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data-create-viz

Converts tabular data and SQL-like query results into Python plots with Evolution Dark styling and optional Plotly interactivity.

520|175|Updated Apr 8, 2026
Search Tags:#data visualization#charts#python#pandas#plotly#seaborn#evolution theme
One-click install
npx skills add https://github.com/evolution-foundation/evo-nexus --skill data-create-viz-evolution-foundation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-create-viz
Source: https://github.com/evolution-foundation/evo-nexus/tree/main/.claude/skills/data-create-viz
Command: npx skills add https://github.com/evolution-foundation/evo-nexus --skill data-create-viz-evolution-foundation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the friction of manually building professional-looking charts by converting query results or tabular data into publication-ready visualizations.

Core Features & Use Cases

  • Data-to-chart transformation: Builds clear plots from a pandas DataFrame, after parsing and cleaning user-provided results or files.
  • Smart chart selection: Recommends the appropriate chart type based on the relationship between fields (trend, comparison, composition, distribution, correlation, ranking, geography, flow, and heatmaps).
  • Evolution Dark styling: Applies a consistent dark theme using Evo colors (including #00FFA7 accent) suitable for internal reports and dashboards.
  • Interactive output option: Supports interactivity (hover/zoom) via Plotly when requested.

Quick Start

Run /data-create-viz with your data source, specify the chart type you want (or ask for a recommendation), and include any extra presentation instructions for a ready-to-use professional chart.

Frequently Asked Questions about data-create-viz

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

FAQPage Schema
How do I turn pandas DataFrame query results into presentation-ready charts?▼

This Skill creates data visualizations by converting query results or tabular data into Python plots, automatically preparing the pandas DataFrame and applying Evolution Dark styling for professional reporting.

What is the best way to choose a chart type for my business dataset?▼

Smart chart selection analyzes the relationships between fields in your business dataset to recommend the appropriate chart type across trend, comparison, composition, distribution, correlation, ranking, geographic, flow, and heatmap visualizations.

Can I use Plotly for interactive data visualizations with pandas data?▼

Yes, Plotly interactivity is supported for data visualizations when requested, enabling hover and zoom functionality alongside the standard Evolution Dark styling applied to your pandas data.

Do I need to clean tabular data before generating Python plots?▼

Extensive manual cleaning is unnecessary; the Skill parses and cleans user-provided pasted or tabular data during the pandas DataFrame preparation step before generating the final Python plots.

Does the Evolution Dark styling work for internal dashboards and reports?▼

Yes, Evolution Dark styling applies a consistent dark theme using Evo colors, including the #00FFA7 accent, making the resulting visualizations specifically suitable for internal reports and dashboards.

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