Assignment operators in R: ‘=’ vs. ‘<-’

In R, you can use  both ‘=’ and ‘<-’ as assignment operators. So what’s the difference between them and which one should you use?

What’s the difference?

The main difference between the two assignment operators is scope. It’s easiest to see the difference with an example:
##Delete x (if it exists) > rm(x) > mean(x=1:10) #[1] 5.5 > x #Error: object 'x' not found
Here x is declared within the function’s scope of the function, so it doesn’t exist in the user workspace. Now, let’s run the same piece of code with using the <- operator:
> mean(x <- 1:10)# [1] 5.5 > x # [1] 1 2 3 4 5 6 7 8 9 10
This time the x variable is declared within the user workspace.

Which one should I use

Well there’s quite a strong following for the “<-” operator:

• The Google R style guide prohibits the use of “=” for assignment.
• Hadley Wickham’s style guide recommends “<-”
• If you want your code to be compatible with S-plus you should use “<-”
• I believe that the General R community recommend using “<-”, but I can’t find anything on the mailing list.

However, I tend always use the “=” operator for the following reasons:

• The other languages I program in (python, C and occasionally JavaScript) use the “=” operator.
• It’s quicker to type “=” and “<-”.
• Typically, when I type declare a variable – I only want it to exist in the current workspace.
• Since I have the pleasure of teaching undergraduates their first course in programming, using “=” avoids misleading expressions like if (x[1]<-2)

Also Introducing Monte Carlo Methods with R, by Robert and Casella recommends using “=”.

If I’m missing something or you disagree, please leave a comment – I would be very interested.

References

• Stackoverflow question
• The R manual’s description of assignment operators