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plotly

Create interactive charts and dashboards with Plotly Express and graph_objects.

322|45|Updated Dec 1, 2025
Search Tags:#python#interactive#plotly#chart#plotly-express
One-click install
npx skills add https://github.com/Microck/ordinary-claude-skills --skill plotly
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: plotly
Source: https://github.com/Microck/ordinary-claude-skills/tree/main/skills_all/plotly
Command: npx skills add https://github.com/Microck/ordinary-claude-skills --skill plotly

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Enables quick and flexible creation of interactive charts and dashboards for scientific and statistical data.

Core Features & Use Cases

  • Scatter, line, bar, heatmap, 3D plots
  • Interactive features and exports (HTML, PNG, PDF, SVG)
  • Express vs Graph Objects API for quick vs detailed customization

Quick Start

Create a simple scatter plot with Plotly Express from a pandas DataFrame.

Frequently Asked Questions about plotly

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

FAQPage Schema
How do I create interactive charts in Python with hover and zoom features?▼

Interactive charts in Python are best created with Plotly, which provides built-in hover tooltips, pan, zoom, and selection across 40+ chart types. Plotly Express enables rapid chart creation from pandas DataFrames, while graph_objects offers fine-grained customization for dashboards and scientific visualizations.

Can I export interactive visualizations as static images like PNG or PDF?▼

Yes. Plotly generates interactive HTML by default and exports to static formats (PNG, PDF, SVG) using Kaleido. This lets you embed charts in reports, presentations, or publications while retaining the option to share interactive versions separately.

What's the difference between Plotly Express and graph_objects for building charts?▼

Plotly Express is a high-level API for rapid exploratory charts from simple function calls. Graph_objects provides lower-level control for detailed customization, layout refinement, and polished dashboard production when Express defaults don't meet your design or interactivity needs.

Does Plotly work with pandas DataFrames for data visualization?▼

Yes. Plotly Express integrates directly with pandas DataFrames, accepting them as input to generate scatter, line, bar, heatmap, and 3D plots with minimal code, making it ideal for exploratory analysis and quick statistical visualizations.

Can I create 3D plots and geographic visualizations with Plotly?▼

Yes. Plotly supports 3D scatter, surface, and mesh plots alongside geographic visualizations with built-in map tiles and color scales. This covers scientific, statistical, and geographic data across diverse domains without switching libraries.

How do I customize chart colors, templates, and styling in Plotly?▼

Plotly offers built-in templates, discrete and continuous color scales, and layout control through both Express parameters and graph_objects properties. This enables consistent branding and theme application across single charts and multi-chart dashboards.

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