beautiful-data-viz
CommunityPublication-ready visuals with clean, readable charts.
Data & Analytics#typography#visualization#matplotlib#seaborn#data-visualization#color-palette#publication-quality
Authorfmschulz
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Creating publication-quality charts in Python/Jupyter can be time-consuming and error-prone; this Skill standardizes typography, layout, and color choices to ensure readability and visual impact.
Core Features & Use Cases
- Automated styling: apply the shared style helper and finalize axes for consistent appearance.
- Palette guidance: access curated palettes and accessibility checks for colorblind-safe visuals.
- Reusable recipes: reference examples in examples/recipes.md for common plots (line charts, ranked dot plots, heatmaps) and integrate into reports.
- Use Case: generate a publication-ready figure for a manuscript figure with tight layout and accessible labels.
Quick Start
Set the plotting style to notebook with a light background and generate a publication-ready line chart from your data.
Dependency Matrix
Required Modules
None requiredComponents
assetsreferences
💻 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: beautiful-data-viz Download link: https://github.com/fmschulz/omics-skills/archive/main.zip#beautiful-data-viz Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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