R is first and foremost an interactive language, and the focus of the libraries, tooling, and community reflects that. I believe working in pandas/sklearn/jupy

R is first and foremost an interactive language, and the focus of the libraries, tooling, and community reflects that. I believe working in pandas/sklearn/jupyter ecosystem is much slower (>50%) if you are doing EDA and statistical modelling (ML) than tidyverse/tidymodels/rstudio. The exception is deep learning and adjacent fields (like computer vision). Of course Python is better at everything else, so adding an extra languages might or might be worth the hassle.