Once you include the statistical packages, ggplot2, and dplyr, there is nothing that beats R in ease of prototyping for data exploration, model fits and sanity checks, and data visualisation of high dimensional data.
In my experience, the specific things R does well, python does it in a clunkier way.
Statistical software written by statisticians in academia, bioconductor, and quick prototyping is still much faster in R than in python.
My use case is to prototype in R, then move to python if things become more production rather than exploratory.