Visualization/Interactive Model Architecture for Multivariate Analysis

Hello,

I came to Panel via a recommendation to a question on bokeh’s discourse page here. Bokeh Visualization/Interactive Model Architecture for Multivariate Analysis

A succinct description of my question …

I have a multivariate analysis and visualization method that can support “what-if” scenarios to include and exclude independent variables and see how that affects modeling performance. To implement this in an interactive visualization app, I am looking for a way to quickly add (or remove) plots and widgets as variables are introduced (excluded) from the analysis.

Does Panel support such capabilities?

I think I found the answer in the documentation here… Panel Components

The Row , Column , and Tabs Panels all behave very similarly. All of them are list-like, which means they have many of the same methods as a simple Python list, making it easy to add, replace, and remove components interactively using append , extend , clear , insert , pop , remove and __setitem__ . These methods make it possible to interactively configure and modify an arrangement of plots, making them an extremely powerful tool for building apps or dashboards.

Hi @_jm

Welcome to the community.

In addition to the links you have found you might also be able to draw inspiration from the the HoloViews composing Elements documentation https://holoviews.org/user_guide/Composing_Elements.html.

Feel free to share some code, screenshots or videos. You might get some inspiration back or inspire others.

1 Like