You should show what you tried with aggregate and tapply.
You could use ave():
> wm <- as.logical(ave(df$T, df$ID, FUN=function(x)x==min(x)))
> df$x_new <- df$x
> df$x_new[wm] <- 0
> df
ID T x x_new
1 1 1 1 0
2 1 2 1 1
3 1 3 1 1
4 2 1 1 0
5 2 4 1 1
6 3 3 1 0
7 3 5 1 1
8 3 6 1 1
9 3 8 1 1
(The as.logical is there because ave() coerces the logical output of
FUN to the type of df$T, numeric, and we need to convert it back to
logical.)
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
> Behalf
> Of Carlos Nasher
> Sent: Tuesday, December 18, 2012 6:10 AM
> To: r-help@r-project.org
> Subject: [R] Set a zero at minimum row by group
>
> Dear R Helpers,
>
> I'm struggling with a data preparation problem. I feel that it is a quite
> easy task but I don't get it done. I hope you can help me with that.
>
> I have a data frame looking like this:
>
> ID <- c(1,1,1,2,2,3,3,3,3)
> T <- c(1,2,3,1,4,3,5,6,8)
> x <- rep(1,9)
> df <- data.frame(ID,T,x)
>
> >df
> ID T x
> 1 1 1
> 1 2 1
> 1 3 1
> 2 1 1
> 2 4 1
> 3 3 1
> 3 5 1
> 3 6 1
> 3 8 1
>
> I want to manipulate the x column in a way that for each customer (ID) at
> the minimum of T the x value is set to zero. The result should look like
> this:
>
> ID T x x_new
> 1 1 1 0
> 1 2 1 1
> 1 3 1 1
> 2 1 1 0
> 2 4 1 1
> 3 3 1 0
> 3 5 1 1
> 3 6 1 1
> 3 8 1 1
>
> I already tried the aggregate() and apply() function, but I don't get the
> result I'm looking for. I would glad if you could help me out.
>
> Best regards,
> Carlos
>
> [[alternative HTML version deleted]]
>
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