One big advantage of SAS over R is arguably its ability to produce quite complex reports with few statements; think of
PROC SUMMARY or
PROC TABULATE for instance.
My heart goes to R because of its openness and vibrant community. But I must admit that SAS's PROCS are quite powerful out-of-the-box. To partially address those issues I wrote an R package titled summarytools which provides ways to generate decent looking and translatable (thanks to pander,
Pandoc implemented in R) simple reports (frequencies, univariate stats, codebook, for the essential part) to various formats like RTF, pdf, and markdown.
However, even with the use of by() to stratify the stats (be it frequencies or univariate numerical stats), I feel I'm still miles away from generating as flexible and complete tables such as with
PROC TABULATE or
PROC MEANS. So my question is: what R packages do you find are "musts" for needs of extracting essential stats from dataframes, splitting on this variable and filtering on that other one. I hope this is not judged as too broad a question; I have made my homework and tried finding the answer to this question before posting here. I'm sure there are some really really well-made packages that adress those issues, and I simply haven't seen them around... yet. So if I may ask, please hold off for a day or two before putting the lock on this one. ;)
Any input is mostly welcome!