[R] How to remove rows based on frequency of factor and then difference date scores

[Chris Beeley]

Many thanks to you both. I have now filed away for future reference the 2 factor tapply as well as the extremely useful looking plyr library. And the code worked beautifully :-)



On 24 Aug 2010, at 19:47, "Abhijit Dasgupta, PhD" <aikidasgupta at gmail.com> wrote:

> The paste-y argument is my usual trick in these situations. I forget that tapply can take multiple ordering arguments :)
> 
> Abhijit
> 
> On 08/24/2010 02:17 PM, David Winsemius wrote:
>> 
>> On Aug 24, 2010, at 1:59 PM, Abhijit Dasgupta, PhD wrote:
>> 
>>> The only problem with this is that Chris's unique individuals are a combination of Type and ID, as I understand it. So Type=A, ID=1 is a different individual from Type=B,ID=1. So we need to create a unique identifier per person, simplistically by uniqueID=paste(Type, ID, sep=''). Then, using this new identifier, everything follows.
>> 
>> I see your point. I agree that a tapply method should present both factors in the indices argument.
>> 
>> > new.df <- txt.df[ -which( txt.df$nn <=1), ]
>> > new.df <- new.df[ with(new.df, order(Type, ID) ), ]  # and possibly needs to be ordered?
>> > new.df$diffdays <- unlist( tapply(new.df$dt2, list(new.df$ID, new.df$Type), function(x) x[1] -x) )
>> > new.df
>>  Type ID       Date Value        dt2 nn diffdays
>> 1    A  1 16/09/2020     8 2020-09-16  3        0
>> 2    A  1 23/09/2010     9 2010-09-23  3     3646
>> 4    B  1  13/5/2010     6 2010-05-13  3        0
>> 
>> But do not agree that you need, in this case at least, to create a paste()-y index. Agreed, however, such a construction can be useful in other situations.
>> 
> 
> 
> -- 
> 
> Abhijit Dasgupta, PhD
> Director and Principal Statistician
> ARAASTAT
> Ph: 301.385.3067
> E: adasgupta at araastat.com
> W: http://www.araastat.com
>