RStudio is a full-fledged IDE and you should definitely use it. It has movable panes for code, console, help files, history, plots, etc. There's nothing comparable in Python land.
Since the acquisition of Yhat by Alteryx (Yhat created Rodeo) the Rodeo project seems dead. Another good alternative is Spyder which offers a similar type of IDE and one that is still being developed.
Disclaimer: I work for RStudio. I previously worked heavily with SciPy.
The difference kind of goes to the fundamental difference between R and Python. R's nature as a statistical programming language is something you have to install packages in python to achieve: numpy, matplotlib, etc.
What you gain with RStudio are environment inspection tools[1] built for the kind of vectors, data frames, etc. that you'd only get with `numpy` in Python land, and therefore PyCharm and VS don't know about (or would need a plugin to know about). Same goes for the plot viewer and `matplotlib`.
Beyond that, a sizeable portion of RStudio's runtime is written in R itself; you can actually write addins for the IDE using R, as opposed to PyCharm where you'd have to know Java or Kotlin, and I assume VS where you'd be required to use .NET.
It's always going to come down to "what is the best tool _for the job_?" Knowing people who use python for data science, they don't seem to indicate to me that they're particularly fond of PyCharm (which is what I'd use for Python if it's too big a project to effectively grok in VIM). They tend to use Jupyter notebooks (not even iPython!) because more important than static inspection and quality tools (which devs care about) is a richly-featured REPL that saves detailed history forever (which a researcher cares about).
