This, along with inferior metaprogramming affordances, is the biggest reason pandas will never be as productive an analyst tool as R's dplyr. In R you can pipe anything into anything. In pandas you're stuck with the methods pandas gives you.
This is also why pandas API is so bloated. A lot of pandas special-case functionality, like dropping duplicate rows, can be replicated in R by chaining together more flexible and orthogonal primitives.
This is also why pandas API is so bloated. A lot of pandas special-case functionality, like dropping duplicate rows, can be replicated in R by chaining together more flexible and orthogonal primitives.