Can I customize the colors and styles?

Absolutely. The skill includes templates for custom color palettes and provides boilerplate code for modifying every aesthetic element of the plots.

Which Python libraries are required?

You will need to have matplotlib, seaborn, pandas, and numpy installed in your local Python environment to use these plotting features.

Does this skill require a specific LLM provider?

No, this skill is provider-agnostic. Because it executes Python code in your local environment, it works perfectly with Claude, GPT-4, Gemini, DeepSeek, and others.

Can I export high-resolution images for papers?

Yes, the skill is pre-configured to save images at 300 DPI in formats like PNG, suitable for professional publications and reports.

Universal Data Visualization

Name: Universal Data Visualization
Author: Microck

byMicrock

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数据科学与机器学习

Generates publication-quality scientific plots and visualizations using Matplotlib and Seaborn across all LLM providers.

关于

This skill provides a comprehensive toolkit for generating professional-grade data visualizations directly within your local environment. It leverages the power of Matplotlib and Seaborn to create a vast range of charts, from basic line plots to complex multi-panel figures and domain-specific visualizations like volcano plots or UMAP projections. Designed to be provider-agnostic, it allows users to produce high-resolution, publication-ready figures for research papers, business reports, and exploratory data analysis (EDA) regardless of the AI model they are using.

主要功能

High-resolution (300 DPI) publication-quality figure generation
Universal compatibility with Claude, GPT-4, Gemini, and local models
Extensive library of plot types including heatmaps, violin plots, and density charts
81 GitHub stars
Customizable aesthetics including color palettes, font scaling, and styling
Complex multi-panel layout support using GridSpec

使用场景

Creating figures for scientific publications and academic research papers
Automating quality control (QC) reporting and exploratory data analysis
Visualizing complex genomic data such as gene expression and clustering results

关于

主要功能

High-resolution (300 DPI) publication-quality figure generation
Universal compatibility with Claude, GPT-4, Gemini, and local models
Extensive library of plot types including heatmaps, violin plots, and density charts
81 GitHub stars
Customizable aesthetics including color palettes, font scaling, and styling
Complex multi-panel layout support using GridSpec

使用场景

Creating figures for scientific publications and academic research papers
Automating quality control (QC) reporting and exploratory data analysis
Visualizing complex genomic data such as gene expression and clustering results