I exaggerated the comparison for effect. However, it is not very difficult
to find functions in dplyr or data.table or indeed other packages that one
may wish to be in base R. Examples, for me, could include
data.table::fread, dplyr::group_by & dplyr::summari[sZ]e combo, etc. Also,
the "popularity" of magrittr::`%>%` is mostly attributable to the tidyverse
(an advanced superset of R). Many R users don't even know that they are
installing the magrittr package.
On Sat, Oct 5, 2019 at 6:30 PM Iñaki Ucar <iu...@fedoraproject.org> wrote:
> On Sat, 5 Oct 2019 at 17:15, Hugh Marera <hugh.mar...@gmail.com> wrote:
> >
> > How is your argument different to, say, "Should dplyr or data.table be
> > part of base R as they are the most popular data science packages and
> they
> > are used by a large number of users?"
>
> Two packages with many features, dozens of functions and under heavy
> development to fix bugs, add new features and improve performance, vs.
> a single operator with a limited and well-defined functionality, and a
> reference implementation that hasn't changed in years (but certainly
> hackish in a way that probably could only be improved from R itself).
>
> Can't you really spot the difference?
>
> Iñaki
>
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