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data-visualization

Generate Python code for Matplotlib and Plotly data visualizations.

1|Updated Jan 6, 2026
Search Tags:#data visualization#data storytelling#dashboards#charts#plotly#matplotlib
One-click install
npx skills add https://github.com/hyukudan/ai-skills --skill data-visualization-hyukudan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-visualization
Source: https://github.com/hyukudan/ai-skills/tree/main/examples/skills/data-visualization
Command: npx skills add https://github.com/hyukudan/ai-skills --skill data-visualization-hyukudan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps users create clear, informative, and impactful data visualizations, transforming raw data into understandable insights and compelling narratives.

Core Features & Use Cases

  • Chart Selection Guidance: Provides a matrix to choose the right chart type based on data and purpose.
  • Code Generation: Offers code snippets for popular libraries like Matplotlib and Plotly for various chart types (line, bar, scatter, etc.).
  • Design Principles: Covers best practices for color, typography, and layout to enhance visual communication.
  • Storytelling Framework: Guides users on structuring data narratives and using annotations effectively.
  • Use Case: A marketing analyst needs to present quarterly sales trends. This Skill can help them select a line chart, generate the Python code using Plotly, and provide tips on annotating key performance indicators.

Quick Start

Use the data-visualization skill to generate a bar chart for comparing product sales using matplotlib.

Frequently Asked Questions about data-visualization

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?▼

Choosing the right chart type depends on your data structure and visualization purpose. This Skill provides a chart selection matrix to help you pick the correct visualization based on whether your goal is exploration, presentation, or dashboarding.

How do I create interactive dashboards using Python libraries like Plotly?▼

You can create interactive dashboards using Plotly by leveraging this Skill's code generation features. It provides customizable Python code snippets and design principles to help you build interactive visualizations tailored to your specific dashboarding goals.

What's the best way to tell a compelling data story with annotations?▼

To tell a compelling data story, use a structured narrative framework and effective annotations. This Skill guides you on structuring data narratives and applying design principles to highlight key performance indicators and insights visually.

Does this data visualization guidance work with both Matplotlib and Plotly?▼

Yes, this data visualization guidance supports both Matplotlib and Plotly. It offers code snippets for various chart types across both Python libraries, allowing you to customize variables based on your specific visualization goals.

How do I generate Python code for a bar chart comparing product sales?▼

To generate Python code for a bar chart, specify your visualization goal and library. This Skill can produce code snippets using Matplotlib or Plotly to compare product sales, applying best practices for color, typography, and layout.

What design principles should I follow for effective data visualization?▼

Effective data visualization requires following design principles for color, typography, and layout. This Skill covers best practices to enhance visual communication, ensuring your charts are clear, informative, and impactful for your audience.

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