analyte_table_illiana.R

library(tidyverse)

#fake excedences data
excedences <- tribble(
  ~analyte, ~threshold,
  "x", 0,
  "y", 1
)
excedences

#fake analyte data
data_long <- 
  tibble(type = rep(c("A", "B"), 5), x = rnorm(10), y = rnorm(10)) |> 
  pivot_longer(c(x,y), names_to = "analyte") 

data_long
excedences

full_join(data_long, excedences) |> 
  mutate(exceded = value > threshold) |> 
  group_by(type, analyte) |> 
  summarize(
    mean = mean(value),
    excecence_count = sum(exceded),
    excedence_percent = sum(exceded)/n()*100
  )