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scientific-visualization

Create publication-ready scientific plots with matplotlib, seaborn, and plotly.

2|Updated May 7, 2026
Search Tags:#data visualization#matplotlib#publication quality#plot generation#scientific plots
One-click install
npx skills add https://github.com/Teng-bio/codex-skills-hub --skill scientific-visualization-teng-bio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/Teng-bio/codex-skills-hub/tree/main/skills/global/scientific-visualization
Command: npx skills add https://github.com/Teng-bio/codex-skills-hub --skill scientific-visualization-teng-bio

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill simplifies the process of creating publication-quality scientific plots, helping researchers present their data clearly and effectively.

Core Features & Use Cases

  • Publication-Quality Plots: Generate line plots, scatter plots, heatmaps, and more with consistent styles and formats suitable for journals.
  • Automated Layouts: Create multi-panel figures with automated alignment and spacing.
  • Colorblind-Friendly: Use pre-configured palettes and colorblind-friendly settings to ensure accessibility.
  • Use Case: A researcher wants to create a line plot comparing different treatments in a biological experiment. This Skill can be used to automatically generate the plot with error bars, appropriate labels, and a publication-ready format.

Quick Start

Run the following command to generate a publication-quality line plot with error bars and labels:

python3 scripts/plot_generator.py data.csv -o my_line_plot.png

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-quality scientific plots for journal submissions?▼

To create publication-quality scientific plots, this Skill automates figure generation using matplotlib, seaborn, and plotly. It applies consistent styles, error bars, labels, and export settings to produce journal-ready figures directly from data.

Can I generate multi-panel figures with automated alignment in matplotlib?▼

Yes, you can generate multi-panel figures with automated alignment and spacing. The Skill uses matplotlib to handle layout configuration, ensuring properly aligned panels for complex scientific data presentation.

How do I make colorblind-friendly scientific plots in Python?▼

To make colorblind-friendly scientific plots, the Skill applies pre-configured palettes and accessibility settings. This ensures your visualizations remain readable and accessible without manual color mapping.

Do I need pandas and scipy to generate scientific plots from CSV data?▼

Yes, pandas and scipy are required dependencies to process data and generate figures. The Skill uses these libraries alongside matplotlib, seaborn, plotly, and numpy to parse data and calculate statistics for scientific plots.

What's the best way to add error bars to a line plot comparing biological treatments?▼

The best way to add error bars to biological treatment line plots is using this Skill's automated plot generator. It processes your CSV data and outputs figures with appropriate error bars, labels, and publication-ready formatting.

Does this Skill support interactive plots with plotly or only static matplotlib figures?▼

The Skill supports both static and interactive scientific plots by using plotly alongside matplotlib and seaborn. It applies publication-quality styles and export settings across all supported visualization libraries.

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