Panel

Panel

Open Source

The powerful data exploration & web app framework for Python.

Data Apps

Scores

Popularity
1/5
Learning Curve
4/5
Flexibility
5/5
Performance
4/5
Portability
3/5

About

Panel is an open-source Python library developed as part of the HoloViz ecosystem, designed for creating interactive dashboards, data exploration tools, and full-featured web applications. Unlike Streamlit (which re-runs the entire script on interaction), Panel offers both a high-level reactive API and a lower-level callback API, giving developers fine-grained control over interactivity. Panel is unique in its deep integration with the scientific Python visualization ecosystem — it natively supports Matplotlib, Bokeh, HoloViews, Altair, Plotly, Vega, and many more plotting libraries, plus widgets for Jupyter, HTML, and native browser rendering. Panel apps can be deployed as standalone web servers or inside Jupyter Notebooks, making it particularly popular in scientific research and data exploration contexts. The library is BSD-licensed and maintained by Anaconda/HoloViz contributors.

Key Features

  • Reactive and callback-based API for interactive dashboards
  • Supports 15+ visualization libraries: Bokeh, Matplotlib, Plotly, Altair, HoloViews, Vega
  • Runs natively in Jupyter Notebooks and as standalone web servers
  • Param-based declarative parameter system for reactive state
  • Template system for professional dashboard layouts
  • WebAssembly (WASM) export via Panel + Pyodide for serverless deployment
  • Streaming data support for real-time dashboards
  • Part of HoloViz ecosystem: interoperates with HoloViews, GeoViews, hvPlot

Pros

  • Broadest visualization library support of any Python dashboard framework
  • Works natively in Jupyter — no context-switching for exploratory analysis
  • Fine-grained reactive control compared to Streamlit's script re-run model
  • WASM export enables serverless static dashboard deployment
  • Strong in scientific Python and academic research communities
  • BSD license, free for all uses

Cons

  • Smaller community and ecosystem compared to Streamlit or Dash
  • Higher learning curve — more concepts to learn (Param, reactive API, callback API)
  • Less polished out-of-the-box UI compared to Streamlit or Gradio
  • Fewer community templates and third-party extensions
  • Documentation can be inconsistent across different versions

Pricing

Open Source

Possible Stacks

Panel Data App

Project

Interactive data application built with Panel and Pandas — create dashboards and data apps with a Pythonic API.

Programming

Data

Data

Sandbox

Learning Resources

No resources yet — check back soon.

Tags

PythonOpen SourceData VisualizationDashboards

Details

Maintained
Yes
Primary language
Python
Domain
Data
GitHub stars
5.7k
Stars updated
2026-04-18