> I for one am happy this discussion pops up, because it's a piece of > information I give to my students as well: convert to a data.frame when you > start your analysis just to play safe. And this discussion shows why that is > -for the time being!- a good advice. The moment tibbles become the default > data format in R, or some R++, or in Julia for all I care, I'll be more than > happy to burn that drop = FALSE on a stake. But for now we can't ignore the > differences and the potential for conflicts when you try to use a tibble > instead of a data.frame.
I think this is sub-optimal advice because most functions do work fine with tibbles. It is only a few packages (largely written some time ago) that don't. And typically, if they don't work with tibbles, you'll get a (usually slightly confusing) error message because some function will get a data frame instead of a vector. So as far I can tell, you only need to as.data.frame() retrospectively, not prospectively. Are you aware of any code that returns an incorrect result (i.e. no error) when given a tibble instead of a data frame? Hadley -- http://hadley.nz ______________________________________________ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel