Dear R cognoscenti,
While having NA as a native type is nifty, it is annoying when making binary
choices.
Question: Is there anything bad about writing comparison functions that
behavior like %in% (which I love) and ignore NAs?
"%>%" <- function(table, x) {
return(which(table > x))
}
"%<%" <- function(table, x) {
return(which(table < x))
}
test <- c(NA, 1:4,NA,5)
test %>% 2
# [1] 3 4 6
test %<% 2
# [1] 1
Why do I want to do this?
Because in coding, I often end up with big chunks looking like this:
((mydataframeName$myvariableName > 2 & !is.na(mydataframeName$myvariableName))
& (mydataframeName$myotherVariableName == "male" &
!is.na(mydataframeName$myotherVariableName)))
Which is much less readable/maintainable/editable than
mydataframeName$myvariableName > 2 & mydataframeName$myotherVariableName ==
"male"
But ">" returns anything involving an NA, so it breaks selection statements
(which can't contain NA) and leaves lines in data that are wished to be excluded
If this does not have nasty side-effects, it would be a great addition to GTD*
in R
If anyone knows a short cut to code the effect I wish, love to hear it.
Cheers,
tim
* GTD = Getting Things Done
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