Hi, I am having some problem creating a for loop which will go systematically through each group in the data frame. I want a loop that adds a new column with values from the sum formula within the loop.

Consider the following structure:

```
df1 <- data.frame(N = c(1,2,3,4,5,6),
name = c("a","b","c","d","e","f"),
ID =c(1,1,1,2,2,2),
sales = c(100, 250, 300, 50, 600, 390),
t = c(0.1,0.3,0.4,0.05,0.15,0.2),
n=c(1,2,3,1,2,3),
correct_result = c(-221.4,-27.8,69.1,-143.71,-19.11,43.19))
```

Each name and corresponding values have one unique ID code.

The formula I am trying to calculate implies that for a given name, say, a, (in the loop i would be=1)

I want to take the sum of sales of all other related names (by their ID) and divide by 1-t for the respective names. The formula itself worked when I only have one ID in the dataset (i.e., in this case 3 rows).

However, my loop is unable to distinguish between the group ID's and thus takes the sum of all values except i. Ideal output is that it takes the sum of all sales which has the same ID (and only those) except i.

```
df1$output <- 0
for(i in 1:nrow(df1)){
if(df1$ID[i]== df1$ID[i]){
for(k in df1$n){
k = df1$n
df1$output[i] <- sum((df1$sales[k!=i]/(1-df1$t[k!=i]))*(df1$t[i]-df1$t[k!=i]))
}}}
```

I also tried to subset within the loop, this gave me the correct result, but only returned ID=2:

```
for(i in 1:nrow(df1)){
p <- df1[df1$ID[i] == df1$ID,]
for(i in 1:nrow(p)){
if(p$ID[i] == p$ID[i]){
for(k in p$n){
k = p$n
p$d1[i] <- sum((p$sales[k!=i]/(1-p$t[k!=i]))*(p$t[i]-p$t[k!=i]))
}}}}
```

Any help is appreciated,

Thanks!