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data-create-viz

Generate publication-quality static and interactive charts from datasets using Python libraries.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Creates professional-quality data visualizations with Python using the Evolution theme (dark background, accent #00FFA7, Inter font). Use when you need to transform query results or a DataFrame into a chart, select the correct chart type for a trend or comparison, generate a plot for a report or presentation, or need an interactive chart with hover and zoom. Sources: Stripe, Omie, Licensing, Evo CRM, or pasted/CSV data.

Core Features & Use Cases

  • Generate publication-quality plots from datasets with consistent Evolution styling.
  • Recommend appropriate chart types for trends, comparisons, distributions, and relationships.
  • Produce both static (matplotlib/seaborn) and interactive (Plotly) visuals for dashboards and reports.
  • Example: convert a dataset of monthly sales into a line chart showing trend.

Quick Start

Create a line chart from a DataFrame named df with date and value columns to visualize a trend.

Frequently Asked Questions about data-create-viz

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

FAQPage Schema
How do I create Python data visualizations from a CSV or DataFrame?▼

You can generate publication-quality data visualizations from CSV files, DataFrames, or raw query results using Python libraries like matplotlib, seaborn, and Plotly with Evolution styling applied automatically.

What is the best way to choose a chart type for trend analysis or comparisons?▼

Chart type recommendations are provided based on your analytical task, evaluating whether your data represents trends, comparisons, distributions, or relationships to select the most appropriate visual format.

Can I generate interactive charts with hover and zoom using Plotly?▼

Yes, interactive visuals with hover and zoom capabilities are supported through Plotly, alongside static charts via matplotlib and seaborn, making them suitable for both dashboards and static reports.

Does this data visualization tool work with Stripe, Omie, or Evo CRM data sources?▼

Yes, data from Stripe, Omie, Licensing, and Evo CRM sources is supported, as well as pasted data or CSV files, allowing you to visualize business analytics directly from these platforms.

Do I need to manually configure dark backgrounds and accent colors for my plots?▼

No, the Evolution theme is applied automatically, styling your plots with a dark background, accent color #00FFA7, and Inter font to ensure consistent publication-quality visual output without manual configuration.

Why use this approach instead of standard matplotlib or seaborn defaults?▼

Standard library defaults lack consistent branding; this approach applies the Evolution theme automatically to your plots, ensuring professional, presentation-ready visuals without manual styling overhead for reporting tasks.

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