# [R] Help understanding loop behaviour

Rui Barradas ru|pb@rr@d@@ @end|ng |rom @@po@pt
Fri Apr 30 19:36:58 CEST 2021

```Hello,

For column J, ave/seq_along seems to be the simplest. For column I, ave
is also a good option, it avoids split/lapply.

xx\$I <- ave(xx\$NUMBER_OF_YEARS, xx\$COMPANY_NUMBER, FUN = function(x){
c(rep(1, length(x) - 1), max(length(x)))
})

xx\$J <- ave(xx\$NUMBER_OF_YEARS, xx\$COMPANY_NUMBER, FUN = seq_along)

Hope this helps,

Às 11:49 de 30/04/21, PIKAL Petr escreveu:
> Hallo,
>
> Sorry, my suggestion did not worked in your case correctly as split used
> natural factor ordering.
>
> So using Jim's data, this results in desired output.
>
> #prepare factor in original ordering
> ff <- factor(xx[,1], levels=unique(xx[,1]))
> lll <- split(xx\$COMPANY_NUMBER, ff)
> xx\$I <- unlist(lapply(lll, function(x) c(rep(1, length(x)-1),
> max(length(x)))),use.names=FALSE)
> xx\$J <- unlist(lapply(lll, function(x) 1:length(x)), use.names=FALSE)
>> xx
>     COMPANY_NUMBER NUMBER_OF_YEARS I J
> 1           70837               3 1 1
> 2           70837               3 1 2
> 3           70837               3 3 3
> 4         1000403               4 1 1
> 5         1000403               4 1 2
> 6         1000403               4 1 3
> 7         1000403               4 4 4
> 8        10029943               3 1 1
> 9        10029943               3 1 2
> 10       10029943               3 3 3
> 11       10037980               4 1 1
> 12       10037980               4 1 2
> 13       10037980               4 1 3
> 14       10037980               4 4 4
> 15       10057418               3 1 1
> 16       10057418               3 1 2
> 17       10057418               3 3 3
> 18        1009550               4 1 1
> 19        1009550               4 1 2
> 20        1009550               4 1 3
> 21        1009550               4 4 4
>
> Cheers.
> Petr
>
>> -----Original Message-----
>> From: R-help <r-help-bounces using r-project.org> On Behalf Of Jim Lemon
>> Sent: Friday, April 30, 2021 11:45 AM
>> To: e-mail ma015k3113 <ma015k3113 using blueyonder.co.uk>; r-help mailing list
>> <r-help using r-project.org>
>> Subject: Re: [R] Help understanding loop behaviour
>>
>> Hi email,
>> If you want what you described, try this:
>>
>> 0070837  3
>> 0070837  3
>> 0070837  3
>> 1000403  4
>> 1000403  4
>> 1000403  4
>> 1000403  4
>> 10029943  3
>> 10029943  3
>> 10029943  3
>> 10037980  4
>> 10037980  4
>> 10037980  4
>> 10037980  4
>> 10057418  3
>> 10057418  3
>> 10057418  3
>> 1009550  4
>> 1009550  4
>> 1009550  4
>> 1009550  4",
>> xx\$I<-NA
>> xx\$J<-NA
>> row_count<-1
>> for(row in 1:nrow(xx)) {
>>   if(row == nrow(xx) ||
>> xx\$COMPANY_NUMBER[row]==xx\$COMPANY_NUMBER[row+1]) {
>>    xx\$I[row]<-1
>>    xx\$J[row]<-row_count
>>    row_count<-row_count+1
>>   } else {
>>    xx\$I[row]<-xx\$J[row]<-xx\$NUMBER_OF_YEARS[row]
>>    row_count<-1
>>   }
>> }
>> xx
>>
>> Like Petr, I am assuming that you want company 10057418 treated the same
>> as the others. If not, let us know why. I am also adssuming that the first
> three
>> rows should _not_ have a "#" at the beginning, which means that they will
> be
>>
>> Jim
>>
>> On Fri, Apr 30, 2021 at 1:41 AM e-mail ma015k3113 via R-help <r-help using r-
>> project.org> wrote:
>>>
>>> I am trying to understand how loops in operate. I have a simple
>>> dataframe xx which is as follows
>>>
>>> COMPANY_NUMBER   NUMBER_OF_YEARS
>>>
>>> #0070837                             3
>>> #0070837                             3
>>> #0070837                             3
>>> 1000403                               4
>>> 1000403                               4
>>> 1000403                               4
>>> 1000403                               4
>>> 10029943                             3
>>> 10029943                             3
>>> 10029943                             3
>>> 10037980                             4
>>> 10037980                             4
>>> 10037980                             4
>>> 10037980                             4
>>> 10057418                             3
>>> 10057418                             3
>>>
>>> 10057418                             3
>>> 1009550                               4
>>> 1009550                               4
>>> 1009550                               4
>>> 1009550                               4
>>> The code I have written is
>>>
>>> while (i <= nrow(xx1) )
>>>
>>> {
>>>
>>> for (j in 1:xx1\$NUMBER_OF_YEARS[i])
>>> {
>>> xx1\$I[i] <- i
>>> xx1\$J[j] <- j
>>> xx1\$NUMBER_OF_YEARS_j[j] <- xx1\$NUMBER_OF_YEARS[j] } i=i +
>>> (xx1\$NUMBER_OF_YEARS[i] ) } After running the code I want my
>> dataframe
>>> to look like
>>>
>>> |COMPANY_NUMBER |NUMBER_OF_YEARS| | I| |J|
>>>
>>> |#0070837 |3| |1| |1|
>>> |#0070837 |3| |1| |2|
>>> |#0070837 |3| |3| |3|
>>> |1000403 |4| |1| |1|
>>> |1000403 |4| |1| |2|
>>> |1000403 |4| |1| |3|
>>> |1000403 |4| |4| |4|
>>> |10029943 |3| |1| |1|
>>> |10029943 |3| |1| |2|
>>> |10029943 |3| |3| |3|
>>> |10037980 |4| |1| |1|
>>> |10037980 |4| |1| |2|
>>> |10037980 |4| |1| |3|
>>> |10037980 |4| |4| |4|
>>> |10057418 |3| |1| |1|
>>> |10057418 |3| |1| |1|
>>> |10057418 |3| |1| |1|
>>> |1009550 |4| |1| |1|
>>> |1009550 |4| |1| |2|
>>> |1009550 |4| |1| |3|
>>> |1009550 |4| |4| |4|
>>>
>>>
>>> I get the correct value of I but in the wrong row but the vaule of J
>>> is correct in the first iteration and then it goes to 1
>>>
>>> Any help will be greatly appreciated
>>>          [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
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>>> and provide commented, minimal, self-contained, reproducible code.
>>
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