Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Another R tip. Get in the habit of using drop = FALSE when indexing (using [ , ] on) data.frames.

In R, single column data.frames are often converted to vectors when manipulated. For example:

d <- data.frame(x = seq_len(3))
print(d)
#>   x
#> 1 1
#> 2 2
#> 3 3

# not a data frame!
d[order(-d$x), ] #> [1] 3 2 1  We were merely trying to re-order the rows and the result was converted to a vector. This happened because the rules for [ , ] change if there is only one result column. This happens even if the there had been only one input column. Another example is: d[,] is also vector in this case. The issue is: if we are writing re-usable code we are often programming before we know complete contents of a variable or argument. For a data.frame named “g” supplied as an argument: g[vec, ] can be a data.frame or a vector (or even possibly a list). However we do know if g is a data.frame then g[vec, , drop = FALSE] is also a data.frame (assuming vec is a vector of valid row indices or a logical vector, note: NA induces some special cases). We care as vectors and data.frames have different semantics, so are not fully substitutable in later code. The fix is to include drop = FALSE as a third argument to [ , ]. # is a data frame. d[order(-d$x), , drop = FALSE]
#>   x
#> 3 3
#> 2 2
#> 1 1


To pull out a column I suggest using one of the many good extraction notations (all using the fact a data.frame is officially a list of columns):

d[["x"]]
#> [1] 1 2 3

d\$x
#> [1] 1 2 3

d[[1]]
#> [1] 1 2 3


My overall advice is: get in the habit of including drop = FALSE when working with [ , ] and data.frames. I say do this even when it is obvious that the result does in fact have more than one column.

For example write “mtcars[, c("mpg", "cyl"), drop = FALSE]” instead of “mtcars[, c("mpg", "cyl")]“. It is clear that for data.frames both forms should work the same (either selecting a data frame with two columns, or throwing an error if we have mentioned a non existent column). But longer drop = FALSE form is safer (go further towards ensuring type stable code) and more importantly documents intent (that you wanted a data.frame result).

One can also try base::subset(), as it has non-dropping defaults.