Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
The scientific visualization skill is designed to aid researchers and scientists in transforming complex data into visually appealing and publication-ready figures. By utilizing popular libraries such as matplotlib, seaborn, and plotly, this skill addresses the common challenge of creating accurate and effective visual representations of scientific data. It ensures that figures not only meet publication standards but also enhance the clarity and accessibility of the information presented, which is crucial for effective communication in scientific literature.
The skill supports matplotlib, seaborn, and plotly for creating visualizations.
Yes, you can export figures in PDF, EPS, and TIFF formats.
Yes, the skill includes options for colorblind-safe palettes.
Yes, you can apply journal-specific styles using provided style files.
Raster images should be 300-600 DPI, while line art should be 600-1200 DPI or in vector format.
Quick Setup:
.claude/skills/Repository
davila7/claude-code-templates