conditional grouping of variables: ave or tapply or by or???

df$v4 <- ave(1:nrow(df), df$v1, FUN = function(i) with(df[i,], v2[!v3]))
df

# 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]))

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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