[R] conditional grouping of variables: ave or tapply or by or???

[Gabor Grothendieck]

Try this:

> df$v4 <- ave(1:nrow(df), df$v1, FUN = function(i) with(df[i,], v2[!v3]))
> df
  v1 v2 v3 v4
1 10  7  0  7
2 10  5  1  7
3 10  7  2  7
4 11  9  0  9
5 11  7  2  9

> # If as is the case here that 0 is always the first in each v1 group
> # then it can be simplified further to:

> df$v4 <- with(df, ave(v2, v1, FUN = function(x) x[1]))


On Thu, Apr 23, 2009 at 6:11 PM, ozan bakis <ozanbakis at gmail.com> wrote:
> Dear R Users,
> I have the following data frame:
>
> v1 <- c(rep(10,3),rep(11,2))
> v2 <- sample(5:10, 5, replace = T)
> v3 <- c(0,1,2,0,2)
> df <- data.frame(v1,v2,v3)
>> df
>  v1 v2 v3
> 1 10  9  0
> 2 10  5  1
> 3 10  6  2
> 4 11  7  0
> 5 11  5  2
>
> I want to add a new column v4 such that its values are equal to the value
> of v2 conditional on v3=0 for each subgroup of v1. In the above example,
> the final result should be like
>
> df$v4 <- c(9,9,9,7,7)
>> df
>  v1 v2 v3 v4
> 1 10  9  0  9
> 2 10  5  1  9
> 3 10  6  2  9
> 4 11  7  0  7
> 5 11  5  2  7
>
>
> I tried the following commands without success.
>
> df$v4 <- ave(df$v2, df$v1, FUN=function(x) x[df$v3==0])
> tapply(df$v2, df$v1, FUN=function(x) x[df$v3==0])
> by(df$v2, df$v1, FUN=function(x) x[df$v3==0])
>
> Any help? Thanks in advance!
> Ozan
>
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>
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