[R] lapply vs. for (was: Incrementing a counter in lapply)

[Patrick Burns]

In my opinion the main issue between using 'for' and
an apply function is the simplicity of the code.  If it is
simpler and more understandable to use 'lapply' than
a 'for' loop in a situation, then use 'lapply'.  If in a
different situation it is the 'for' loop that is simpler, then
use the 'for' loop.

In modern day R whatever timing differences there may
be are likely to be slight, and virtually certain not to be
critical.

Where the confusion comes in is because in the olden
days of S-PLUS, the timing differences could be quite
substantial in some cases.  The hangover from that is
that apply functions are too often recommended in R.


Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of S Poetry and "A Guide for the Unwilling S User")

Gregor Gorjanc wrote:

>>From: Thomas Lumley
>>    
>>
>>>On Tue, 14 Mar 2006, John McHenry wrote:
>>>
>>>      
>>>
>>>>Thanks, Gabor & Thomas.
>>>>
>>>>Apologies, but I used an example that obfuscated the question that I
>>>>wanted to ask.
>>>>
>>>>I really wanted to know how to have extra arguments in 
>>>>        
>>>>
>>>functions that
>>>      
>>>
>>>>would allow, per the example code, for something like a 
>>>>        
>>>>
>>>counter to be 
>>>      
>>>
>>>>incremented. Thomas's suggestion of using mapply 
>>>>        
>>>>
>>>(reproduced below with 
>>>      
>>>
>>>>corrections) is probably closest.
>>>>        
>>>>
>>>It is probably worth pointing out here that the R 
>>>documentation does not 
>>>specify the order in which lapply() does the computation.
>>>
>>>If you could work out how to increment a counter (and you could, with 
>>>sufficient effort), it would not necessarily work, because the 'i'th 
>>>evaluation would not necessarily be of the 'i'th element.
>>>
>>>[lapply() does in fact start at the beginning, go on until it 
>>>gets to the 
>>>end, and then stop, but this isn't documented.   Suppose R became 
>>>multithreaded, for example....]
>>>      
>>>
>>The corollary, it seems to me, is that sometimes it's better to leave the
>>good old for loop alone.  It's not always profitable to turn for loops into
>>some *apply construct.  The trick is learning to know when to do it and when
>>not to.
>>    
>>
>
>Can someone share some of this tricks with me? Up to now I have always
>done things with for loop. Just recently I started to pay attention to
>*apply* constructs and I already wanted to start implementing them
>instead of good old for, but then a stroke of lightning came from this
>thread. Based on words from Thomas, lapply should not be used for tasks
>where order is critical. Did I get this clear enough. Additionally, I
>have read notes (I lost link, but was posted on R-help, I think) from
>Thomas on R and he mentioned that it is commonly assumed that *apply* (I
>do not remember which one of *apply*) is faster than loop, but that this
>is not true. Any additional pointers to literature?
>
>  
>