Skip to content

Jupyter-flex: Easy interactive dashboards for Jupyter

Use Jupyter Notebooks to quickly create interactive dashboards.

  • Use Markdown headers and Jupyter Notebook cell tags to define the dashboard components
  • Flexible and easy way to specify row and column based layouts
  • Use nbconvert to create static reports
  • Use Voila to start a live Jupyter Kernel for fully dynamic applications
  • Support for ipywidgets

Inspired by Flex Dashboards.



$ pip install jupyter-flex


The Getting started page goes through the basic steps of taking a Jupyter Notebook and creating your first Jupyter-flex dashboard, explains simple Jupyter-flex concepts such as layouts, document orientation and explains how to use nbconvert to generate a static .html dashboard.

The Layouts page goes in depth about all the options to control the content of Jupyter-flex dashboards.

The Plotting page goes through some considerations around different plotting libraries in Jupyter-flex dashboards.

The Voila and IPywidgets page describes how to leverage Voila to create dashboards that use a live Jupyter kernel that enable viewers to change underlying parameters and see the results immediately using ipywidgets.


Jupyter-flex: altair
Altair plots
Jupyter-flex: Plotly Plots
Plotly plots
Jupyter-flex: Bokeh Plots
Bokeh plots
ipywidgets-gallery (runs in
Jupyter-flex: bqplot
bqplot plots (runs in
Jupyter-flex: Movie Explorer
Movie Explorer (runs in
Jupyter-flex: Wealth of Nations
Wealth of Nations (runs in
Jupyter-flex: Iris Clustering
Iris clustering (runs in
Jupyter-flex: NBA Scoring
NBA Scoring


Source for all examples can be found on Github.

Some apps developed using Jupyter-flex

  • Investment Flow Type Classification [App] [Source]