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