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plotly

Generate interactive scientific and statistical data visualizations with Python.

Updated Aug 23, 2026
Search Tags:#dashboards#charts#data analysis#visualization#plotly#interactive plots
One-click install
npx skills add https://github.com/oscartejera/josephine-app --skill plotly-oscartejera
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: plotly
Source: https://github.com/oscartejera/josephine-app/tree/main/.agents/skills/plotly
Command: npx skills add https://github.com/oscartejera/josephine-app --skill plotly-oscartejera

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill empowers users to transform complex data into clear, interactive, and publication-quality charts and dashboards, making data insights accessible and engaging.

Core Features & Use Cases

  • Versatile Charting: Generates over 40 types of charts, from basic scatter plots to complex 3D visualizations and geographic maps.
  • Interactivity: Outputs interactive HTML charts with features like zooming, panning, and hover tooltips.
  • Use Case: A data analyst needs to visualize sales trends over time and by region. They can use this Skill to create an interactive line chart showing sales figures, with options to filter by region and zoom into specific periods, all generated from a pandas DataFrame.

Quick Start

Use the plotly skill to create a scatter plot from the dataframe 'df' using 'x' for the x-axis and 'y' for the y-axis.

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 from a pandas DataFrame?▼

You can create interactive charts from a pandas DataFrame by generating scatter plots, line charts, or dashboards that support zooming, panning, and hover tooltips. The Skill outputs interactive HTML files or static images directly from your data.

Can I generate 3D plots and geographic maps for data analysis?▼

Yes, you can generate 3D plots and geographic maps for data analysis. The Skill supports over 40 chart types, including complex 3D visualizations, heatmaps, and statistical distribution charts for interactive scientific plotting.

What is the best way to build interactive dashboards with Python?▼

The best way to build interactive dashboards with Python is using Plotly Express for quick visualizations or graph objects for fine-grained customization. This allows you to filter data by region and zoom into specific periods while outputting interactive HTML.

Does this visualization approach support both quick plotting and fine-grained customization?▼

Yes, this visualization approach supports both quick plotting and fine-grained customization. You can use Plotly Express for rapid chart generation or switch to graph objects to finely customize scatter plots, financial charts, and statistical distributions.

What output formats do interactive data visualizations support?▼

Interactive data visualizations support output as interactive HTML files with zooming and panning features, as well as static images. This makes data insights accessible for publication-quality charts and dashboards.

Are there limitations when generating statistical distribution charts?▼

Statistical distribution charts are fully supported without specific limitations mentioned. You can generate them alongside scatter plots, bar charts, and heatmaps, using either quick Plotly Express commands or detailed graph objects for visualization.

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