Data Visualization

Trust Score 83/100

Practical guidance and Python code patterns (matplotlib, seaborn, plotly) for choosing chart types and producing accessible, publication-quality data visualizat

triggers:chartvisualizationplotmatplotlibseabornplotlyheatmapsmall multiples

GitHub SKILL.md

What it does

Provides a compact, practical guide to selecting appropriate chart types and implementing them in Python. Includes code patterns, styling best-practices, accessibility checks, and templates for line, bar, histogram, heatmap, small-multiples, and interactive Plotly charts. Useful for analysts and engineers who need reproducible, publication-ready visualizations.

When to use it

Use this skill when you need to: pick the correct chart for a dataset (time series, distribution, correlation, geographic), produce clean and accessible figures for reports or presentations, convert exploratory plots into polished visuals, or add interactive Plotly exports for sharing.

What's included

Scripts: none bundled, but the SKILL.md contains ready-to-use Python code snippets for Matplotlib, Seaborn and Plotly.
References: design & accessibility checklists, colorblind-friendly palettes, typography and layout rules.
Instructions: chart selection heuristics, number formatting helpers, interactive export templates, and an accessibility checklist.

Compatible agents

Works well with Claude Code, Copilot-like coding assistants, and any agent that can run or suggest Python snippets for visualization and reporting.

Audit Summary

Pure reference/knowledge skill with no scripts — provides comprehensive data visualization guidance including chart selection, Python code patterns (matplotlib/seaborn/plotly), accessibility checklists, design principles, Chinese font configuration, and insight card templates. Well-organized and immediately useful for any agent working with data. No security concerns whatsoever.

Watch Out

Purely a reference skill — no executable scripts or automation, just code patterns for an agent to use
Chinese font section is macOS-specific, Linux users need different font paths

Notes

Solid knowledge-skill. Architecture score reflects lack of scripts/references separation, which is expected for a reference-only skill. The content quality is high — covers chart selection, anti-patterns, accessibility, and practical code templates comprehensively.

Information

Repository: didi-skills
Stars: 52

Trust Score

Overall83

Security95

Code Quality82

Architecture55

Usefulness72

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