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

[Abhijit Dasgupta, PhD]

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