📊 PyThesisPlot

Scientific Plotting Skill for Claude Code — Transform raw data into publication-ready figures with Nature/Science quality standards.

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🎯 What is PyThesisPlot?

PyThesisPlot is a Claude Code Skill that teaches AI assistants how to create publication-quality scientific figures from raw data. It provides:

• 📊 Intelligent Workflow: Data → Analysis → Recommendations → Confirmation → Figures
• 🎨 Journal-Ready Output: 300 DPI, Nature/Science style compliance
• 🔬 Multi-Domain Support: Biology, Psychology, Economics, Chemistry
• 📁 Organized Output: Timestamped directories with reproducible code

Trigger: When you upload data files (CSV/Excel/TXT) and ask for plots, charts, or figures.

Supported Platforms: Claude Code · OpenCode · OpenClaw · Kimi CLI · Trae · Cursor

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📦 Installation

For Humans

Copy and paste this to your AI assistant:

Install PyThesisPlot skill for me:
https://github.com/stephenlzc/pythesis-plot

Or if you enjoy YAML-induced headaches, read the Installation Guide. But seriously, let the agent handle it. Humans copy-paste paths wrong.

For LLM Agents

Claude Code:

git clone https://github.com/stephenlzc/pythesis-plot.git ~/.claude/skills/pythesis-plot
pip install pandas matplotlib seaborn openpyxl numpy scipy

OpenCode / OpenClaw:

git clone https://github.com/stephenlzc/pythesis-plot.git ~/.opencode/skills/pythesis-plot
pip install pandas matplotlib seaborn openpyxl numpy scipy

Kimi CLI:

git clone https://github.com/stephenlzc/pythesis-plot.git ~/.kimi/skills/pythesis-plot
pip install pandas matplotlib seaborn openpyxl numpy scipy

Trae:

git clone https://github.com/stephenlzc/pythesis-plot.git ~/.trae/skills/pythesis-plot
pip install pandas matplotlib seaborn openpyxl numpy scipy

Full instructions: docs/installation.md

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🚀 Skip This README

We're past the era of manual plotting. Just paste this into your agent:

I have some data and need publication-ready figures for my thesis. 
Use PyThesisPlot skill to help me:
https://github.com/stephenlzc/pythesis-plot

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🚀 Quick Start

Once installed, simply upload your data and ask:

"Help me create some charts for my thesis"

"Plot this data for my scientific paper"

"Generate publication-ready figures from this Excel file"

The skill will automatically:

1. Analyze your data structure and types
2. Recommend appropriate chart types
3. Wait for your confirmation on chart selection
4. Generate 300 DPI PNG figures + reproducible Python code

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📋 Skill Structure

pythesis-plot/
├── SKILL.md                          # Skill definition (trigger conditions)
├── README.md                         # This file
├── README.zh-CN.md                   # Chinese documentation
├── scripts/
│   ├── workflow.py                   # Main orchestrator
│   ├── data_analyzer.py              # Data analysis engine
│   └── plot_generator.py             # Figure generation engine
├── references/
│   ├── workflow_guide.md             # Workflow documentation
│   ├── chart_types.md                # Chart selection guide
│   ├── style_guide.md                # Visual standards
│   └── examples.md                   # Code examples
└── assets/themes/
    ├── academic.mplstyle             # Academic journal style
    ├── nature.mplstyle               # Nature journal style
    └── presentation.mplstyle         # Presentation style

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🎨 Supported Chart Types

Chart Type	Best For	Example Use Case
📈 Line Plot	Time series, Trends	Gene expression over time
📊 Bar Chart	Group comparisons	Treatment vs Control
🎯 Box Plot	Distribution, Outliers	qPCR Ct values
⚡ Scatter + Regression	Correlations	Dose-response relationships
🔥 Heatmap	Correlation matrices	Multi-gene expression
📋 Dashboard	Multi-panel figures	Complete study overview

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💡 Example Use Cases

Example 1: Biomedical Research (qPCR Data)

User: "I have qPCR data for my PCOS study. Help me create figures."

AI: Analyzing Mouse_PCOS_BRAC1_RawData_108.xlsx...
    Detected: 108 samples, 3 groups, gene expression data
    
    Recommended Charts:
    1. Body weight comparison (bar chart)
    2. BRAC1 expression levels (log scale bar chart)
    3. qPCR Ct distributions (box plot)
    4. Comprehensive 2×2 dashboard

User: "Generate all of them"

AI: ✅ Generated 4 publication-ready figures in output/20250312-143052-PCOS/

Example 2: Psychology RCT Study

User: "Plot my mental health intervention results"

AI: Analyzing Adolescent_Mental_Health_Intervention_1200.xlsx...
    Detected: 1200 participants, 4-arm RCT, pre/post measurements
    
    Recommended Charts:
    1. CONSORT-style study flow
    2. SDQ pre/post comparison
    3. Responder analysis (stacked bar)
    4. Effect size forest plot

User: "Generate schemes 1, 2, and 3"

AI: ✅ Generated 3 figures with statistical annotations

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⚙️ How It Works

1. Skill Trigger

The skill activates when the YAML description in SKILL.md matches your request:

---
name: pythesis-plot
description: Python scientific plotting tool... 
  Triggers when users upload data files (txt/md/excel/csv) 
  and mention "help me plot", "create chart", "data visualization", 
  "thesis figure", "scientific plotting"...
---

2. Workflow Stages

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│ Data Upload │────▶│  Analysis   │────▶│Recommendations│
└─────────────┘     └─────────────┘     └──────┬──────┘
                                                │
                                                ▼
┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Delivery  │◀────│ Generation  │◀────│Confirmation │
│  (PNG+Code) │     │             │     │  (Required) │
└─────────────┘     └─────────────┘     └─────────────┘

3. Output Organization

All outputs saved to timestamped directory:

output/
└── 20250312-143052-your-data/
    ├── 20250312-143052-your-data.csv    # Original data (renamed)
    ├── analysis_report.md               # Data analysis report
    ├── plot_config.json                 # Chart configuration
    ├── 20250312-143052_plot.py          # Reproducible Python code
    └── *.png                            # 300 DPI figures

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📖 Documentation

• Workflow Guide — Complete workflow walkthrough
• Chart Types — When to use which chart
• Style Guide — Color schemes and visual standards
• Examples — Code examples and tutorials

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🔧 Dependencies

pip install pandas matplotlib seaborn openpyxl numpy scipy

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🤝 Contributing

Contributions welcome! This skill follows the standard SKILL.md format:

1. Fork this repository
2. Modify SKILL.md or add new chart types
3. Test with sample data
4. Submit a Pull Request

Skill Format

---
name: pythesis-plot
description: | 
  Clear trigger conditions for when AI should load this skill.
  List specific phrases and contexts.
---

# Skill Body

## Quick Start
Brief instructions...

## Features
- Feature 1
- Feature 2

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🌐 Languages

• English: README.md (this file)
• 中文: README.zh-CN.md

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📄 License

MIT License — see LICENSE for details.

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🙏 Acknowledgments

• 🎨 Color palettes from Nature and Science style guides
• 📊 Visualization practices from Seaborn
• 🎓 Academic standards from Matplotlib

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Made with ❤️ for Researchers

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