numeric summary table

quick_summary <- function(df, vars, group = NULL){
  
  group_is_null <- is.null(group)
  
  coll <- checkmate::makeAssertCollection()
  
  checkmate::assert_data_frame(x = df,
                               add = coll)
  
  checkmate::assert_character(x = vars,
                              add = coll)
  
  checkmate::assert_character(x = group,
                              null.ok = TRUE,
                              add = coll)
  
  checkmate::assert_subset(x = vars,
                           choices = names(df),
                           add = coll)
  
  if (!group_is_null){
    checkmate::assert_subset(x = group,
                             choices = names(df),
                             add = coll)
  }
  
  if (any(vars %in% group)){
    in_both <- vars[vars %in% group]
    coll$push(paste0("The following variables names are in both 'vars' and 'group': ",
                     paste0(in_both, collapse = ", ")))
  }
  
  checkmate::reportAssertions(coll)
  
  df <- df[c(vars, group)]
  
  checkmate::assert_data_frame(x = df[vars],
                               types = "numeric",
                               .var.name = "vars",
                               add = coll)
  
  checkmate::reportAssertions(coll)
  
  if (!group_is_null){
    group_order <- 
      lapply(df[group],
             function(x) if (is.factor(x)) levels(x) else unique(x))
    group_order <- stats::setNames(group_order, group)
  }

  ncount <- function(x, na.rm = TRUE) sum(!is.na(x))

  df <- tidyr::gather(data = df,
                      key = !!"variable",
                      value = !!"value",
                      dplyr::one_of(vars))
  
    df <- dplyr::group_by_at(.tbl = df,
                             .vars = c("variable", group)) 
  
  df <- dplyr::summarise_at(.tbl = df,
                            .vars = "value",
                            .fun = dplyr::funs(
                              n = ncount,
                              mean = mean,
                              sd = sd,
                              min = min,
                              median = median,
                              max = max
                            ), 
                            na.rm = TRUE)
  
  df$variable <- factor(df$variable, levels = vars)
  
  if (!group_is_null){
    df[group] <- mapply(factor,
                        x = df[group], 
                        levels = group_order)
  }
  
  dplyr::arrange_at(.tbl = df, "variable")
}