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reversa-highcharts-visualizer

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

Updated Jun 26, 2026
Search Tags:#html#data visualization#charts#javascript#dashboard#csv#highcharts
One-click install
npx skills add https://github.com/RLuf/fzagent --skill reversa-highcharts-visualizer-rluf
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reversa-highcharts-visualizer
Source: https://github.com/RLuf/fzagent/tree/main/.agents/skills/reversa-highcharts-visualizer
Command: npx skills add https://github.com/RLuf/fzagent --skill reversa-highcharts-visualizer-rluf

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 JSON into polished, interactive charts normally requires manual JavaScript coding and library configuration. This Skill automates the entire pipeline: it analyzes your data, picks the right chart type, and outputs a single self-contained HTML file with an interactive Highcharts visualization. ## Core Features & Use Cases - 40+ Chart Types: Line, area, column, bar, pie, donut, scatter, bubble, heatmap, treemap, sunburst, sankey, funnel, gauge, stock (candlestick/OHLC), maps, gantt, wordcloud, network graph, and more, with a decision table mapping data goals to chart types. - Data Parsing & Analysis Scripts: Python utilities parse CSV/JSON/Excel (handling Brazilian number formats and encodings), compute descriptive statistics, and suggest the best chart type based on data shape. - Standalone HTML Output: Every chart is delivered as a single self-contained .html file with pinned Highcharts 11.4.8, accessibility and exporting modules, responsive layout, dark mode themes, and Portuguese localization. - Use Case: Paste a CSV of monthly sales by region and ask for a dashboard; the Skill analyzes the data, recommends a stacked column plus line combo, and writes a ready-to-open HTML file with formatted tooltips and export buttons. ## Quick Start Create an interactive bar chart from the attached sales-data.csv file and save it as a standalone HTML page.

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 and delimiter, converts Brazilian number formats, and outputs Highcharts-ready JSON. The data is then injected into a standalone HTML file with the chosen chart type.

What chart types does Highcharts support for data visualization?▼

This Skill covers over 40 types including line, area, column, bar, pie, scatter, bubble, heatmap, treemap, sunburst, sankey, funnel, gauge, candlestick stock charts, maps, and gantt. The references/CHART_CATALOG.md file documents when to use each type with code examples.

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

Run scripts/analyze_data.py on your data file to get descriptive statistics and ranked chart suggestions based on whether data is temporal, categorical, or relational. The SKILL.md decision table also maps goals like trend, comparison, or composition to recommended types.

Does the generated Highcharts HTML work offline without internet?▼

Yes, when run by the Reversa Docs team the HTML loads Highcharts from local assets/vendor/ files pinned via vendor-pins.yaml, so it works over file:// without internet. CDN links at code.highcharts.com are only a fallback for standalone use.

Why is my Highcharts chart slow with large datasets?▼

Charts with over 10,000 points need the boost module (modules/boost.js) with boostThreshold set around 5000, plus disabled animations and markers. The Skill's error reference also recommends downsampling data via the analysis script for very large inputs.

Can Highcharts handle Excel files with multiple sheets?▼

Yes, scripts/parse_data.py reads .xlsx and .xls files using openpyxl and accepts a --sheet parameter to select a specific tab. Without the parameter it parses the active sheet and reports all available sheet names in the metadata.

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