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scientific-visualization

Generate publication-ready scientific figures with matplotlib, seaborn, and plotly.

13|3|Updated Jun 10, 2026
Search Tags:#plotly#matplotlib#seaborn#publication#data plotting#scientific visualization
One-click install
npx skills add https://github.com/tassiovale/claude-code-kit --skill scientific-visualization-tassiovale
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/tassiovale/claude-code-kit/tree/main/skills/scientific-visualization
Command: npx skills add https://github.com/tassiovale/claude-code-kit --skill scientific-visualization-tassiovale

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, seaborn, plotly, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the creation of publication-ready scientific figures, saving time and ensuring compliance with journal standards.

Core Features & Use Cases

  • Publication-Ready Styles: Apply predefined styles for journals like Nature, Science, and Cell.
  • Automated Formatting: Automate figure formatting, including size, color, and typography.
  • Data Visualization: Use matplotlib, seaborn, and plotly to visualize data and generate publication-quality plots.
  • Use Case: Suppose you need to create a multi-panel figure for a journal submission. This Skill can automatically format the plot, label axes, and export the figure in the correct resolution and format.

Quick Start

Use the scientific-visualization skill to create a publication-ready line plot with error bars from the data in 'data.csv'.

Frequently Asked Questions about scientific-visualization

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

FAQPage Schema
How do I create publication-ready scientific figures for journal submissions?▼

You can create publication-ready scientific figures by applying predefined styles for journals like Nature, Science, and Cell. This Skill automates plot formatting, axis labeling, and export resolution using matplotlib, seaborn, and plotly.

What is the best way to automate matplotlib and seaborn plot formatting for scientific presentations?▼

The best way to automate plot formatting is by applying predefined publication styles that automatically adjust figure size, color palettes, and typography for scientific presentations using this Skill's built-in templates.

Do I need to install matplotlib, seaborn, and plotly to generate publication-quality plots?▼

Yes, you need matplotlib, seaborn, and plotly installed. These frameworks are required dependencies for this Skill to generate publication-quality plots, create multi-panel figures, and export visualizations.

Can I use plotly to generate multi-panel figures and export them in specific resolution formats?▼

Yes, you can use plotly alongside matplotlib and seaborn to generate multi-panel figures. The Skill automates the formatting process and exports the final scientific figures in the correct resolution and file format required for journal submissions.

Does this approach support predefined scientific visualization styles for specific journals like Cell and Nature?▼

Yes, this approach supports predefined scientific visualization styles. It includes built-in templates specifically designed to meet the strict formatting, size, and typography standards of journals like Cell, Nature, and Science.

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