research-visualization
CommunityVisualize research data for publication.
Education & Research#data analysis#visualization#plotly#matplotlib#seaborn#publication#scientific figures
AuthorMekann2904
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill streamlines the creation of publication-quality scientific figures, from exploratory data analysis to final submission-ready visuals, addressing the complex requirements of academic journals.
Core Features & Use Cases
- Integrated Plotting: Combines Matplotlib, Seaborn, and Plotly for diverse visualization needs.
- Journal-Specific Formatting: Adapts figures to meet the strict width, resolution, and format requirements of journals like Nature, Science, and Cell.
- Advanced Features: Supports multi-panel layouts, statistical annotations, colorblind-safe palettes, and interactive web-based dashboards.
- Use Case: Generate a multi-panel figure with bar plots, line graphs, and scatter plots, formatted precisely for a Nature submission, including appropriate fonts and color schemes.
Quick Start
Use the research-visualization skill to create a publication-ready bar plot for your data.
Dependency Matrix
Required Modules
matplotlibseabornplotlynumpypandasscipy
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: research-visualization Download link: https://github.com/Mekann2904/mekann/archive/main.zip#research-visualization Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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