Visualising high-dimensional datasets in Plotly - multiple sliders for multiple independent variables?

📊 Plotly Python
1

Hi there, I am using Plotly to visualise high-dimensional datasets for which it is extremely useful. Given the animation_frame allows iterating along a ‘hidden’ dimension, it seems logical that multiple animation_frames would allow iterating across multiple hidden dimensions (granted it may be challenging to develop a good intuition of such a high-dimensional dataset!).

For example, if I’m trying to plot the spread of a dataset with px.box, I can set independent variables with x, color, facet_col, facet_row, and animation_frame - so I can visualise the spread of data as a function of five independent variables (there is a sixth variable for which the variation across is plotted).

Say I have a higher dimensional dataset - I understand from the documentation that there is no way with the one-liner functions (eg px.box) but is there a way with graph_objects? Or perhaps with Dash?

Many thanks,
Nick

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Hey @nickMasonSmith welcome to the forums.

Your use case sounds interesting!

You can do a lot of cool stuff with dash, so I would say yes, even if I did not fully understand what you want to do exactly. :wink: