counting occurrences in column and create variable in R

You were almost there! rle will work very nicely, you just need to sort your table on ID before computing rle:

CT <- data.frame( value = runif(10) , id = sample(5,10,repl=T) )

#  sort on ID when calculating rle
Count <- rle( sort( CT$id ) )

#  match values
CT$Count <- Count[[1]][ match( CT$id , Count[[2]] ) ]
CT
#       value id Count
#1  0.94282600  1     4
#2  0.12170165  2     2
#3  0.04143461  1     4
#4  0.76334609  3     2
#5  0.87320740  4     1
#6  0.89766749  1     4
#7  0.16539820  1     4
#8  0.98521044  5     1
#9  0.70609853  3     2
#10 0.75134208  2     2

data.table usually provides the quickest way

set.seed(3)
library(data.table)
ct <- data.table(id=sample(1:10,15,replace=TRUE),item=round(rnorm(15),3))
st <- ct[,countid:=.N,by=id]
 id   item countid
 1:  2  0.953       2
 2:  9  0.535       2
 3:  4 -0.584       2
 4:  4 -2.161       2
 5:  7 -1.320       3
 6:  7  0.810       3
 7:  2  1.342       2
 8:  3  0.693       1
 9:  6 -0.323       5
10:  7 -0.117       3
11:  6 -0.423       5
12:  6 -0.835       5
13:  6 -0.815       5
14:  6  0.794       5
15:  9  0.178       2

If you don't feel the need to use base R, plyr makes this task easy:

> set.seed(3)
> library(plyr)
> ct <- data.frame(id=sample(1:10,15,replace=TRUE),item=round(rnorm(15),3))
> ct <- ddply(ct,.(id),transform,idcount=length(id))
> head(ct)
  id   item idcount
1  2  0.953       2
2  2  1.342       2
3  3  0.693       1
4  4 -0.584       2
5  4 -2.161       2
6  6 -0.323       5