### Best Practices

- Keep notebooks focused and well-documented
- Use markdown cells for documentation
- Consider using `nbconvert` for notebook conversion
- Version control notebooks with clear outputs

For more information, visit [Jupyter's official documentation](https://jupyter.org/documentation). 