Table Function to output descriptive statistics

tbl_steele.r

# try to do table function in base R

tbl_steele <- function(data, var, ...){
  require(descr)
  require(htmlTable)
  
  levels_logic <- lapply(data[, var], function(x) levels(x))
  levels_logic1 <- lapply(levels_logic, function(x) is.null(x)) # combine these statements in the future
  if(sum(unlist(levels_logic1)) < length(var)){
    cat("Are all of your variables properly labelled?\n")
    cat("When your variables are properly labelled, the table will be easier to read.")
  }
  a <- lapply(data[, var], function(x) freq(x, plot = F))
  b <- do.call(rbind, a)
  remove_total <- "Total"
  d <- b[!rownames(b) %in% remove_total, ]
  e <- suppressWarnings(data.frame(d))
  e_percent <- sprintf("%.1f", e$Percent)
  f <- cbind(paste0(e$Frequency, " ", "(", e_percent, ")"))
  g <- lapply(mtcars[, var], function(x) length(unique(x)))
  g1 <- do.call(rbind, g)
  h <- htmlTable(f, rnames = rownames(d), rgroup = var, n.rgroup = c(g1), header = "Count (%)", ...)
  return(h)
}

# run the function
# use test data set mtcars
# tbl_steele(data = mtcars, var = c("vs", "am"), caption = "Descriptive Statistics Table")

# in order to test the levels/labels, use the following
# mtcars$vs <- factor(mtcars$vs, levels = c(0, 1), labels = c("0. Zero", "1. One"))
# you'll see that the levels for am are 0/1, hopefully prompting the user to label their factor variables