Why is `[` better than `subset`?


Also [ is faster:

microbenchmark(subset(airquality, Month == 8 & Temp > 90),airquality[airquality$Month == 8 & airquality$Temp > 90,])
    Unit: microseconds
                                                           expr     min       lq   median       uq     max neval
                     subset(airquality, Month == 8 & Temp > 90) 301.994 312.1565 317.3600 349.4170 500.903   100
     airquality[airquality$Month == 8 & airquality$Temp > 90, ] 234.807 239.3125 244.2715 271.7885 340.058   100

When I need to filter a data.frame, i.e., extract rows that meet certain conditions, I prefer to use the subset function:

subset(airquality, Month == 8 & Temp > 90)

Rather than the [ function:

airquality[airquality$Month == 8 & airquality$Temp > 90, ]

There are two main reasons for my preference:

  1. I find the code reads better, from left to right. Even people who know nothing about R could tell what the subset statement above is doing.

  2. Because columns can be referred to as variables in the select expression, I can save a few keystrokes. In my example above, I only had to type airquality once with subset, but three times with [.

So I was living happy, using subset everywhere because it is shorter and reads better, even advocating its beauty to my fellow R coders. But yesterday my world broke apart. While reading the subset documentation, I notice this section:


This is a convenience function intended for use interactively. For programming it is better to use the standard subsetting functions like [, and in particular the non-standard evaluation of argument subset can have unanticipated consequences.

Could someone help clarify what the authors mean?

First, what do they mean by "for use interactively"? I know what an interactive session is, as opposed to a script run in BATCH mode but I don't see what difference it should make.

Then, could you please explain "the non-standard evaluation of argument subset" and why it is dangerous, maybe provide an example?