Python vs R is the new Matlab vs R (and soon it may be Julia vs R). My answer is always the same: there are a few excellent and quasi-standard packages/librari

Python vs R is the new Matlab vs R (and soon it may be Julia vs R). My answer is always the same: there are a few excellent and quasi-standard packages/libraries that exist in one of them without fully equivalent analogues in the others, so if you need any of those then go with that system (eg Simulink in Matlab, tons of classical statistical models in R, some ML/DL libraries in Python). In fact, you might have to use multiple systems if your problems are complex enough and you don't want to compromise. If you don't fall in that category, then just stick with what you have, any of those languages are decent enough general purpose tools and the differences don't justify a codebase migration.