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reversa-highcharts-visualizer

Generates standalone HTML data visualizations with Highcharts.js from CSV, JSON, or Excel data.

Updated Aug 14, 2026
Search Tags:#html#data visualization#charts#javascript#dashboard#csv#highcharts
One-click install
npx skills add https://github.com/Ruggery/OCR_Cartorio --skill reversa-highcharts-visualizer-ruggery
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reversa-highcharts-visualizer
Source: https://github.com/Ruggery/OCR_Cartorio/tree/main/.agents/skills/reversa-highcharts-visualizer
Command: npx skills add https://github.com/Ruggery/OCR_Cartorio --skill reversa-highcharts-visualizer-ruggery

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, and includes scripts (resource) and references (resource) components.

What problem does it solve? Turning raw data from spreadsheets, CSV files, or pasted tables into polished, interactive charts normally requires manual JavaScript coding and chart library expertise. This Skill automates the entire pipeline: analyzing your data, picking the right chart type, and producing a single self-contained HTML file with an interactive Highcharts visualization. ## Core Features & Use Cases - Automatic chart type selection: Analyzes your data (temporal vs categorical, number of series, value ranges) and recommends the best chart from 40+ types including line, column, pie, heatmap, sankey, treemap, gauge, funnel, and stock charts. - Standalone HTML output: Generates a single self-contained .html file with pinned Highcharts 11.4.8, accessibility and exporting modules, responsive layout, rich tooltips, and optional dark mode. - Data parsing utilities: Python scripts parse CSV (with encoding and Brazilian number format detection), JSON, and Excel files, plus generate sample data for exploring chart types. - Use Case: Paste a quarterly sales table and receive a ready-to-open HTML dashboard with animated, responsive charts formatted with Brazilian locale (thousands separators, month names). ## Quick Start Ask the agent to create an interactive chart from your data, for example: create a Highcharts dashboard from the attached sales.csv showing monthly revenue trends.

Frequently Asked Questions about reversa-highcharts-visualizer

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

FAQPage Schema
How do I create an interactive chart from a CSV file with Highcharts?▼

Provide the CSV file and the skill parses it with scripts/parse_data.py, which auto-detects encoding, delimiters, and Brazilian number formats like 1.234,56. It then injects the parsed data directly into a standalone HTML file with the appropriate Highcharts chart type.

What chart types does Highcharts support for data visualization?▼

The skill covers 40+ chart types documented in references/CHART_CATALOG.md, including line, area, column, bar, pie, scatter, bubble, heatmap, treemap, sunburst, sankey, funnel, gauge, wordcloud, network graph, box plot, stock, maps, and gantt charts.

How do I choose the right chart type for my data?▼

Run scripts/analyze_data.py on your data file to get statistics and ranked chart suggestions based on whether data is temporal, categorical, or hierarchical. The skill also applies a decision table mapping goals like trends, comparison, or composition to recommended chart types.

Does Highcharts work offline without a CDN?▼

Yes. When run by the Reversa Docs team, Highcharts modules load from local assets/vendor/ files pinned via vendor-pins.yaml, so pages work via file:// without internet. CDN links at code.highcharts.com version 11.4.8 serve only as fallback.

Why is my Highcharts chart slow with large datasets?▼

Charts with over 10,000 points need the boost module with boostThreshold set around 5000, disabled animations, and disabled markers. The skill's error reference also recommends downsampling data through scripts/analyze_data.py for very large inputs.

Can I generate sample data to test a chart type?▼

Yes. Run scripts/sample_data.py with a --type flag such as line, pie, sankey, stock, or treemap to generate realistic sample datasets in Highcharts-ready JSON format, useful for exploring chart types before you have real data.

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