Visualization/Interactive Model Architecture for Multivariate Analysis


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

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

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