absolutely agree with everything you said!
We had a longer discussion about this (stats/data science in Observable in general) in this thread: Observable for research - (advanced) statistics
Since then, I’ve been trying to port a few R/python functions to JS, which are also based on mljs:
R’s lm, vif, View, summary, stargazer: Linear models in Observable notebooks / Christoph Pahmeyer / Observable
R’s cor, var(i), corrplot, plot, hist: Correlation, Variance And Covariance (Matrices) / Christoph Pahmeyer / Observable
Seaborns (python) pairplot: Plotting pairwise relationships in a dataset / Christoph Pahmeyer / Observable
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Just as you said before, these lack a solid/fast WASM implementation in the background. So they will become slow on large datasets! Anyways, I’ill add those to the notebook later!
Especially for the summary (Summary Table / Observable / Observable), and obviously the plot functions (Shorthand / Observable Plot / Observable / Observable) Observable has much better alternatives though 