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figures-python

Generate publication-quality PNG and SVG plots with consistent color palettes.

3.0k|205|Updated Mar 4, 2026
Search Tags:#visualization#matplotlib#seaborn#data-visualization#publication-ready#research-figures
One-click install
npx skills add https://github.com/Norman-bury/research-writing-skill --skill figures-python
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: figures-python
Source: https://github.com/Norman-bury/research-writing-skill/tree/main/skills/figures-python
Command: npx skills add https://github.com/Norman-bury/research-writing-skill --skill figures-python

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researchers spend valuable time formatting figures for manuscripts; this skill streamlines the creation of publication-quality visuals and consistent color schemes.

Core Features & Use Cases

  • Enforce top-journal color schemes to ensure visuals match high-profile publication aesthetics.
  • Output formats and DPI: export PNG and SVG at high resolution (default 450 DPI) for figures in manuscripts, slides, and reports.
  • Font handling and localization: ensure proper font rendering (including Chinese fonts) across platforms and languages.
  • Directory organization: save outputs to a structured figures/ directory, ready for integration into your manuscript.

Quick Start

Generate a publication-ready figure from your dataset and save it in both PNG and SVG formats under the figures/ directory.

Frequently Asked Questions about figures-python

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

FAQPage Schema
How do I generate publication-ready figures for a research manuscript in Python?▼

To generate publication-ready figures, this skill applies top-journal color schemes, high DPI resolution, and proper font handling to your data. It outputs PNG and SVG formats directly to a structured figures/ directory for easy manuscript integration.

Can I use matplotlib and seaborn to create journal-ready data visualizations?▼

Yes, you can use matplotlib and seaborn to create journal-ready data visualizations. This skill enforces consistent color palettes and high-resolution formatting suitable for scholarly articles directly from these libraries.

How do I export high-resolution PNG and SVG plots at 450 DPI for academic papers?▼

Exporting high-resolution PNG and SVG plots at 450 DPI is handled automatically by this skill. It enforces default 450 DPI output and saves both formats to a figures/ directory for manuscript and presentation use.

Does this data-visualization tool handle Chinese font rendering across different platforms?▼

Yes, this data-visualization tool handles Chinese font rendering across platforms. It includes font handling and localization features to ensure proper rendering across different languages and operating systems.

What is the best way to apply consistent color schemes to research figures for scholarly articles?▼

The best way to apply consistent color schemes to research figures is using this skill, which enforces top-journal color palettes. This ensures your visuals match high-profile publication aesthetics automatically.

Do I need any external dependencies to create publication-quality plots with this skill?▼

No external dependencies are required to create publication-quality plots with this skill. It operates independently to enforce styling, high DPI export, and directory organization for your research figures.

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