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mikeandrusyak
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dataviz

Generate publication-ready charts and runnable code across Python, R, and JavaScript.

Updated Apr 18, 2026
Search Tags:#dashboards#charts#matplotlib#seaborn#d3#altair#datavisualization
One-click install
npx skills add https://github.com/mikeandrusyak/dataviz-skill --skill dataviz-mikeandrusyak
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dataviz
Source: https://github.com/mikeandrusyak/dataviz-skill/tree/main
Command: npx skills add https://github.com/mikeandrusyak/dataviz-skill --skill dataviz-mikeandrusyak

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Transform raw data into effective, publication-ready visualizations that communicate findings clearly and confidently.

Core Features & Use Cases

  • Automatic chart selection based on data relationships (comparison, distribution, correlation, time, geography, etc.).
  • Multi-library support across Python (seaborn, matplotlib, altair), R (ggplot2), and JavaScript (D3.js, Vega-Lite, Plotly, Bokeh) with inline SVG/HTML artifacts.
  • Design and accessibility guidance (Gestalt principles, color palettes, colorblind-friendly schemes) and storytelling for analysis and reporting.
  • Code generation and explanation across languages, plus evaluation notes and narrative help for final deliverables.
  • Use cases include creating charts, dashboards, and visual explorations from pasted data, real datasets, or conversations.

Quick Start

Provide a dataset or describe the visualization goal and I will generate a chart, runnable code, and an inline artifact.

Frequently Asked Questions about dataviz

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

FAQPage Schema
How do I choose the right chart type for my data visualization?▼

Data visualization chart selection matches chart types to data relationships like comparison, distribution, correlation, time, or geography. The skill analyzes your dataset to automatically select optimal chart types and generate ready-to-run code across Python, R, and JavaScript libraries.

Can I generate interactive dashboards using Python and JavaScript libraries?▼

You can build interactive dashboards using Python (altair, plotly, bokeh) and JavaScript (D3.js, Vega-Lite). The skill generates runnable code and inline HTML artifacts suited for interactive explorations and dashboard deployment.

What's the best way to create publication-ready charts with matplotlib and seaborn?▼

Publication-ready charts with matplotlib and seaborn apply Gestalt principles and colorblind-friendly palettes. The skill generates styled code templates, inline SVG artifacts, and narrative documentation for final reporting deliverables.

Does this data visualization approach support both Python and R ecosystems?▼

Data visualization supports Python (seaborn, matplotlib, altair) and R (ggplot2) ecosystems. The skill generates code templates, inline artifacts, and explanation documentation across these languages for charts and dashboards.

How do I make accessible data visualizations with colorblind-friendly schemes?▼

Accessible data visualizations use colorblind-friendly schemes and Gestalt design principles. The skill applies accessibility considerations to generated charts, providing appropriate color palettes and design guidance across all supported libraries.

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