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plotly

Generate interactive Plotly charts from dataframes in Python.

Updated Mar 15, 2026
Search Tags:#charts#interactive#data analysis#visualization#graphs#plotly
One-click install
npx skills add https://github.com/sagunkayastha/claude_skills_collection --skill plotly-sagunkayastha
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: plotly
Source: https://github.com/sagunkayastha/claude_skills_collection/tree/main/data-analysis-visualization/plotly
Command: npx skills add https://github.com/sagunkayastha/claude_skills_collection --skill plotly-sagunkayastha

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill empowers users to create a wide range of interactive and publication-quality data visualizations, making complex data understandable and engaging.

Core Features & Use Cases

  • Interactive Charts: Generate plots with hover info, zoom, pan, and web-embeddable capabilities.
  • Versatile Chart Types: Supports over 40 chart types, from basic scatter plots to complex 3D surfaces and maps.
  • Use Case: Visualize sales data with interactive dashboards, explore scientific datasets with dynamic plots, or create engaging presentations with web-ready charts.

Quick Start

Use the plotly skill to create a scatter plot from the attached dataframe 'sales_data.csv'.

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 in Python for exploratory data analysis?▼

Interactive data visualizations in Python are generated using the Plotly library, supporting over 40 chart types including scatter, bar, pie, histograms, and 3D plots. These charts feature hover tooltips, zoom, pan, and web export capabilities for exploratory data analysis.

Can I build interactive dashboards and presentation graphics with web-embeddable charts?▼

Yes, interactive dashboards and presentation graphics can be built with web-embeddable charts. The visualizations support web export, interactive hover info, zoom, and pan, making complex data understandable and engaging for web display.

What types of graphs and charts can I generate for visualizing complex datasets?▼

Over 40 chart types can be generated for visualizing complex datasets, ranging from basic scatter and line plots to complex bar, pie, box plots, histograms, 3D surfaces, and maps. This versatility facilitates dynamic exploration of scientific and sales data.

Does Python Plotly support 3D plots and geographic maps for data analysis?▼

Python Plotly supports 3D plots and geographic maps for data analysis. Users can generate complex 3D surfaces and maps alongside over 40 other chart types, facilitating dynamic exploration of scientific datasets with interactive features like hover tooltips.

What is the best way to add hover tooltips and zoom features to my data graphs?▼

The best way to add hover tooltips and zoom features to data graphs is by using the Plotly library in Python. It natively generates interactive, publication-quality visualizations equipped with hover info, zoom, and pan capabilities for enhanced data exploration.

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