holoviews

Create interactive multi-layered plots and dashboards with HoloViz, Panel, and Bokeh.

3|Updated Apr 2, 2026

Search Tags:#visualization #data-science #panel #bokeh #holoviews #interactive-plots

Ready to run

npx skills add https://github.com/legout/pi-config --skill holoviews-legout

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: holoviews
Source: https://github.com/legout/pi-config/tree/main/installed-skills/holoviews
Command: npx skills add https://github.com/legout/pi-config --skill holoviews-legout

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires holoviews, hvsampledata, panel, watchfiles, pandas, bokeh.

What problem does it solve?

This skill addresses the complexity of creating professional, interactive data visualizations by providing a standardized, declarative framework that separates data processing from rendering.

Core Features & Use Cases

Declarative Visualization: Build complex, multi-layered plots using a concise, composable API.
Interactive Dashboards: Seamlessly integrate plots into web-based applications using Panel for real-time data exploration.
Use Case: Create a multi-panel dashboard for earthquake analysis that allows users to filter data by magnitude and depth while maintaining consistent, publication-ready styling across all charts.

Quick Start

Use the holoviews skill to generate an interactive bar chart visualizing the distribution of earthquake magnitudes from the sample dataset.

Frequently Asked Questions about holoviews

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

FAQPage Schema

How do I create interactive plots for data science reporting?▼

You can create interactive plots for data science by using a declarative framework that separates data processing from rendering, ensuring professional-grade output through bokeh and panel integrations.

Does HoloViews work with Panel and Bokeh to build dashboards?▼

Yes, HoloViews integrates seamlessly with Panel and Bokeh to build interactive web-based dashboards, allowing users to explore real-time data through multi-layered plots and reactive interactivity.

How do I build multi-layered visualizations for analytical data?▼

Building multi-layered visualizations is achieved through a concise, composable API that enables you to construct complex, multi-panel charts suitable for scientific and analytical reporting.

What's the best declarative visualization framework for scientific dashboards?▼

A declarative visualization framework within the HoloViz ecosystem is ideal for scientific dashboards, as it provides standardized, publication-quality rendering and supports complex multi-layered plots.

Do I need pandas and bokeh to render interactive data visualizations?▼

Yes, you need pandas for data handling and bokeh for rendering interactive data visualizations, along with panel and watchfiles to ensure reactive interactivity and professional-grade display.

Can I filter earthquake data by magnitude in an interactive dashboard?▼

Yes, you can filter earthquake data by magnitude and depth in an interactive dashboard, maintaining consistent publication-ready styling across all charts while allowing real-time data exploration.