What 1-2 letter object names conflict with existing R objects?

Question

To make my code more readable, I like to avoid names of objects that already exist when creating new objects. Because of the package-based nature of R, and because functions are

Answer 1

Been thinking about this more. Here's a list of one-letter object names in base R:

> var.names <- c(letters,LETTERS)
> var.names[sapply(var.names,exists)]
[1] "c" "q" "t" "C" "D" "F" "I" "T" "X"

And one- and two-letter object names in base R:

one.letter.names <- c(letters,LETTERS)

N <- length(one.letter.names)


first <- rep(one.letter.names,N)
second <- rep(one.letter.names,each=N)

two.letter.names <- paste(first,second,sep="")

var.names <- c(one.letter.names,two.letter.names)

> var.names[sapply(var.names,exists)]
[1] "c"  "d"  "q"  "t"  "C"  "D"  "F"  "I"  "J"  "N"  "T"  "X"  "bc" "gc"
[15] "id" "sd" "de" "Re" "df" "if" "pf" "qf" "rf" "lh" "pi" "vi" "el" "gl"
[29] "ll" "cm" "lm" "rm" "Im" "sp" "qq" "ar" "qr" "tr" "as" "bs" "is" "ls"
[43] "ns" "ps" "ts" "dt" "pt" "qt" "rt" "tt" "by" "VA" "UN"

That's a much bigger list than I initially suspected, although I would never think of naming a variable "if", so to a certain degree it makes sense.

Still doesn't capture object names not in base, or give any sense of which functions are best avoided. I think a better answer would either use expert opinion to figure out which functions are important (e.g. using c is probably worse than using qf) or use a data mining approach on a bunch of R code to see what short-named functions get used the most.