The flip side is that in pandas, chaining is less uniform because it is based on methods.
In R you can pipe a data frame into any function from any package or one you just wrote, so you use %>% for any piping that happens. In pandas, you have special pandas methods that don't need the pipe, but to pipe with any other function, you have to write .pipe.
The comparison is not really between %>% and ., it's between "you just use %>% for everything" and "you use . for a bloated, somewhat arbitrary collection of special pandas methods, and .pipe for everything else".
The sad thing about the conventional object-oriented programming paradigm is how it put the really cool syntactic idea of piping/chaining in the straitjacket of classes and objects.
The ability to pipe shouldn't be tied to whether a function is a method of a class.
