Create table with means and frequencies in R

Question

I have a dataset like this:

structure(list(age = c(23, 25, 60, 12), sex = c(0, 1, 0, 1), 
    bmi = c(25, 30, 23, 24), disease = c(0, 1, 0, 1)), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -4L))

I want to calculate the mean(SD) or frequency(percentage) of each variable divided by sex (men <- sex=1, women <- sex=0). Afterwards, I want to report the results in a table.

I want that R automatically chooses between mean±SD or frequency(percentage) depending on type of data. For instance, age is continous (mean), bmi is continous (mean) while disease is binary (0 or 1, where 1=there is disease so I want the frequency to be the n° of patients with disease = 1)

This is an example of the final result that I want to have:

Answer 1

dt <- structure(list(age = c(23, 25, 60, 12), sex = c(0, 1, 0, 1), 
               bmi = c(25, 30, 23, 24), disease = c(0, 1, 0, 1)), class = c("tbl_df", 
                                                                            "tbl", "data.frame"), row.names = c(NA, -4L))

library(data.table)

setDT(dt) # make it a data.table

# prepare your data
dt[, sex := factor(sex, labels = c("Women", "Men"))]
dt[, disease := as.logical(disease)]


dcast(melt(dt[, lapply(.SD, \(x) {
  switch(class(x),
         "numeric" = sprintf("%.0f ± %.0f", mean(x), sd(x)),
         "logical" = sprintf("%.0f (%.0f %%)", sum(x), 100 * sum(x) / .N)
  )
}), sex], id.vars = "sex"), variable ~ sex)

#    variable    Women         Men
# 1:      age  42 ± 26      18 ± 9
# 2:      bmi   24 ± 1      27 ± 4
# 3:  disease  0 (0 %)   2 (100 %)