This is a snippet of the dataset I am currently working on:

> sample
    name sex count
1  Maria   f    97
2 Thomas   m    12
3  Maria   m     5
4  Maria   f    97
5 Thomas   m     8
6  Maria   m     4

I want to sum up the counts grouped by name and sex to finally get this data.frame:

> result
    Maria Thomas
f   194      0
m     9     20

I wrote a simple loop to iterate over the rows and sum up the counts:

result <- matrix(0, nrow=2, ncol=2)
colnames(result) <- unique(sample$name)
rownames(result) <- unique(sample$sex)

for (i in 1:nrow(sample)) {
    sex <- as.character(sample[i,"sex"])
    name <- sample[i,"name"]
    count <- sample[i,"count"]

    result[sex, name] <- result[sex, name] + count
}

Is it suitable to do it this way? Are there any other ways to do it in a more elegant / shorter fashion?

This is a snippet of the dataset I am currently working on:

> sample
    name sex count
1  Maria   f    97
2 Thomas   m    12
3  Maria   m     5
4  Maria   f    97
5 Thomas   m     8
6  Maria   m     4

I want to sum up the counts grouped by name and sex to finally get this data.frame:

> result
    Maria Thomas
f   194      0
m     9     20

I wrote a simple loop to iterate over the rows and sum up the counts:

result <- matrix(0, nrow=2, ncol=2)
colnames(result) <- unique(sample$name)
rownames(result) <- unique(sample$sex)

for (i in 1:nrow(sample)) {
    sex <- as.character(sample[i,"sex"])
    name <- sample[i,"name"]
    count <- sample[i,"count"]

    result[sex, name] <- result[sex, name] + count
}

Is it suitable to do it this way? Are there any other ways to do it in a more elegant / shorter fashion?

Edit:

I already tried it with aggregate, but the output is in a different format:

> aggregate(sample$count,by=list(sample$name,sample$sex),sum)
  Group.1 Group.2   x
1   Maria       m   9
2  Thomas       m  20
3   Maria       w 194