R help - Apr 2009 - conditional grouping of variables: ave or tapply or by or???

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

	[[alternative HTML version deleted]]

On Thu, Apr 23, 2009 at 5:11 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!
Here's one approach with the plyr package, http://had.co.nz/plyr

library(plyr)
ddply(df, .(v1), transform, v4 = v2[v3 == 0])

Hadley


-- 
http://had.co.nz/

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
>
> ? ? ? ?[[alternative HTML version deleted]]
>
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