Fill nth columns in a dataframe - r

Question

I have this data frame:
df <- data.frame(A=c("a","b","c","d","e","f","g","h","i"),
B=c("1","1","1","2","2","2","3","3","3"),
C=c(0.1,0.2,0.4,0.1,0.5,0.7,0.1,0.2,0.5))
> df
A B C
1 a 1 0.1
2 b 1 0.2
3 c 1 0.4
4 d 2 0.1
5 e 2 0.5
6 f 2 0.7
7 g 3 0.1
8 h 3 0.2
9 i 3 0.5
I would like to add 1000 further columns and fill this columns with the values generated by :
transform(df, D=ave(C, B, FUN=function(b) sample(b, replace=TRUE)))
I've tried with a for loop but it does not work:
for (i in 4:1000){
df[, 4:1000] <- NA
df[,i] = transform(df, D=ave(C, B, FUN=function(b) sample(b, replace=TRUE)))
}

Answer 1

For efficiency reasons, I suggest running sample only once for each group. This can be achieved with this:
sample2 <- function(x, size)
{
if(length(x)==1) rep(x, size) else sample(x, size, replace=TRUE)
}
new_df <- do.call(rbind, by(df, df$B,
function(d) cbind(d, matrix(sample2(d$C, length(d$C)*1000),
ncol=1000))))
Notes:
I've created sample2 in case there is a group with only one C value. Check ?sample to see what I mean.
The names of the columns will be numbers, from 1 to 1000. This can be changed as in the answer by #agstudy.
The row names are also changed. "Fixing" them is similar, just use row.names instead of col.names.

Answer 2

Using replicate for example:
cbind(df,replicate(1000,ave(df$C, df$B,
FUN=function(b) sample(b, replace=TRUE))))
To add 4 columns for example:
cbind(df,replicate(4,ave(df$C, df$B,
FUN=function(b) sample(b, replace=TRUE))))
A B C 1 2 3 4
1 a 1 0.1 0.2 0.2 0.1 0.2
2 b 1 0.2 0.4 0.2 0.4 0.4
3 c 1 0.4 0.1 0.1 0.1 0.1
4 d 2 0.1 0.1 0.5 0.5 0.1
5 e 2 0.5 0.7 0.1 0.5 0.1
6 f 2 0.7 0.1 0.7 0.7 0.7
7 g 3 0.1 0.2 0.5 0.2 0.2
8 h 3 0.2 0.2 0.1 0.2 0.1
9 i 3 0.5 0.5 0.5 0.1 0.5
Maybe you need to rename columns by something like :
gsub('([0-9]+)','D\\1',colnames(res))
1] "A" "B" "C" "D1" "D2" "D3" "D4"