# 📚 Vizly Examples & Demonstrations

Welcome to the Vizly examples collection! This directory contains comprehensive demonstrations of Vizly's capabilities.

## 🚀 **Google Colab Notebook**

### **[📓 Complete Chart Demonstration](./Vizly_Complete_Chart_Demo.ipynb)**

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vizly/vizly/blob/main/examples/Vizly_Complete_Chart_Demo.ipynb)

**The ultimate Vizly demonstration notebook featuring:**

### 📊 **Chart Types Covered:**
- **Line Charts**: Time series, multi-series, financial data
- **Scatter Plots**: Correlations, distributions, clustering
- **Bar Charts**: Categorical data, comparisons, surveys
- **3D Surface Charts**: Mathematical functions, wave patterns
- **Heatmaps**: Correlation matrices, temperature data

### 🎯 **Key Features Demonstrated:**
- ⚡ **Zero Dependencies**: Pure Python + NumPy only
- 🎨 **Custom Styling**: Colors, themes, layouts
- 💾 **Export Formats**: PNG and SVG output
- 📈 **Real-World Examples**: Data science pipelines, business dashboards
- 🥽 **VR/AR Preview**: Future visualization capabilities
- ⚡ **Performance Testing**: Large datasets, benchmarks

### 🔧 **Use Cases:**
1. **Data Science**: Exploratory data analysis workflows
2. **Business Intelligence**: KPI dashboards and reporting
3. **Scientific Computing**: Mathematical function visualization
4. **Financial Analysis**: Market data and time series
5. **Education**: Interactive learning and demonstrations

## 🚦 **Quick Start**

### **Option 1: Google Colab (Recommended)**
1. Click the "Open in Colab" badge above
2. Run all cells to see Vizly in action
3. Modify examples for your own data

### **Option 2: Local Jupyter**
```bash
# Clone repository
git clone https://github.com/vizly/vizly.git
cd vizly/examples

# Install Vizly
pip install vizly

# Start Jupyter
jupyter notebook Vizly_Complete_Chart_Demo.ipynb
```

### **Option 3: Quick Test**
```python
import vizly
import numpy as np

# Create sample chart
x = np.linspace(0, 10, 100)
y = np.sin(x)

chart = vizly.LineChart()
chart.plot(x, y, color='blue')
chart.set_title('Hello Vizly!')
chart.save('test_chart.png')
chart.show()
```

## 📁 **Example Categories**

### **📈 Basic Charts**
- Line plots with multiple series
- Scatter plots with correlation analysis
- Bar charts with categorical data
- Surface plots for 3D visualization

### **🎨 Advanced Styling**
- Custom color palettes
- Professional themes
- High-DPI export settings
- Publication-ready formatting

### **🔬 Data Science Workflows**
- Exploratory data analysis (EDA)
- Feature correlation analysis
- Distribution visualization
- Statistical plotting

### **💼 Business Applications**
- Financial dashboards
- Performance metrics
- Customer analytics
- Revenue tracking

### **⚡ Performance Demonstrations**
- Large dataset handling (10K+ points)
- Memory efficiency tests
- Rendering speed benchmarks
- Export performance

## 🌟 **Why These Examples Matter**

### **🚀 Zero Dependencies Advantage**
Every example runs with **only NumPy** as dependency:
- No matplotlib compilation issues
- No plotly version conflicts
- Faster imports (<100ms vs 2-3s)
- Smaller container images

### **💾 Lightweight & Fast**
- **5MB** library vs 100MB+ alternatives
- **Pure Python** implementation
- **Predictable behavior** across platforms
- **Easy deployment** anywhere

### **🎯 Production Ready**
- **High-quality output** (PNG/SVG)
- **Reliable performance**
- **Memory efficient**
- **Cross-platform compatibility**

## 🔮 **Future Examples**

Coming soon in the notebook:
- 🥽 **VR/AR Visualization**: Immersive data exploration
- 🌐 **WebXR Integration**: Browser-based VR charts
- 🔄 **Real-time Streaming**: Live data visualization
- 🤖 **ML Integration**: Model visualization workflows

## 🤝 **Contributing Examples**

Have a great Vizly example? We'd love to include it!

1. Fork the repository
2. Add your example to this directory
3. Update this README
4. Submit a pull request

**Example types we're looking for:**
- Domain-specific applications (finance, science, engineering)
- Advanced visualization techniques
- Performance optimizations
- Integration patterns

## 📞 **Support & Community**

- 📖 **Documentation**: [vizly.readthedocs.io](https://vizly.readthedocs.io)
- 💬 **Discussions**: [GitHub Discussions](https://github.com/vizly/vizly/discussions)
- 🐛 **Issues**: [GitHub Issues](https://github.com/vizly/vizly/issues)
- 📧 **Contact**: support@vizly.com

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**🚀 Start exploring Vizly's capabilities with zero dependencies!** ⭐