@edyhsgr Potentially controversial, but I agree!
I was annoyed when the code demos for a particular uni course relied on #tidyR, because I felt that I hadn't learned enough #baseR yet.
So I stuck to base for my big assignment, only bringing in other packages where needed. It's not that I dislike tidy; it's just that I want to be in control of the packages - I don't want the packages to be in control of me.
Any #rstats users here that use #tidyr et al. for clustering and ordination?
I'm trying to wrap my head around how I should manage a workflow like:
data -> distance matrix -> clustering or ordination
*without* the benefit of row names to link the original data to the resulting cluster leaf or ordination point.