[groceryheist]

To answer your question:

ggplot2 : plotnine is quite good ggplot2 clone based on matplotlib. I feel like ggplot2 is a bit better and more complete, but if you want to do something that isn't supported it's harder for me to hack than matplotlib.

Tidyverse: To me, ggplot2 is the only essential part of the tidyverse. Lubridate is also good. Most others seem like semantics and syntax sugar. I prefer data.table, which is similar to Pandas. DT is super fast but imho Pandas has a more intuitive and consistent API (and if you want a speed up for large N then dask might work).

I use both R and Python on a regular basis. I choose Python for lower-level stuff, automation, parallelism / concurrency, and R for bespoke statistics. I use both for everyday statistics and plotting, but I feel that R has light advantages. I feel like if you're comfortable switching languages there are good reasons to use both. It's also important for me because I work with different teams that have different practices and preferences.