how can I normalize data frame values by the sum (get percents)

Question

I have the following data frame: ``` > str(df) 'data.frame': 52 obs. of 3 variables: $ n : int 10 20 64 108 128 144 256 320 404 512 ... $ step : Factor w/ 4 levels "Step1","Step2",..: 1 1 1 1 1 1 1 1 1 1 ... $ value: num 0.00178 0.000956 0.001613 0.001998 0.002975 ... ``` Now I would like to normalize/divide the `df$value` by the sum of values that belong to the same n i.e. so I can get the percentages. This doesn't work but shows what I would like to achieve. Here I precompute into dfa the sums of the values that belong to the same n and try to divide on the original `df$value` by the aggregated total `dfa$value` with matching `n`: ``` dfa <- aggregate(x=df$value, by=list(df$n), FUN=sum) names(dfa)[names(dfa)=="Group.1"] <- "n" names(dfa)[names(dfa)=="x"] <- "value" df$value <- df$value / dfa[dfa$n==df$n,][[1]] ```

Accepted Answer

I think the following works, using package `data.table`.

```
df <- data.table(df)
df[,value2 := value/sum(value),by=n]
```

how can I normalize data frame values by the sum (get percents)

Solution

Problem