data.table - What do . (dot) and % (percentage) mean in R?

Question

My question might sound stupid but I have noticed that . and % is often used in R and to be frank I don't really know why it is used.

I have seen it in dplyr (go here for an example) and data.table (i.e. .SD) but I am sure it must be used in other place as well.

Therefore, my question is:

• What does . mean? Is it some kind of R coding best practice nomenclature? (i.e. _functionName is often used in javascript to indicate it is a private function). If yes, what's the rule?
• Same question for %, which is also often used in R (i.e. %in%,%>%,...).

My guess always has been that . and % are a convenient way to quickly call function but the way data.table uses . does not follow this logic, which confuses me.

Answer 1

. has no inherent/magical meaning in R. It's just another character that you can use in symbol names. But because it is so convenient to type, it has been given special meaning by certain functions and conventions in R. Here are just a few

• . is used look up S3 generic method implementations. For example, if you call a generic function like plot with an object of class lm as the first parameter, then it will look for a function named plot.lm and, if found, call that.
• often . in formulas means "all other variables", for example lm(y~., data=dd) will regress y on all the other variables in the data.frame dd.
• libraries like dplyr use it as a special variable name to indicate the current data.frame for methods like do(). They could just as easily have chosen to use the variable name X instead
• functions like bquote use .() as a special function to escape variables in expressions
• variables that start with a period are considered "hidden" and will not show up with ls() unless you call ls(all.names=TRUE) (similar to the UNIX file system behavior)

However, you can also just define a variable named my.awesome.variable<-42 and it will work just like any other variable.

A % by itself doesn't mean anything special, but R allows you to define your own infix operators in the form %<something>% using two percent signs. If you define

`%myfun%` <- function(a,b) {
    a*3-b*2
}

you can call it like

5 %myfun% 2
# [1] 11