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nature-figure

Create publication-quality scientific figures with Python matplotlib or R ggplot2.

34.2k|1.9k|Updated Apr 24, 2026
Search Tags:#Python#R#scientific figures#publication standards#multi-panel layout#SVG export
One-click install
npx skills add https://github.com/Yuan1z0825/nature-skills --skill nature-figure
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: nature-figure
Source: https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-figure
Command: npx skills add https://github.com/Yuan1z0825/nature-skills --skill nature-figure

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the creation of high-quality, publication-ready scientific figures that serve as clear visual arguments, ensuring the figures meet rigorous journal standards.

Core Features & Use Cases

  • Figure Construction: Guides users through establishing scientific claims, evidence hierarchy, and visual layout before coding.
  • Style Enforcement: Applies Nature-style typography, color palettes, and layout conventions to ensure aesthetic consistency.
  • Backend Compatibility: Supports both Python/matplotlib and R/ggplot2 workflows, enforcing exclusive use for rendering, exporting, and QA.
  • Format Support: Produces editable SVG and high-resolution raster images (PNG, TIFF) adhering to journal requirements.
  • Use Case: Prepare multi-panel figures for research publications, conference presentations, or detailed technical reports, with automatic style and format delivery.

Quick Start

State the scientific question you want to visualize and choose either Python or R to generate the figure accordingly.

Frequently Asked Questions about nature-figure

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create publication-ready scientific figures that meet Nature journal standards?▼

This Skill produces publication-ready scientific figures aligned with Nature standards by enforcing specific typography, color palettes, and multi-panel layout conventions through Python matplotlib or R ggplot2 workflows.

Can I use Python or R to generate multi-panel scientific figures with SVG export?▼

Yes, you can generate multi-panel scientific figures with SVG export by exclusively using Python matplotlib or R ggplot2 for all rendering and output processes, ensuring the final visual arguments meet journal requirements.

What is the best way to assemble schematic and imaging figures for research publications?▼

The best way to assemble schematic and imaging figures for research publications is to establish a visual layout and evidence hierarchy first, then apply consistent Nature-style aesthetics and export to high-resolution TIFF or editable SVG formats.

Does this approach support exporting high-resolution raster images like PNG and TIFF?▼

Yes, the workflow supports exporting high-resolution raster images like PNG and TIFF, alongside editable SVG formats, to fulfill the rigorous resolution and file format requirements of scientific journals.

Why do I need to choose between matplotlib and ggplot2 for scientific figure rendering?▼

You must choose between matplotlib and ggplot2 because the workflow requires the exclusive use of either Python or R for all rendering, exporting, and quality assurance processes to maintain consistent style enforcement.

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