I agree with Matloff's overall point, though. "Tidy programming" (which came to mean non-standard evaluation) is very hard to understand, even for R profession

I agree with Matloff's overall point, though. "Tidy programming" (which came to mean non-standard evaluation) is very hard to understand, even for R professionals. It relies on directly handling symbols, and encourages using new notations to do it. Debugging is even more complex with NST code, and people learning the language will be doing a lot of debugging. I can't imagine a good way to introduce functions to newer users when using NST. You'd have to first mention environments, scoping, and symbols. My rant aside, I did find this next quote from Matloff a better argument for using dplyr: > mean(Nile[80:100]) "printing the mean Nile River flow during a certain range of years. Incredibly, not only would this NOT be in a first lesson with Tidy, the students in a Tidy course may actually never learn how to do this. Typical Tidiers don't consider vectors very important for learners, let alone vector subscipts." With dplyr, you'd subset based on a `filter()`, likely specifying the years to keep. It encourages self-explanatory code. Matloff's vector subscript tells me nothing about why certain elements are kept.