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.
Terminal
``` $ 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.
Altair plots
Plotly plots
Bokeh plots
ipywidgets-gallery (runs in binder.org)
bqplot plots (runs in mybinder.org)
Movie Explorer (runs in mybinder.org)
Wealth of Nations (runs in mybinder.org)
Iris clustering (runs in mybinder.org)
NBA Scoring
!!! info Source for all examples can be found on Github.