Data Visualization Skill
This skill provides capabilities for creating data visualizations.
Quick Start
Using matplotlib for basic charts:
import matplotlib.pyplot as plt
# Simple line chart
plt.plot([1, 2, 3, 4], [1, 4, 2, 3])
plt.title("Sample Chart")
plt.savefig("chart.png")
Capabilities
Chart Types
- Line charts
- Bar charts
- Pie charts
- Scatter plots
- Histograms
- Box plots
- Heatmaps
Libraries Supported
- Matplotlib (static charts)
- Seaborn (statistical visualizations)
- Plotly (interactive charts)
- Altair (declarative visualization)
Advanced Features
- Multi-axis plots
- Subplots and grids
- Custom themes and styling
- Annotations and labels
- Export to various formats (PNG, SVG, PDF)
Best Practices
- Choose the right chart type for your data
- Use clear labels and titles
- Consider color accessibility
- Keep visualizations simple and focused
- Export at appropriate resolution for intended use
