Hey, author of siuba here, I totally agree that subclassing would be a natural choice in python. One challenge there is that users will often get a DataFrame ba

Hey, author of siuba here, I totally agree that subclassing would be a natural choice in python. One challenge there is that users will often get a DataFrame back (e.g. from pd.read_csv), so it requires a lot of casting to the child class. Right now, a compromise I've been exploring is just attaching siuba's DF functions to a pandas DataFrame, e.g. df.siu_mutate(...). This seems to be what pandas wants people to do [1]! One obstacle here is that the DataFrame has 300+ methods, which can be overwhelming to learners. I've spent a lot of time wondering whether the piping syntax feels like too much vs chaining. It's still an open question in my mind, so it's really helpful to hear what feels most natural! https://pandas.pydata.org/pandas-docs/stable/development/extending.html#registering-custom-accessors https://pandas.pydata.org/pandas-docs/stable/development/ext...