Python is a pretty bad language for tabular data analysis and plotting, which seems to be the actual topic of this post. R is certainly better, hell Tableau, Matlab, JMP, Prism and even Excel are all better in many cases. Pandas+seaborn has done a lot, but seaborn still has frustrating limits. And pandas is essentially a separate programming language.

If your data is already in a table, and you’re using Python, you’re doing it because you want to learn Python for your next job. Not because it’s the best tool for your current job. The one thing Python has on all those other options is $$$. You will be far more employable than if you stick to R.

And the reason for that is because Python is one of the best languages for data and ML engineering, which is about 80% of what a data science job actually entails.

> And pandas is essentially a separate programming language.

I'd say dplyr/tidyverse is a lot more a separate programming language to R than pandas is to Python.

...unless your data engineering job happens on a database, in which case R's dbplyr is far better than anything Python has to offer.