For example, I have a data frame with data across categories and subcategories and I want to be able to get row with maximum value in a particular column etc.
SQL is what comes to mind first. But since I am not interested in joins or indices etc, python’s list comprehensions would do the same thing better with a more modern syntax.
What’s best practice in R for such operations?
EDIT:
For now I think I am fine with which.max. Why I asked the question the way I did is simply that I have come to learn that in R there are many libraries etc doing pretty much the same thing. Just by reading the documentation it’s very hard to evaluate how popular (ie how well the library fulfills its purpose). My personal experience with Python is that the day you figure out how to use list comprehensions (with itertools as a bonus), you are pretty much covered. Over time this has evolved as best practice, you don’t see lambda and filter for example that often in the general python debate these days as list comprehensions does the same thing easier and more uniform.
Some additional context would help, but from the sounds of it – you may be looking for
which.max()or the related functions. For group by operations, I default to theplyrfamily of functions, but there are certainly faster alternatives in base R if speed is of utmost importance.