###############################################################################
# FAST VERSION — identical results, fully vectorised
###############################################################################
profvis({
  
  ## --- Fix 1: vectorised arithmetic (no loop, no regrowth) ------------------
  doubled <- df$value * 2
  
  ## --- Fix 2: operate on the column directly (no matrix coercion) -----------
  df$normalized <- df$value / 100
  
  ## --- Fix 3: one grouped pass at C level -----------------------------------
  group_means <- tapply(df$value, df$group, mean)
  
})

###############################################################################
# Same three fixes with other approach:
#

##############################################################################
library(dplyr)
profvis({
  group_means <- df |> group_by(group) |> summarise(m = mean(value))
})

system.time({
  group_means <- df |> group_by(group) |> summarise(m = mean(value))
})

#
library(data.table)
profvis({
  dt <- as.data.table(df)
  group_means <- dt[, .(m = mean(value)), by = group]
})

system.time({
  dt <- as.data.table(df)
  group_means <- dt[, .(m = mean(value)), by = group]
})