AwesomeDataviz

Jupyter & notebook visualization

Interactive charts inside Jupyter and other notebooks. 16 tools, ranked by GitHub stars and updated .

Libraries that shine inside Jupyter and other notebooks: interactive widgets, inline 3D views and charts that update as you explore.

By GitHub stars, the most popular notebook visualization tools here are Bokeh (20.5K stars), Plotly (Python) (18.8K stars), and PyGWalker (16K stars). 11 of 16 had commits in the last 90 days.
1 Bokeh

Interactive Web Plotting for Python.

 Python 20.5K 344 BSD-3-Clause
2 Plotly (Python)

Interactive web based visualization built on top of plotly.js

 Python 18.8K 739 MIT
3 PyGWalker

Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker.

 Python 16K 154 Apache-2.0
4 ydata-profiling

Generates statistical analytic reports with visualization for quick data analysis (formerly pandas-profiling).

 Python 13.7K 8 MIT
5 Phoenix

ML observability in a notebook with UMAP visualizations

 Machine learning 11.7K 3,725 Elastic-2.0
6 Perspective

Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly.

 More JavaScript 11.3K 337 Apache-2.0
7 Vega-Altair

Declarative statistical visualizations, based on Vega-Lite.

 Python 10.5K 153 BSD-3-Clause
8 Voilà

Turns Jupyter notebooks into standalone interactive web applications.

 Python 5.9K 12 BSD
9 Panel

Data exploration and web app framework for Python that works with many plotting libraries.

 Python 5.8K 392 BSD-3-Clause
10 leafmap

Interactive mapping and geospatial analysis in Jupyter with multiple mapping backends.

 Python 3.8K 147 MIT
11 bqplot

Plotting library for IPython/Jupyter notebooks.

 Python 3.7K 21 Apache-2.0
12 HoloViews

Complex and declarative visualizations from annotated data.

 Python 2.9K 321 BSD-3-Clause
13 Lets-Plot

Grammar of graphics plotting library for Python and Kotlin, by JetBrains.

 Python 1.8K 606 MIT
14 Lets-Plot for Kotlin

Grammar of graphics plotting API for Kotlin, built on Lets-Plot.

 JVM 487 129 MIT
15 Quibbler Inactive

Your data and anything you plot is effortlessly live and interactive.

 Python 332 0 MIT
16 ipychart Inactive

The power of Chart.js in Jupyter Notebook.

 Python 133 0 MIT

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Frequently asked questions

What is the most popular notebook visualization tool?

By GitHub stars, Bokeh is the most popular, with 20.5K stars, followed by Plotly (Python) (18.8K) and PyGWalker (16K).

Which notebook visualization tools are actively maintained?

14 of the 16 tools listed had commits in the last 12 months, including Bokeh, Plotly (Python), PyGWalker, ydata-profiling, and Phoenix. Each tool page shows monthly commit activity.

Are these notebook visualization tools free and open source?

15 of the 16 tools listed use an OSI-approved open-source license; the others are source-available, free to use, or use a custom license, so check each tool page. The most common license here is MIT.

Missing a tool? Add it with a one-line pull request to the README.