data-viz-plots

Create publication-quality plots locally using matplotlib and seaborn, compatible with any LLM provider.

• Generate scientific visualizations with matplotlib and seaborn
• Create scatter, line, box, violin, and heatmap plots
• Supports any LLM provider including GPT, Gemini, Claude, etc.
• Executes locally in user environment

• Local execution (no cloud dependency)
• Works with any LLM provider
• Supports multi-panel and complex figures
• High-resolution export (300 dpi)
• Customizable styling and aesthetics
• Includes error bars, grid, and legends
• Publishable figure quality
• No data upload or sharing

1. 1.Import libraries: matplotlib, seaborn, pandas, numpy
2. 2.Create basic plots (scatter, line, bar, box, violin, heatmap)
3. 3.Combine multiple plots in multi-panel figures using gridspec
4. 4.Customize labels, titles, colors, and styling
5. 5.Save high-DPI images for publication or reports