Aggregate using data.table

I'm looking for a simpler way to aggregate and calculate percentages of a numerical variable using data.table. The following code outputs the desired result, my question is if there is a better way to get the same result. I'm not really familiarized with the package, so any tips would be useful.

I'd like to have the following columns:

   second_factor_variable third_factor_variable factor_variable       porc porcentaje
1:                   HIGH                     C           > 200 0.04456544        4 %
2:                    LOW                     A        51 - 100 0.31739130       32 %
3:                    LOW                     A       101 - 200 0.68260870       68 %
4:                    LOW                     A         26 - 50 0.00000000        0 %

Where porc is the numerical percentage and porcentage would be the percentage rounded to be used as a label in a ggplot call.

library("ggplot2")
library("scales")
library("data.table")

### Generate some data
set.seed(123)
df <- data.frame(x = rnorm(10000, mean = 100, sd = 50))
df <- subset(df, x > 0)

df$factor_variable <- cut(df$x, right = TRUE, 
                          breaks = c(0, 25, 50, 100, 200, 100000),
                          labels = c("0 - 25", "26 - 50", "51 - 100", "101 - 200", "> 200")
                          )

df$second_factor_variable <- cut(df$x, right = TRUE, 
                                 breaks = c(0, 100, 100000),
                                 labels = c("LOW", "HIGH")
                                 )

df$third_factor_variable <- cut(df$x, right = TRUE, 
                                 breaks = c(0, 50, 100, 100000),
                                 labels = c("A", "B","C")
                                )

str(df)

### Aggregate
DT <- data.table(df)
dt = DT[, list(factor_variable = unique(DT$factor_variable),
              porc = as.numeric(table(factor_variable)/length(factor_variable)),
              porcentaje = paste( round( as.numeric(table(factor_variable)/length(factor_variable), 0 ) * 100 ), "%")
              ), by="second_factor_variable,third_factor_variable"]

EDIT

I've tried agstudy's solution grouping by with just one variable, and I believe it didn't work for producing the labels (porcentaje column). In the real dataset, I ended up having a similar issue and I can't spot whats wrong about this function.

grp <- function(factor_variable) {
  porc = as.numeric(table(factor_variable)/length(factor_variable))
  list(factor_variable = factor_variable[1],
       porc =porc,
       porcentaje = paste( round( porc, 0 ) * 100 , "%"))
}

DT[, grp(factor_variable) , by="second_factor_variable"]

The numerical values are correct

DT2 <- DT[DT$second_factor_variable %in% "LOW"]
table(DT2$factor_variable)/length(DT2$factor_variable)

I believe the same problems appears if i group by with 2 factor variables:

DT[, grp(factor_variable) , by="second_factor_variable,third_factor_variable"]