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plotly

Create interactive web-embeddable visualizations with Plotly Express and graph_objects.

2|Updated Apr 12, 2026
Search Tags:#interactive#visualization#plotly#export#plotly-express#dash#graph-objects
One-click install
npx skills add https://github.com/Clay-HHK/claude-config --skill plotly-clay-hhk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: plotly
Source: https://github.com/Clay-HHK/claude-config/tree/main/skills/plotly
Command: npx skills add https://github.com/Clay-HHK/claude-config --skill plotly-clay-hhk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Provide interactive, exploratory, and web-embeddable visualizations so users can inspect data with hover tooltips, pan/zoom, selections, and animations rather than static images that hide detail and interactivity.

Core Features & Use Cases

  • Wide chart coverage: 40+ chart types including scatter, line, bar, heatmap, 3D, maps, financial charts, and hierarchical diagrams.
  • Two APIs: Plotly Express for fast, high-level plotting from DataFrames and graph_objects for fine-grained control and custom multi-trace figures.
  • Interactivity & exports: Built-in hover tooltips, selection, rangesliders, animations, HTML export for embedding, and static image export via kaleido.
  • Integration: Embeds in Dash apps or Jupyter (FigureWidget) for interactive dashboards and web applications.
  • Use Case: Build an exploratory dashboard that lets analysts filter time series, zoom into regions, and export interactive charts for stakeholder presentations.

Quick Start

Create an interactive scatter plot from my pandas DataFrame df using Plotly Express with hover tooltips and export it as a standalone HTML file.

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 with hover tooltips and zoom from a pandas DataFrame?▼

Interactive data visualizations with hover tooltips and zoom can be created using Plotly Express for fast, high-level plotting directly from pandas DataFrames. This allows you to inspect data dynamically rather than viewing static images.

Can I export interactive charts as a standalone HTML file for web embedding?▼

Yes, interactive charts can be exported as standalone HTML files for web embedding. The Skill supports HTML export for presentations and dashboards, alongside static image exports like PNG via the kaleido engine.

What is the best way to build an exploratory dashboard with time series filtering and selection?▼

The best way to build an exploratory dashboard with time series filtering is by leveraging built-in interactivity like selections and rangesliders. Figures can be embedded into Dash apps or Jupyter via FigureWidget for full web application integration.

Does this support both high-level plotting and fine-grained control for custom multi-trace figures?▼

Yes, it supports both high-level plotting and fine-grained control through two APIs. Use Plotly Express for rapid plotting from DataFrames, and switch to graph_objects for custom multi-trace figures and detailed layout adjustments.

What chart types are available for geospatial, 3D, and financial data visualization?▼

Over 40 chart types are available for geospatial, 3D, and financial data visualization. The Skill covers scatter, line, bar, heatmap, 3D surfaces, maps, financial charts, and hierarchical diagrams for exploratory analysis.

When should I not use interactive visualizations for my data presentation?▼

You should avoid interactive visualizations when you need lightweight static images for printed reports. While interactive charts provide exploratory depth, generating static exports via kaleido adds processing overhead compared to native static plotting libraries.

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