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LeonChaoX
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plotly

Generate interactive Plotly visualizations in Python with hover, pan/zoom, and HTML export.

783|65|Updated Feb 27, 2026
Search Tags:#data visualization#plotly#interactive visualization#html export#plotly express#graph objects#scientific plotting
One-click install
npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill plotly-leonchaox
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: plotly
Source: https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/11-%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90%E4%B8%8E%E7%BB%9F%E8%AE%A1%E5%BB%BA%E6%A8%A1/plotly
Command: npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill plotly-leonchaox

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you turn analysis results into clear, interactive visualizations so you can explore patterns and present findings without building charts from scratch.

Core Features & Use Cases

  • Interactive, publication-quality visualizations: Create hoverable, zoomable charts suitable for dashboards, exploratory analysis, and stakeholder presentations.
  • Multiple APIs for different needs: Use Plotly Express for fast, tidy-data-driven charts and graph_objects for fine-grained control when you need custom traces, annotations, and advanced layouts.
  • Production-ready export workflows: Export to standalone interactive HTML and generate static images for reports and manuscripts.

Quick Start

Use the plotly skill to generate an interactive scatter chart from your pandas DataFrame and open it in a browser for interactive exploration.

Frequently Asked Questions about plotly

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

FAQPage Schema
How do I create interactive data visualizations from a pandas DataFrame for exploratory analysis?▼

Interactive data visualizations can be generated directly from pandas DataFrames using Plotly Express for fast, tidy-data-driven chart creation. This allows you to explore patterns through hover, pan, zoom, and selection capabilities.

What is the best way to export interactive charts to HTML for stakeholder presentations?▼

Exporting interactive charts to standalone HTML files is supported natively for dashboards and presentations. This workflow also includes generating static images for manuscripts and reports via Kaleido.

Does Plotly Express provide enough control for custom traces and advanced layouts?▼

Plotly Express provides fast, tidy-data-driven charts, but you can use plotly.graph_objects for fine-grained control when you need custom traces, annotations, and advanced layouts.

Can I build 3D and statistical interactive charts for scientific figures?▼

Building interactive charts for scientific figures is fully supported across 2D/3D, statistical, map, and hierarchical scenarios. These publication-quality visualizations enable detailed analytical exploration.

Do I need additional dependencies to generate static images from interactive visualizations?▼

Generating static images from interactive visualizations requires Kaleido for the export workflow. Standalone interactive HTML files can be exported natively without additional image rendering dependencies.

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