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hiroshi75
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data-visualization

Generate publication-quality charts with Matplotlib, Seaborn, and Plotly.

Updated Mar 13, 2026
Search Tags:#data visualization#python#data analysis#plotly#matplotlib#charting#seaborn
One-click install
npx skills add https://github.com/hiroshi75/agentlattice --skill data-visualization-hiroshi75
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-visualization
Source: https://github.com/hiroshi75/agentlattice/tree/main/templates/skills/data/data-visualization
Command: npx skills add https://github.com/hiroshi75/agentlattice --skill data-visualization-hiroshi75

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps users create clear, informative, and accessible data visualizations using Python, addressing the challenge of choosing the right chart type and applying effective design principles.

Core Features & Use Cases

  • Chart Selection Guidance: Provides a comprehensive guide to selecting the most appropriate chart type based on the data and the message to be conveyed.
  • Python Visualization Code: Offers reusable code patterns for creating various charts with popular libraries like Matplotlib, Seaborn, and Plotly.
  • Design Principles: Outlines best practices for color usage, typography, layout, and accuracy to ensure visualizations are effective and professional.
  • Accessibility: Emphasizes considerations for color blindness, contrast, and text readability to make visualizations usable by a wider audience.
  • Use Case: A data analyst needs to present quarterly sales trends. This Skill can guide them to use a line chart, provide the Python code to generate it with proper labels, and ensure it's accessible.

Quick Start

Use the data-visualization skill to create a line chart showing sales trends over time from the provided dataframe.

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 in Python?▼

Choosing the right chart type for data visualization involves matching your data structure and message to the appropriate format. This Skill provides comprehensive guidance on selecting charts based on the data and the specific message you need to convey.

How do I create accessible data visualizations with color blindness considerations?▼

Creating accessible data visualizations requires careful color selection, contrast adjustment, and text readability. This Skill emphasizes design principles and accessibility standards to ensure your charts are usable by a wider audience, including those with color blindness.

Can I generate publication-quality figures using Matplotlib and Seaborn?▼

You can generate publication-quality figures using Matplotlib and Seaborn by applying effective design principles. This Skill offers reusable Python code patterns and outlines best practices for color usage, typography, and layout to ensure professional results.

Do I need Python and Pandas installed to use Plotly for charting?▼

Yes, you need Python 3 installed along with the matplotlib, seaborn, pandas, and plotly libraries to use this charting functionality. These dependencies are required to execute the data visualization code patterns provided by the Skill.

What is the best way to visualize quarterly sales trends over time?▼

The best way to visualize quarterly sales trends is by using a line chart to show progression over time. This Skill guides you to the appropriate chart format and provides the Python code to generate it with proper labels and accessible design.

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