Michelle Golchert contrasts libraries for visualizing data in R and Python:
Unlike R, Python – as a “general-purpose” programming language – does not include data visualization tools by default. However, Python also provides many libraries for this purpose, such as Matplotlib and Seaborn.
Python now also offers numerous packages (like plotnine and ggpy) which are equivalents of ggplot2 in R, and allow you to create plots in Python according to the same “Grammar of Graphics” principle.
This is an area where I think R has the upper hand at most levels: it’s easier to get started plotting with R (thanks to the built-in plots), it’s easier to do “intermediate-quality” plots (stuff you would use in an internal presentation), and you tend to have more control when building professional-quality plots. You can certainly create beautiful visuals in both languages, though.