R/50_longplot.R

In brinton: A Graphical EDA Tool

#' Displays a longplot in a html file.
#'
#' A longplot is a range of suitable graphics that represent the relationship
#' within the values of one, or a limited number, of variables in a dataset. Each
#' graphic relates the values of all the selected variables and eventually the
#' row number in which they appear.
#'
#' In order to present the range of graphics, the user must define a dataset and
#' select at least one variable whitin it. Future work will include graphics that
#' can combine up to three variables.
#'
#' @seealso Specimens of grphics for \href{https://sciencegraph.github.io/brinton/articles/specimen.html}{univariate}
#' and \href{https://sciencegraph.github.io/brinton/articles/specimen2.html}{bivariate} data.
#'
#' @param data Data.frame. Default dataset to use for plot. If not already a
#' data.frame, it should be first coerced to by [as.data.frame()].
#' @param vars Character. A specific variable within the dataset.
#' @param label Logical. If `TRUE` the output includes labels that show the names
#' of the graphics that are being displayed.
#' @param dir Directory in which the files are stored.
#'
#' @return Cause the side-effect of creating and displaying a temporary html file
#' that includes a range of graphics suitable for this particular combination of
#' variables.
#' @export
#'
#' @examples
#' if (interactive()) {
#' longplot(esoph, "tobgp")
#' }
longplot <- function(data,
                     vars,
                     label = TRUE,
                     dir = tempdir()
                     )
{

# check markdown ----------------------------------------------------------


  if (rmarkdown::pandoc_available("1.12.3") == FALSE) {print(warning_pandoc)}
  else if (rmarkdown::pandoc_available("1.12.3") == TRUE) {

# aux functions -----------------------------------------------------------

    # add_plots <- function(a, b) {
    #   write(
    #     paste0(
    #       "gridExtra::grid.arrange(",
    #       paste0(a, 1:b, collapse = ", "),
    #       ", ncol=5)"
    #     ),
    #     file.path(dir, "brinton_outcomes", "longplot.R"),
    #     append = TRUE
    #   )
    # }

    add_plots_patchwork <- function(a, b) {
      write(
        paste0(paste0(a, 1:b, collapse = " + "), " + patchwork::plot_layout(widths = rep(1, 5))"),
        file.path(dir, "brinton_outcomes", "longplot.R"),
        append = TRUE
      )
    }

    add_plots_patchwork_guides <- function(a, b) {
      write(
        paste0(paste0(a, 1:b, collapse = " + "), " + patchwork::plot_spacer() + patchwork::plot_spacer() + patchwork::plot_layout(guides = 'collect', ncol = 5) & theme(legend.position = 'bottom', legend.key.size = unit(0.5,'line'), legend.title = element_blank()) & guides(position = 'bottom', fill = guide_legend(nrow = 1), color = guide_legend(nrow = 1))"),
        file.path(dir, "brinton_outcomes", "longplot.R"),
        append = TRUE
      )
    }

    add_float_patchwork <- function(a, b, w, h, n) {
      write(
        paste0(paste0(a, 1:b, collapse = " + "), " + patchwork::plot_layout(widths = panel.", w,
               ", heights = panel.", h, ", ncol = ", n, ", )"),
        file.path(dir, "brinton_outcomes", "longplot.R"),
        append = TRUE
      )
    }

    add_label <- function(a, b) {
      char_types <-
        paste0(a, " = c('", paste0(b, collapse = "', '"), "')")
      write(
        paste0('cat("', char_types, '")'),
        file.path(dir, "brinton_outcomes", "longplot.R"),
        append = TRUE
      )
    }

# check class -------------------------------------------------------------


  if(is.data.frame(data) == FALSE) {
    stop("I am so sorry, but this function only works with a data.frame input!\n",
          "You have provided an object of class ", class(data))
  }
  if(tibble::is_tibble(data) == TRUE) {
    # stop(warning_tibble)
    data <- as.data.frame(data)
  }
  if(sum(as.vector(sapply(data, is.list) == TRUE)) > 0) {
    data <- data[sapply(data, is.list) == F]
  }

  data_list <- lapply(data, FUN=remove_attr)
  data <- as.data.frame(data_list)

  string      <- " argument expects a character vector"
  if(is.character(vars)  == FALSE) {
    stop(paste0("The 'vars'",  string))
  }

# check vars --------------------------------------------------------------

  if(length(vars) > 2) {
    stop("Only 1 and 2 variables combinations have been considered.")
  } else {
  if (length(vars) == 1 & (
    is.logical(unlist(data[, vars])) == TRUE |
    is.factor(unlist(data[, vars])) == TRUE |
    is.ordered(unlist(data[, vars])) == TRUE |
    is.character(unlist(data[, vars])) == TRUE)
  ) {long <- length(unique(unlist(data[, vars])))/6 + 0.7}
  else if (length(vars) == 1 & (
    is.numeric(unlist(data[, vars])) == TRUE |
    lubridate::is.instant(unlist(data[, vars])) == TRUE)
  ) {long <- 2}
  else if (length(vars) == 2 & (
    (lubridate::is.instant(unlist(data[, vars[1]])) == TRUE  &
     lubridate::is.instant(unlist(data[, vars[2]])) == TRUE) |
    (is.numeric(unlist(data[, vars[1]])) == TRUE  &
     lubridate::is.instant(unlist(data[, vars[2]])) == TRUE) |
    (lubridate::is.instant(unlist(data[, vars[1]])) == TRUE  &
     is.numeric(unlist(data[, vars[2]])) == TRUE))
  ) {long <- 2}
  else if (length(vars) == 2 &
           is.numeric(unlist(data[, vars[1]])) == TRUE &
           is.numeric(unlist(data[, vars[2]])) == TRUE
  ) {long <- 2}
  else if (length(vars) == 2 & ((
    is.numeric(unlist(data[, vars[1]])) == TRUE &
    is.factor(unlist(data[, vars[2]])) == TRUE) |
    (
      is.numeric(unlist(data[, vars[2]])) == TRUE &
      is.factor(unlist(data[, vars[1]])) == TRUE))
  ) {long <- length(unlist(unique(data[, vars][which(sapply(data[, vars], is.factor))])))/4 + 0.5}
  else if (length(vars) == 2 &
           is.factor(unlist(data[, vars[1]])) == TRUE &
           is.factor(unlist(data[, vars[2]])) == TRUE
  ) {wide <- length(unique(unlist(data[, vars[2]]))) / 5
    long  <- length(unique(unlist(data[, vars[2]]))) / 5
    longt <- length(unique(unlist(data[, vars[1]]))) / 5}
    else{stop("Only variables of the following classes have been considerated:
              logical, Date, POSIXct, POSIXlt, numeric, factor, ord.factor and character. ")}



# setup -------------------------------------------------------------------


  my_env <- new.env()
  ncol <- 5
  dir.create(file.path(dir, "brinton_outcomes", fsep = .Platform$file.sep), showWarnings = FALSE)
  writeLines(output_long, file.path(dir, "brinton_outcomes", "longplot.R"))
  write(paste0("cat('Graphics from the ",
               deparse(substitute(vars)),
               " variable(s) of the ",
               sys.call()[2],
               " dataframe')"),
        file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)

# 1var --------------------------------------------------------------------


# datetime ----------------------------------------------------------------


  if (length(vars) == 1 & lubridate::is.instant(unlist(data[, vars])) == TRUE) {
    write(paste0("#+ datetime, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('line graph',
                'stepped line graph')
    dt11 <- pp_1DD_linegraph(data, colnames(data[vars]), pp_size = 1/ncol)
    dt12 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_trans = 'step')
    add_plots_patchwork("dt1", 2)
    if (label == TRUE) {add_label("dtt", stripe)}
    stripe <- c('point graph',
                'point-to-point graph')
    dt21 <- pp_1DD_pointgraph(data, colnames(data[vars]), pp_size = 1/ncol)
    dt22 <- pp_1DD_linegraph(data, colnames(data[vars]), pp_size = 1/ncol, pp_points = TRUE)
    add_plots_patchwork("dt2", 2)
    if (label == TRUE) {add_label("dtt", stripe)}
    stripe <- c('binned heatmap',
                'bw binned heatmap',
                'color binned heatmap')
    dt31 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    dt32 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    dt33 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("dt3", 3)
    if (label == TRUE) {add_label("dtt", stripe)}
    stripe <- c('bw heatmap', 'color heatmap')
    p151 <- pp_1DD_raster(data, colnames(data[vars]), 'yx', 'bw')
    p152 <- pp_1DD_raster(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("p15", 2)
    if (label == TRUE) {add_label("dtt", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))}

# logical -----------------------------------------------------------------


    else if (length(vars) == 1 & is.logical(unlist(data[, vars])) == TRUE) {
    write(paste0("#+ logical, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('line graph',
                'point graph',
                'point-to-point graph',
                'tile plot',
                'linerange graph')
    lg11 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    lg12 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    lg13 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    lg14 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    lg15 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("lg1", 5)
    if (label == TRUE) {add_label("lgc", stripe)}
    stripe <- c('binned heatmap',
                'bw binned heatmap',
                'color binned heatmap')
    lg21 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    lg22 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    lg23 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("lg2", 3)
    if (label == TRUE) {add_label("lgc", stripe)}
    stripe <- c('bar graph',
                'bw bar graph',
                'color bar graph')
    lg31 <- pp_bargraph(data, colnames(data[vars]), 'black')
    lg32 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    lg33 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("lg3", 3)
    if (label == TRUE) {add_label("lgc", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))}

# ordered -----------------------------------------------------------------


    else if (length(vars) == 1 & is.ordered(unlist(data[, vars])) == TRUE) {
    # classes <- data[,vars]
    # data[,vars] <- ifelse(nchar(as.vector(data[,vars])) > 10,
    #                       paste0(substring(as.vector(data[,vars]), 1, 8), "..."), as.vector(data[,vars]))
    # data[,vars] <- classes
    write(paste0("#+ ordered, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('line graph',
                'point graph',
                'point-to-point graph',
                'tile plot',
                'linerange graph')
    of11 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    of12 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    of13 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    of14 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    of15 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("of1", 5)
    if (label == TRUE) {add_label("ord", stripe)}
    stripe <- c('binned heatmap',
                'bw binned heatmap',
                'color binned heatmap')
    of21 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    of22 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    of23 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("of2", 3)
    if (label == TRUE) {add_label("ord", stripe)}
    stripe <- c('bar graph',
                'bw bar graph',
                'color bar graph')
    of31 <- pp_bargraph(data, colnames(data[vars]), 'black')
    of32 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    of33 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("of3", 3)
    if (label == TRUE) {add_label("ord", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))}

# factor ------------------------------------------------------------------


    else if (length(vars) == 1 & is.factor(unlist(data[, vars])) == TRUE & is.ordered(unlist(data[, vars])) == FALSE) {
    # classes <- data[,vars]
    # data[,vars] <- ifelse(nchar(as.vector(data[,vars])) > 10, paste0(substring(as.vector(data[,vars]), 1, 8), "..."), as.vector(data[,vars]))
    # data[,vars] <- classes
    write(paste0("#+ factor, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    data[[vars]] <- factor(data[[vars]], levels = unique(data[[vars]]))
    stripe <- c('line graph',
                'point graph',
                'point-to-point graph',
                'tile plot',
                'linerange graph')
    ft11 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    ft12 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    ft13 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    ft14 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    ft15 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("ft1", 5)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- forcats::fct_infreq(data[[vars]], ordered = TRUE)
    stripe <- c('freq. reordered line graph',
                'freq. reordered point graph',
                'freq. reordered point-to-point graph',
                'freq. reordered tile plot',
                'freq. reordered linerange graph')
    ft21 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    ft22 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    ft23 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    ft24 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    ft25 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("ft2", 5)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- as.character(data[[vars]])
    stripe <- c('alphab. reordered line graph',
                'alphab. reordered point graph',
                'alphab. reordered point-to-point graph',
                'alphab. reordered tile plot',
                'alphab. reordered linerange graph')
    ft31 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    ft32 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    ft33 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    ft34 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    ft35 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("ft3", 5)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- factor(data[[vars]], levels = unique(data[[vars]]))
    stripe <- c('binned heatmap',
                'bw binned heatmap',
                'color binned heatmap')
    ft41 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    ft42 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    ft43 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("ft4", 3)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- forcats::fct_infreq(data[[vars]], ordered = TRUE)
    stripe <- c('freq. reordered binned heatmap',
                'bw freq. reordered binned heatmap',
                'color freq. reordered binned heatmap')
    ft51 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    ft52 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    ft53 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("ft5", 3)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- as.character(data[[vars]])
    stripe <- c('alphab. reordered binned heatmap',
                'bw alphab. reordered binned heatmap',
                'color alphab. reordered binned heatmap')
    ft61 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    ft62 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    ft63 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("ft6", 3)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- factor(data[[vars]], levels = unique(data[[vars]]))
    stripe <- c('bar graph',
                'bw bar graph',
                'color bar graph')
    ft71 <- pp_bargraph(data, colnames(data[vars]), 'black')
    ft72 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    ft73 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("ft7", 3)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- forcats::fct_infreq(data[[vars]], ordered = TRUE)
    stripe <- c('freq. reordered bar graph',
                'bw freq. reordered bar graph',
                'color freq. reordered bar graph')
    ft81 <- pp_bargraph(data, colnames(data[vars]), 'black')
    ft82 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    ft83 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("ft8", 3)
    if (label == TRUE) {add_label("fac", stripe)}
    data[[vars]] <- as.character(data[[vars]])
    stripe <- c('alphab. reordered bar graph',
                'bw alphab. reordered bar graph',
                'color alphab. reordered bar graph')
    ft91 <- pp_bargraph(data, colnames(data[vars]), 'black')
    ft92 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    ft93 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("ft9", 3)
    if (label == TRUE) {add_label("fac", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))}

# character ---------------------------------------------------------------


    else if (length(vars) == 1 & is.character(unlist(data[, vars])) == TRUE ) {
    # data[,vars] <- ifelse(nchar(as.vector(data[,vars])) > 10, paste0(substring(as.vector(data[,vars]), 1, 8), "..."), as.vector(data[,vars]))
    write(paste0("#+ character, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    data[[vars]] <- factor(data[[vars]], levels = unique(data[[vars]]))
    stripe <- c('line graph',
                'point graph',
                'point-to-point graph',
                'tile plot',
                'linerange graph')
    p011 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    p012 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    p013 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    p014 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    p015 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("p01", 5)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- forcats::fct_infreq(data[[vars]], ordered = TRUE)
    stripe <- c('freq. reordered line graph',
                'freq. reordered point graph',
                'freq. reordered point-to-point graph',
                'freq. reordered tile plot',
                'freq. reordered linerange graph')
    p021 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    p022 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    p023 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    p024 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    p025 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("p02", 5)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- as.character(data[[vars]])
    stripe <- c('alphab. reordered line graph',
                'alphab. reordered point graph',
                'alphab. reordered point-to-point graph',
                'alphab. reordered tile plot',
                'alphab. reordered linerange graph')
    p031 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    p032 <- pp_1DD_pointgraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    p033 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    p034 <- pp_1DD_tileplot(data, colnames(data[vars]), 'yx')
    p035 <- pp_1DD_linerange(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    add_plots_patchwork("p03", 5)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- factor(data[[vars]], levels = unique(data[[vars]]))
    stripe <- c('binned heatmap',
                'bw binned heatmap',
                'color binned heatmap')
    p041 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    p042 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    p043 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("p04", 3)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- forcats::fct_infreq(data[[vars]], ordered = TRUE)
    stripe <- c('freq. reordered binned heatmap',
                'bw freq. reordered binned heatmap',
                'color freq. reordered binned heatmap')
    p051 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    p052 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    p053 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("p05", 3)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- as.character(data[[vars]])
    stripe <- c('alphab. reordered binned heatmap',
                'bw alphab. reordered binned heatmap',
                'color alphab. reordered binned heatmap')
    p061 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    p062 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    p063 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("p06", 3)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- factor(data[[vars]], levels = unique(data[[vars]]))
    stripe <- c('bar graph',
                'bw bar graph',
                'color bar graph')
    p071 <- pp_bargraph(data, colnames(data[vars]), 'black')
    p072 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    p073 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("p07", 3)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- forcats::fct_infreq(data[[vars]], ordered = TRUE)
    stripe <- c('freq. reordered bar graph',
                'bw freq. reordered bar graph',
                'color freq. reordered bar graph')
    p081 <- pp_bargraph(data, colnames(data[vars]), 'black')
    p082 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    p083 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("p08", 3)
    if (label == TRUE) {add_label("cha", stripe)}
    data[[vars]] <- as.character(data[[vars]])
    stripe <- c('alphab. reordered bar graph',
                'bw alphab. reordered bar graph',
                'color alphab. reordered bar graph')
    p091 <- pp_bargraph(data, colnames(data[vars]), 'black')
    p092 <- pp_bargraph(data, colnames(data[vars]), 'bw')
    p093 <- pp_bargraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("p09", 3)
    if (label == TRUE) {add_label("cha", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))}

# numeric -----------------------------------------------------------------


    else if (length(vars) == 1 & is.numeric(unlist(data[, vars])) == TRUE) {
    my_binwidth <- (max(data[vars], na.rm=TRUE)-min(data[vars], na.rm=TRUE))/20
    write(paste0("#+ numeric, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('line graph',
                'stepped line graph')
    p011 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol)
    p012 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_trans = 'step')
    add_plots_patchwork("p01", 2)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('point-to-point graph',
                'stepped point-to-point graph')
    p161 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE)
    p162 <- pp_1DD_linegraph(data, colnames(data[vars]), 'yx', pp_size = 1/ncol, pp_points = TRUE, pp_trans = 'step')
    add_plots_patchwork("p16", 2)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('area graph')
    p131 <- pp_1DD_areagraph(data, colnames(data[vars]), 'yx')
    add_plots_patchwork("p13", 1)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('stepped area graph',
                'bw stepped area graph',
                'color stepped area graph')
    p181 <- pp_1DD_areagraph(data, colnames(data[vars]), 'yx', pp_trans = 'step', pp_color = 'black')
    p182 <- pp_1DD_areagraph(data, colnames(data[vars]), 'yx', pp_trans = 'step', pp_color = 'bw')
    p183 <- pp_1DD_areagraph(data, colnames(data[vars]), 'yx', pp_trans = 'step', pp_color = 'color')
    add_plots_patchwork("p18", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('seq. stripe graph',
                'bw seq. stripe graph',
                'color seq. stripe graph')
    p191 <- pp_1DD_stripegraph(data, colnames(data[vars]), pp_color = 'black')
    p192 <- pp_1DD_stripegraph(data, colnames(data[vars]), pp_color = 'bw')
    p193 <- pp_1DD_stripegraph(data, colnames(data[vars]), pp_color = 'color')
    add_plots_patchwork("p19", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('stripe graph', 'bw stripe graph', 'color stripe graph')
    p021 <- pp_stripegraph(data, colnames(data[vars]), 'black')
    p022 <- pp_stripegraph(data, colnames(data[vars]), 'bw')
    p023 <- pp_stripegraph(data, colnames(data[vars]), 'color')
    add_plots_patchwork("p02", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('binned stripe graph',
                'bw binned stripe graph',
                'color binned stripe graph')
    p031 <- pp_binned_stripegraph(data, colnames(data[vars]), 'black', my_binwidth)
    p032 <- pp_binned_stripegraph(data, colnames(data[vars]), 'bw', my_binwidth)
    p033 <- pp_binned_stripegraph(data, colnames(data[vars]), 'color', my_binwidth)
    add_plots_patchwork("p03", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('point graph',
                'bw point graph',
                'color point graph')
    p041 <- pp_1DD_scatterplot(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'black')
    p042 <- pp_1DD_scatterplot(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'bw')
    p043 <- pp_1DD_scatterplot(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'color')
    add_plots_patchwork("p04", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('point graph with trend line',
                'bw point graph with trend line',
                'color point graph with trend line')
    p121 <- pp_1DD_scatterplot(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'black', 'true')
    p122 <- pp_1DD_scatterplot(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'bw', 'true')
    p123 <- pp_1DD_scatterplot(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'color', 'true')
    add_plots_patchwork("p12", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('binned point graph',
                'bw binned point graph',
                'color binned point graph')
    p051 <- pp_1DD_binnedpointgraph(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'black')
    p052 <- pp_1DD_binnedpointgraph(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'bw')
    p053 <- pp_1DD_binnedpointgraph(data, colnames(data[vars]), 'yx', pp_size = 3/ncol, 'color')
    add_plots_patchwork("p05", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('binned heatmap', 'bw binned heatmap', 'color binned heatmap')
    p061 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'black')
    p062 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'bw')
    p063 <- pp_1DD_heatmap(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("p06", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('blank', 'bw heatmap', 'color heatmap')
    p151 <- blank(data, colnames(data[vars]))
    p152 <- pp_1DD_raster(data, colnames(data[vars]), 'yx', 'bw')
    p153 <- pp_1DD_raster(data, colnames(data[vars]), 'yx', 'color')
    add_plots_patchwork("p15", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('bar graph',
                'bw bar graph',
                'color bar graph')
    p071 <- pp_bargraph(data, colnames(data[vars]), 'black', 'xy', pp_size = 0.2*my_binwidth)
    p072 <- pp_bargraph(data, colnames(data[vars]), 'bw', 'xy', pp_size = 0.2*my_binwidth)
    p073 <- pp_bargraph(data, colnames(data[vars]), 'color', 'xy', pp_size = 0.2*my_binwidth)
    add_plots_patchwork("p07", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('histogram',
                'bw histogram',
                'color histogram')
    p081 <- pp_histogram(data, colnames(data[vars]), 'black', pp_binwidth = my_binwidth)
    p082 <- pp_histogram(data, colnames(data[vars]), 'bw', pp_binwidth = my_binwidth)
    p083 <- pp_histogram(data, colnames(data[vars]), 'color', pp_binwidth = my_binwidth)
    add_plots_patchwork("p08", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('freq. polygon')
    p141 <- pp_histogram(data, colnames(data[vars]), 'black', 1, pp_geom = 'line', my_binwidth)
    add_plots_patchwork("p14", 1)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('density plot',
                'filled density plot')
    p091 <- pp_density(data, colnames(data[vars]), pp_size = 1/ncol)
    p092 <- pp_density(data, colnames(data[vars]), pp_size = 1/ncol, pp_color='black')
    add_plots_patchwork("p09", 2)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('violin plot',
                'filled violin plot')
    p101 <- pp_violin(data, colnames(data[vars]), pp_size = 1/ncol)
    p102 <- pp_violin(data, colnames(data[vars]), pp_size = 1/ncol, pp_color='black')
    add_plots_patchwork("p10", 2)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('box plot',
                '3 uniaxial',
                'normal qq plot')
    p111 <- pp_boxplot(data, colnames(data[vars]), pp_size = 1/ncol)
    p112 <- pp_3uniaxial(data, colnames(data[vars]), pp_size = 4/ncol)
    p113 <- qqplot(data, colnames(data[vars]), pp_size = 1/ncol)
    add_plots_patchwork("p11", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('ecfd plot',
                'dotted ecfd plot',
                'stepped ecfd plot')
    p171 <- pp_ecdf(data, colnames(data[vars]), pp_trans = "rect")
    p172 <- pp_ecdf(data, colnames(data[vars]), pp_trans = "point")
    p173 <- pp_ecdf(data, colnames(data[vars]), pp_trans = "step")
    add_plots_patchwork("p17", 3)
    if (label == TRUE) {add_label("num", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }


# 2var --------------------------------------------------------------------


# dtt~num -----------------------------------------------------------------


  else if (length(vars) == 2 & (
             (lubridate::is.instant(unlist(data[, vars[1]])) == TRUE  &
             lubridate::is.instant(unlist(data[, vars[2]])) == TRUE) |
             (is.numeric(unlist(data[, vars[1]])) == TRUE  &
              lubridate::is.instant(unlist(data[, vars[2]])) == TRUE) |
             (lubridate::is.instant(unlist(data[, vars[1]])) == TRUE  &
              is.numeric(unlist(data[, vars[2]])) == TRUE))) {
    # my_binwidth <- (max(data[vars], na.rm=TRUE)-min(data[vars], na.rm=TRUE))/20
    write(paste0("#+ numeric_datetime, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('scatter plot', 'scatter plot with trend line')
    p001 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, pp_color = 'black', pp_smooth = FALSE)
    p002 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, pp_color = 'black', pp_smooth = TRUE)
    add_plots_patchwork("p00", 2)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    stripe <- c('binned scatter plot', 'bw binned scatter plot', 'color binned scatter plot')
    p021 <- pp_binnedpointgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'black')
    p022 <- pp_binnedpointgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'bw')
    p023 <- pp_binnedpointgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'color')
    add_plots_patchwork("p02", 3)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    stripe <- c('binned heatmap', 'bw binned heatmap', 'color binned heatmap')
    p031 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black')
    p032 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw')
    p033 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color')
    add_plots_patchwork("p03", 3)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    stripe <- c('blank', 'bw heatmap', 'color heatmap')
    p051 <- blank2(data, colnames(data[vars][1]), colnames(data[vars][2]))
    p052 <- pp_raster(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw')
    p053 <- pp_raster(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color')
    add_plots_patchwork("p05", 3)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    stripe <- c('contour plot', 'bw contour plot', 'color contour plot')
    p061 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'black')
    p062 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'bw')
    p063 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'color')
    add_plots_patchwork("p06", 3)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    stripe <- c('contour plot with data points')
    p071 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, 'TRUE')
    add_plots_patchwork("p07", 1)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    stripe <- c('path graph', 'bw path graph', 'color path graph')
    p101 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'black', pp_size = 3/ncol)
    p102 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'bw', pp_size = 3/ncol)
    p103 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'color', pp_size = 3/ncol)
    add_plots_patchwork("p10", 3)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    stripe <- c('point-to-point graph', 'bw point-to-point graph', 'color point-to-point graph')
    p111 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'black', pp_size = 3/ncol)
    p112 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'bw', pp_size = 3/ncol)
    p113 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'color', pp_size = 3/ncol)
    add_plots_patchwork("p11", 3)
    if (label == TRUE) {add_label("{dtt~num} OR {2dtt}", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }

# 2num --------------------------------------------------------------------


  else if (length(vars) == 2 & is.numeric(unlist(data[, vars[1]])) == TRUE & is.numeric(unlist(data[, vars[2]])) == TRUE) {
    # my_binwidth <- (max(data[vars], na.rm=TRUE)-min(data[vars], na.rm=TRUE))/20
    write(paste0("#+ numeric, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('scatter plot', 'bw scatter plot', 'color scatter plot')
    p001 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'black', FALSE)
    p002 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'bw', FALSE)
    p003 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'color', FALSE)
    add_plots_patchwork("p00", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('binned scatter plot', 'bw binned scatter plot', 'color binned scatter plot')
    p021 <- pp_binnedpointgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'black')
    p022 <- pp_binnedpointgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'bw')
    p023 <- pp_binnedpointgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'color')
    add_plots_patchwork("p02", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('binned heatmap', 'bw binned heatmap', 'color binned heatmap')
    p031 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black')
    p032 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw')
    p033 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color')
    add_plots_patchwork("p03", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('hexagonal binned heatmap', 'bw hexagonal binned heatmap', 'color hexagonal binned heatmap')
    p041 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', 6)
    p042 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 6)
    p043 <- pp_heatmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 6)
    add_plots_patchwork("p04", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('blank', 'bw heatmap', 'color heatmap')
    p051 <- blank2(data, colnames(data[vars][1]), colnames(data[vars][2]))
    p052 <- pp_raster(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw')
    p053 <- pp_raster(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color')
    add_plots_patchwork("p05", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('contour plot', 'bw contour plot', 'color contour plot')
    p061 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'black')
    p062 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'bw')
    p063 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'color')
    add_plots_patchwork("p06", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('contour plot with data points', 'bw contour plot with data points', 'color contour plot with data points')
    p071 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, 'TRUE')
    p072 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', pp_size = 3/ncol, 'TRUE')
    p073 <- pp_contourmap(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', pp_size = 3/ncol, 'TRUE')
    add_plots_patchwork("p07", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('scatter plot with confidence ellipse', 'bw scatter plot with confidence ellipse', 'color scatter plot with confidence ellipse')
    p241 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'black', FALSE, TRUE, FALSE)
    p242 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'bw', FALSE, TRUE, FALSE)
    p243 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'color', FALSE, TRUE, FALSE)
    add_plots_patchwork("p24", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('scatter plot with marginal rugs', 'bw scatter plot with marginal rugs', 'color scatter plot with marginal rugs')
    p251 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'black', FALSE, FALSE, TRUE)
    p252 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'bw', FALSE, FALSE, TRUE)
    p253 <- pp_scatterplot(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 3/ncol, 'color', FALSE, FALSE, TRUE)
    add_plots_patchwork("p25", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('parallel plot', 'bw parallel plot', 'color parallel plot')
    p081 <- pp_parallel(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'black', pp_size = 3/ncol)
    p082 <- pp_parallel(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'bw', pp_size = 3/ncol)
    p083 <- pp_parallel(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'color', pp_size = 3/ncol)
    add_plots_patchwork("p08", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('unscaled parallel plot', 'unscaled bw parallel plot', 'unscaled color parallel plot')
    p091 <- pp_parallel(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'black', pp_size = 3/ncol)
    p092 <- pp_parallel(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'bw', pp_size = 3/ncol)
    p093 <- pp_parallel(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'color', pp_size = 3/ncol)
    add_plots_patchwork("p09", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('path graph', 'bw path graph', 'color path graph')
    p101 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'black', pp_size = 3/ncol)
    p102 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'bw', pp_size = 3/ncol)
    p103 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), FALSE, 'color', pp_size = 3/ncol)
    add_plots_patchwork("p10", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('point-to-point graph', 'bw point-to-point graph', 'color point-to-point graph')
    p111 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'black', pp_size = 3/ncol)
    p112 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'bw', pp_size = 3/ncol)
    p113 <- pp_pathgraph(data, colnames(data[vars][1]), colnames(data[vars][2]), TRUE, 'color', pp_size = 3/ncol)
    add_plots_patchwork("p11", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('point graph', 'bw point graph', 'color point graph')
    p121 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'point')
    p122 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', pp_size = 3/ncol, pp_geom = 'point')
    p123 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', pp_size = 3/ncol, pp_geom = 'point')
    add_plots_patchwork("p12", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('line graph', 'stepped line graph')
    p131 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'line')
    p132 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'step')
    add_plots_patchwork("p13", 2)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('area graph')
    p141 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'area')
    add_plots_patchwork("p14", 1)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('stepped area graph', 'bw stepped area graph', 'color stepped area graph')
    p151 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'bar')
    p152 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', pp_size = 3/ncol, pp_geom = 'bar')
    p153 <- pp_unfolded(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', pp_size = 3/ncol, pp_geom = 'bar')
    add_plots_patchwork("p15", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('blank', 'bw seq. heatmap', 'color seq. heatmap')
    p161 <- blank2(data, colnames(data[vars][1]), colnames(data[vars][2]))
    p162 <- pp_unf_raster(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', pp_size = 3/ncol, pp_geom = 'heat')
    p163 <- pp_unf_raster(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', pp_size = 3/ncol, pp_geom = 'heat')
    add_plots_patchwork("p16", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('blank', 'bw seq. stripe graph', 'color seq. stripe graph')
    p171 <- blank2(data, colnames(data[vars][1]), colnames(data[vars][2]))
    p172 <- pp_unf_tile(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', pp_size = 3/ncol, pp_geom = 'tile')
    p173 <- pp_unf_tile(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', pp_size = 3/ncol, pp_geom = 'tile')
    add_plots_patchwork("p17", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('histogram', 'bw histogram', 'color histogram')
    p181 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'hist')
    p182 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', pp_size = 3/ncol, pp_geom = 'hist')
    p183 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', pp_size = 3/ncol, pp_geom = 'hist')
    add_plots_patchwork("p18", 3)
    if (label == TRUE) {add_label("num", stripe)}
    stripe <- c('freq. polygon')
    p191 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'freq')
    add_plots_patchwork("p19", 1)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('density plot', 'filled density plot')
    p201 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'dens')
    p202 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'fill', pp_size = 3/ncol, pp_geom = 'dens')
    add_plots_patchwork("p20", 2)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('violin plot', 'filled violin plot')
    p211 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'viol')
    p212 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'fill', pp_size = 3/ncol, pp_geom = 'viol')
    add_plots_patchwork("p21", 2)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('box plot')
    p221 <- pp_unf_yuxt(data, colnames(data[vars][1]), colnames(data[vars][2]), 'black', pp_size = 3/ncol, pp_geom = 'box')
    add_plots_patchwork("p22", 1)
    if (label == TRUE) {add_label("2num", stripe)}
    stripe <- c('ecdf plot', 'point ecdf plot', 'stepped ecdf plot')
    p231 <- pp_unf_ecdf(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 1/ncol, pp_trans = 'line')
    p232 <- pp_unf_ecdf(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 1/ncol, pp_trans = 'point')
    p233 <- pp_unf_ecdf(data, colnames(data[vars][1]), colnames(data[vars][2]), pp_size = 1/ncol, pp_trans = 'step')
    add_plots_patchwork("p23", 3)
    if (label == TRUE) {add_label("2num", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }

# ordnum ------------------------------------------------------------------


  else if (length(vars) == 2 & ((
    is.numeric(unlist(data[, vars[1]])) == TRUE &
    is.ordered(unlist(data[, vars[2]])) == TRUE) |
    (
      is.numeric(unlist(data[, vars[2]])) == TRUE &
      is.ordered(unlist(data[, vars[1]])) == TRUE))) {
    write(paste0("#+ ordered_numeric, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    var1 <- colnames(data[vars][which(sapply(data[vars], is.numeric))])
    var2 <- colnames(data[vars][which(sapply(data[vars], is.ordered))])
    stripe <- c('path graph',
                'point graph',
                'tile plot')
    ordnum11 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'line')
    ordnum12 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'point')
    ordnum13 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'tile')
    add_plots_patchwork("ordnum1", 3)
    if (label == TRUE) {add_label("ord-num", stripe)}
    stripe <- c('binned heatmap',
                'bw binned heatmap',
                'color binned heatmap')
    ordnum41 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'bin', 'black')
    ordnum42 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'bin', 'bw')
    ordnum43 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'bin', 'color')
    add_plots_patchwork("ordnum4", 3)
    if (label == TRUE) {add_label("ord-num", stripe)}
    stripe <- c('violin plot', 'filled violin plot')
    ordnum21 <- pp_basicgraph(data, var2, var1, pp_size = 1/ncol, 'violin')
    ordnum22 <- pp_basicgraph(data, var2, var1, pp_size = 1/ncol, 'violin filled')
    add_plots_patchwork("ordnum2", 2)
    if (label == TRUE) {add_label("ord-num", stripe)}
    stripe <- c('box plot')
    ordnum31 <- pp_basicgraph(data, var2, var1, pp_size = 1/ncol, 'box')
    add_plots_patchwork("ordnum3", 1)
    if (label == TRUE) {add_label("ord-num", stripe)}
    write(paste0("#+ factor_numeric2, fig.width=12, fig.height=2.5"), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('blank',
                'bw stacked histogram',
                'color stacked histogram')
    ordnum51 <- blank2(data, var1, var2)
    ordnum52 <- pp_histogram2(data, var1, var2)
    ordnum53 <- pp_histogram2(data, var1, var2, pp_color = "color", pp_scale = "ordinal")
    add_plots_patchwork_guides("ordnum5", 3)
    if (label == TRUE) {add_label("ord-num", stripe)}
    stripe <- c('blank',
                'bw 100% stacked histogram',
                'color 100% stacked histogram')
    ordnum61 <- blank2(data, var1, var2)
    ordnum62 <- pp_histogram2(data, var1, var2, pp_position = "fill")
    ordnum63 <- pp_histogram2(data, var1, var2, pp_color = "color", pp_position = "fill", pp_scale = "ordinal")
    add_plots_patchwork_guides("ordnum6", 3)
    if (label == TRUE) {add_label("ord-num", stripe)}
    stripe <- c('density plot',
                'bw density plot',
                'color density plot')
    ordnum71 <- pp_density2(data, var1, var2, 0.5, "line", "black")
    ordnum72 <- pp_density2(data, var1, var2, 0.5, "line", "bw")
    ordnum73 <- pp_density2(data, var1, var2, 0.5, "line", "viridis")
    add_plots_patchwork_guides("ordnum7", 3)
    if (label == TRUE) {add_label("ord-num", stripe)}
    stripe <- c('blank',
                'bw filled density plot',
                'color filled density plot')
    ordnum81 <- blank2(data, var1, var2)
    ordnum82 <- pp_density2(data, var2, var1, 0.5, "area", "bw")
    ordnum83 <- pp_density2(data, var2, var1, 0.5, "area", "viridis")
    add_plots_patchwork_guides("ordnum8", 3)
    if (label == TRUE) {add_label("ord-num", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }

# facnum ------------------------------------------------------------------


  else if (length(vars) == 2 & ((
    is.numeric(unlist(data[, vars[1]])) == TRUE &
    (is.factor(unlist(data[, vars[2]])) == TRUE & is.ordered(unlist(data[, vars[2]])) == FALSE)) |
    (
      is.numeric(unlist(data[, vars[2]])) == TRUE &
      (is.factor(unlist(data[, vars[1]])) == TRUE & is.ordered(unlist(data[, vars[1]])) == FALSE)))) {
    write(paste0("#+ factor_numeric, fig.width=12, fig.height=", long), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    var1 <- colnames(data[vars][which(sapply(data[vars], is.numeric))])
    var2 <- colnames(data[vars][which(sapply(data[vars], is.factor))])
    data2 <- data[ , c(var1, var2)]
    data3b <- as.data.frame(stats::ftable(data2[2], useNA = "no"))
    data2[,2]  <- factor(data2[,2], levels = data3b[order(-data3b$Freq),][,1], ordered = TRUE)
    data4 <- data[ , c(var1, var2)]
    data4[,2] <- as.character(data4[,2])
    stripe <- c('path graph',
                'freq. reordered path graph',
                'alphab. reordered path graph')
    facnum011 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'line')
    facnum012 <- pp_basicgraph(data2, var1, var2, pp_size = 1/ncol, 'line')
    facnum013 <- pp_basicgraph(data4, var1, var2, pp_size = 1/ncol, 'line')
    add_plots_patchwork("facnum01", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('point graph',
                'freq. reordered point graph',
                'alphab. reordered point graph')
    facnum021 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'point')
    facnum022 <- pp_basicgraph(data2, var1, var2, pp_size = 1/ncol, 'point')
    facnum023 <- pp_basicgraph(data4, var1, var2, pp_size = 1/ncol, 'point')
    add_plots_patchwork("facnum02", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('tile plot',
                'freq. reordered tile plot',
                'alphab. reordered tile plot')
    facnum031 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'tile')
    facnum032 <- pp_basicgraph(data2, var1, var2, pp_size = 1/ncol, 'tile')
    facnum033 <- pp_basicgraph(data4, var1, var2, pp_size = 1/ncol, 'tile')
    add_plots_patchwork("facnum03", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('binned heatmap',
                'freq. reordered binned heatmap',
                'alphab. reordered binned heatmap')
    facnum111 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'bin', 'black')
    facnum112 <- pp_basicgraph(data2, var1, var2, pp_size = 1/ncol, 'bin', 'black')
    facnum113 <- pp_basicgraph(data4, var1, var2, pp_size = 1/ncol, 'bin', 'black')
    add_plots_patchwork("facnum11", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('bw binned heatmap',
                'bw freq. reordered binned heatmap',
                'bw alphab. reordered binned heatmap')
    facnum121 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'bin', 'bw')
    facnum122 <- pp_basicgraph(data2, var1, var2, pp_size = 1/ncol, 'bin', 'bw')
    facnum123 <- pp_basicgraph(data4, var1, var2, pp_size = 1/ncol, 'bin', 'bw')
    add_plots_patchwork("facnum12", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('color binned heatmap',
                'color freq. reordered binned heatmap',
                'color alphab. reordered binned heatmap')
    facnum131 <- pp_basicgraph(data, var1, var2, pp_size = 1/ncol, 'bin', 'color')
    facnum132 <- pp_basicgraph(data2, var1, var2, pp_size = 1/ncol, 'bin', 'color')
    facnum133 <- pp_basicgraph(data4, var1, var2, pp_size = 1/ncol, 'bin', 'color')
    add_plots_patchwork("facnum13", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('violin plot', 'freq. reordered violin plot', 'alphab. reordered violin plot')
    facnum211 <- pp_basicgraph(data, var2, var1, pp_size = 1/ncol, 'violin')
    facnum212 <- pp_basicgraph(data2, var2, var1, pp_size = 1/ncol, 'violin')
    facnum213 <- pp_basicgraph(data4, var2, var1, pp_size = 1/ncol, 'violin')
    add_plots_patchwork("facnum21", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('filled violin plot', 'freq. reordered filled violin plot', 'alphab. reordered filled violin plot')
    facnum221 <- pp_basicgraph(data, var2, var1, pp_size = 1/ncol, 'violin filled')
    facnum222 <- pp_basicgraph(data2, var2, var1, pp_size = 1/ncol, 'violin filled')
    facnum223 <- pp_basicgraph(data4, var2, var1, pp_size = 1/ncol, 'violin filled')
    add_plots_patchwork("facnum22", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('box plot', 'freq. reordered box plot', 'alphab. reordered box plot')
    facnum311 <- pp_basicgraph(data, var2, var1, pp_size = 1/ncol, 'box')
    facnum312 <- pp_basicgraph(data2, var2, var1, pp_size = 1/ncol, 'box')
    facnum313 <- pp_basicgraph(data4, var2, var1, pp_size = 1/ncol, 'box')
    add_plots_patchwork("facnum31", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    write(paste0("#+ factor_numeric2, fig.width=12, fig.height=2.5"), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe <- c('blank',
                'bw stacked histogram',
                'color stacked histogram')
    facnum51 <- blank2(data, var1, var2)
    facnum52 <- pp_histogram2(data, var1, var2)
    facnum53 <- pp_histogram2(data, var1, var2, pp_color = "color")
    add_plots_patchwork_guides("facnum5", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('blank',
                'bw 100% stacked histogram',
                'color 100% stacked histogram')
    facnum61 <- blank2(data, var1, var2)
    facnum62 <- pp_histogram2(data, var1, var2, pp_position = "fill")
    facnum63 <- pp_histogram2(data, var1, var2, pp_color = "color", pp_position = "fill")
    add_plots_patchwork_guides("facnum6", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('density plot',
                'blank',
                'color density plot')
    facnum71 <- pp_density2(data, var1, var2, 0.5, "line", "black")
    facnum72 <- blank2(data, var1, var2)
    facnum73 <- pp_density2(data, var1, var2, 0.5, "line", "color")
    add_plots_patchwork_guides("facnum7", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    stripe <- c('blank',
                'filled density plot',
                'color filled density plot')
    facnum81 <- blank2(data, var1, var2)
    facnum82 <- pp_density2(data, var2, var1, 0.5, "area", "bw")
    facnum83 <- pp_density2(data, var2, var1, 0.5, "area", "color")
    add_plots_patchwork_guides("facnum8", 3)
    if (label == TRUE) {add_label("fac-num", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }

# 2ord --------------------------------------------------------------------


  else if (length(vars) == 2 & is.ordered(unlist(data[, vars[1]])) == TRUE & is.ordered(unlist(data[, vars[2]])) == TRUE) {
    panel.h <- unit(nrow(unique(data[vars[1]]))*0.7, "cm")
    panel.w <- unit(3.5, "cm")
    panel.h2 <- unit(nrow(unique(data[vars[2]]))*0.7, "cm")
    panel.w2 <- unit(nrow(unique(data[vars[1]]))*0.7, "cm")
    write(paste0("#+ 2ord_1, fig.width=8, fig.height=", long+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('bw stacked bar graph', 'color stacked bar graph')
    ofof01   <- pp_stackedbar(data, colnames(data[vars][2]), colnames(data[vars][1]), 'bw', 'stack', 'ordinal')
    ofof02   <- pp_stackedbar(data, colnames(data[vars][2]), colnames(data[vars][1]), 'color', 'stack', 'ordinal')
    add_float_patchwork("ofof0", 2, "w", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    write(paste0("#+ 2ord_2, fig.width=8, fig.height=", longt+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('transposed bw stacked bar graph', 'transposed color stacked bar graph')
    ofof051   <- pp_stackedbar(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'stack', 'ordinal')
    ofof052   <- pp_stackedbar(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'stack', 'ordinal')
    add_float_patchwork("ofof05", 2, "w", "h", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    write(paste0("#+ 2ord_3, fig.width=8, fig.height=", long+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('bw 100% stacked bar graph', 'color 100% stacked bar graph')
    ofof11   <- pp_stackedbar(data, colnames(data[vars][2]), colnames(data[vars][1]), 'bw', 'fill', 'ordinal')
    ofof12   <- pp_stackedbar(data, colnames(data[vars][2]), colnames(data[vars][1]), 'color', 'fill', 'ordinal')
    add_float_patchwork("ofof1", 2, "w", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    write(paste0("#+ 2ord_4, fig.width=8, fig.height=", longt+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('transposed bw 100% stacked bar graph', 'transposed color 100% stacked bar graph')
    ofof151   <- pp_stackedbar(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'fill', 'ordinal')
    ofof152   <- pp_stackedbar(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'fill', 'ordinal')
    add_float_patchwork("ofof15", 2, "w", "h", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    write(paste0("#+ 2ord_5, fig.width=", longt*2+5, ", fig.height=", long+1.5), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('bw heatmap', 'color heatmap')
    ofof21   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'observed')
    ofof22   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'observed')
    add_float_patchwork("ofof2", 2, "w2", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    stripe  <- c('blank', 'color residuals heatmap')
    ofof41   <- blank2(data, colnames(data[vars][1]), colnames(data[vars][2]))
    ofof42   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'residuals')
    add_float_patchwork("ofof4", 2, "w2", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    stripe  <- c('bw contribution to x2 heatmap', 'color contribution to x2 heatmap')
    ofof61   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'contrib')
    ofof62   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'contrib')
    add_float_patchwork("ofof6", 2, "w2", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    stripe  <- c('bw balloon plot', 'color balloon plot')
    ofof101   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'observed', pp_geom = 'point')
    ofof102   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'observed', pp_geom = 'point')
    add_float_patchwork("ofof10", 2, "w2", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    stripe  <- c('blank', 'color residuals balloon plot')
    ofof121   <- blank2(data, colnames(data[vars][1]), colnames(data[vars][2]))
    ofof122   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'residuals', pp_geom = 'point')
    add_float_patchwork("ofof12", 2, "w2", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    stripe  <- c('bw contribution to x2 balloon plot', 'color contribution to x2 balloon plot')
    ofof141   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'contrib', pp_geom = 'point')
    ofof142   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'contrib', pp_geom = 'point')
    add_float_patchwork("ofof14", 2, "w2", "h2", 2)
    if (label == TRUE) {add_label("2ord", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }

# 2fac --------------------------------------------------------------------


  else if (length(vars) == 2 &
             (is.factor(unlist(data[, vars[1]])) == TRUE & is.ordered(unlist(data[, vars[1]])) == FALSE) &
             (is.factor(unlist(data[, vars[2]])) == TRUE & is.ordered(unlist(data[, vars[2]])) == FALSE)) {
    panel.h <- unit(nrow(unique(data[vars[1]]))*0.7, "cm")
    panel.h2 <- unit(nrow(unique(data[vars[2]]))*0.7, "cm")
    panel.w <- unit(3.5, "cm")
    data2 <- data[, vars]
    data3  <- as.data.frame(stats::ftable(data2[1], useNA = "no"))
    data3b <- as.data.frame(stats::ftable(data2[2], useNA = "no"))
    data2[,1]  <- factor(data2[,1], levels = data3[order(-data3$Freq),][,1], ordered = TRUE)
    data2[,2]  <- factor(data2[,2], levels = data3b[order(-data3b$Freq),][,1], ordered = TRUE)
    data4 <- data[, vars]
    data4[[vars[1]]] <- as.character(data4[[vars[1]]])
    data4[[vars[2]]] <- as.character(data4[[vars[2]]])
    write(paste0("#+ 2fac_1, fig.width=12, fig.height=", long+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('color stacked bar graph', 'color freq. reordered stacked bar graph', 'color alphab. reordered stacked bar graph')
    fafa01   <- pp_stackedbar(data, colnames(data2[vars][2]), colnames(data2[vars][1]), 'color', 'stack')
    fafa02   <- pp_stackedbar(data2, colnames(data2[vars][2]), colnames(data2[vars][1]), 'color', 'stack')
    fafa03   <- pp_stackedbar(data4, colnames(data4[vars][2]), colnames(data4[vars][1]), 'color', 'stack')
    add_float_patchwork("fafa0", 3, "w", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    write(paste0("#+ 2fac_2, fig.width=12, fig.height=", longt+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('transposed color stacked bar graph', 'transposed color freq. reordered stacked bar graph', 'transposed color alphab. reordered stacked bar graph')
    fafa051   <- pp_stackedbar(data, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'stack')
    fafa052   <- pp_stackedbar(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'stack')
    fafa053   <- pp_stackedbar(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'stack')
    add_float_patchwork("fafa05", 3, "w", "h", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    write(paste0("#+ 2fac_3, fig.width=12, fig.height=", long+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('color 100% stacked bar graph', 'color freq. reordered 100% stacked bar graph', 'color alphab. reordered 100% stacked bar graph')
    fafa11   <- pp_stackedbar(data, colnames(data[vars][2]), colnames(data[vars][1]), 'color', 'fill')
    fafa12   <- pp_stackedbar(data2, colnames(data2[vars][2]), colnames(data2[vars][1]), 'color', 'fill')
    fafa13   <- pp_stackedbar(data4, colnames(data4[vars][2]), colnames(data4[vars][1]), 'color', 'fill')
    add_float_patchwork("fafa1", 3, "w", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    write(paste0("#+ 2fac_4, fig.width=12, fig.height=", longt+1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('transposed color 100% stacked bar graph', 'transposed color freq. reordered 100% stacked bar graph', 'transposed color alphab. reordered 100% stacked bar graph')
    fafa151   <- pp_stackedbar(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'fill')
    fafa152   <- pp_stackedbar(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'fill')
    fafa153   <- pp_stackedbar(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'fill')
    add_float_patchwork("fafa15", 3, "w", "h", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    panel.h2 <- unit(nrow(unique(data[vars[2]]))*0.7, "cm")
    panel.w2 <- unit(nrow(unique(data[vars[1]]))*0.7, "cm")
    write(paste0("#+ 2fac_5, fig.width=", wide*3+10, ", fig.height=", long+1.5), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('bw heatmap', 'bw freq. reordered heatmap', 'bw alphab. reordered heatmap')
    fafa21   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'observed')
    fafa22   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'observed')
    fafa23   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'observed')
    add_float_patchwork("fafa2", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('color heatmap', 'color freq. reordered heatmap', 'color alphab. reordered heatmap')
    fafa31   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'observed')
    fafa32   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'observed')
    fafa33   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'observed')
    add_float_patchwork("fafa3", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('color residuals heatmap', 'color freq. reordered residuals heatmap', 'color alphab. reordered residuals heatmap')
    fafa41  <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'residuals')
    fafa42   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'residuals')
    fafa43   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'residuals')
    add_float_patchwork("fafa4", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('bw contribution to x2 heatmap', 'bw freq. reordered contribution to x2 heatmap', 'bw alphab. reordered contribution to x2 heatmap')
    fafa61   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'contrib')
    fafa62   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'contrib')
    fafa63   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'contrib')
    add_float_patchwork("fafa6", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('color contribution to x2 heatmap', 'color freq. reordered contribution to x2 heatmap', 'color alphab. reordered contribution to x2 heatmap')
    fafa71   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'contrib')
    fafa72   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'contrib')
    fafa73   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'contrib')
    add_float_patchwork("fafa7", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('bw balloon plot', 'bw freq. reordered balloon plot', 'bw alphab. reordered balloon plot')
    fafa81   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'observed', pp_geom = "point")
    fafa82   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'observed', pp_geom = "point")
    fafa83   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'observed', pp_geom = "point")
    add_float_patchwork("fafa8", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('color balloon plot', 'color freq. reordered balloon plot', 'color alphab. reordered balloon plot')
    fafa91   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'observed', pp_geom = "point")
    fafa92   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'observed', pp_geom = "point")
    fafa93   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'observed', pp_geom = "point")
    add_float_patchwork("fafa9", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('color residuals balloon plot', 'color freq. reordered residuals balloon plot', 'color alphab. reordered residuals balloon plot')
    fafa101   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'residuals', pp_geom = "point")
    fafa102   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'residuals', pp_geom = "point")
    fafa103   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'residuals', pp_geom = "point")
    add_float_patchwork("fafa10", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('bw contribution to x2 balloon plot', 'bw freq. reordered contribution to x2 balloon plot', 'bw alphab. reordered contribution to x2 balloon plot')
    fafa121   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'contrib', pp_geom = "point")
    fafa122   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'contrib', pp_geom = "point")
    fafa123   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'contrib', pp_geom = "point")
    add_float_patchwork("fafa12", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    stripe  <- c('color contribution to x2 balloon plot', 'color freq. reordered contribution to x2 balloon plot', 'color alphab. reordered contribution to x2 balloon plot')
    fafa131   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'contrib', pp_geom = "point")
    fafa132   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'contrib', pp_geom = "point")
    fafa133   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'contrib', pp_geom = "point")
    add_float_patchwork("fafa13", 3, "w2", "h2", 3)
    if (label == TRUE) {add_label("2fac", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }

# facord ------------------------------------------------------------------


  else if (length(vars) == 2 &
             ((
               is.ordered(unlist(data[, vars[1]])) == TRUE &
               (is.factor(unlist(data[, vars[2]])) == TRUE & is.ordered(unlist(data[, vars[2]])) == FALSE)) |
              (
                is.ordered(unlist(data[, vars[2]])) == TRUE &
                (is.factor(unlist(data[, vars[1]])) == TRUE & is.ordered(unlist(data[, vars[1]])) == FALSE)))) {
    var2 <- colnames(data[vars][,sapply(data[vars], function(x) is.factor(x) & !is.ordered(x)), drop = FALSE])
    var1 <- colnames(data[vars][which(sapply(data[vars], is.ordered))])
    panel.h <- unit(length(unique(data[,var2]))*0.7, "cm")
    panel.h2 <- unit(length(unique(data[,var1]))*0.7, "cm")
    panel.w <- unit(3.5, "cm")
    data2 <- data[, vars]
    data3b <- as.data.frame(stats::ftable(data2[2], useNA = "no"))
    data2[,2]  <- factor(data2[,2], levels = data3b[order(-data3b$Freq),][,1], ordered = TRUE)
    data4 <- data[, vars]
    data4[[vars[2]]] <- as.character(data4[[vars[2]]])
    write(paste0("#+ facord_1, fig.width=12, fig.height=", length(unique(unlist(data[, var2]))) / 3.7 + 1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('bw stacked bar graph', 'bw freq. reordered stacked bar graph', 'bw alphab. reordered stacked bar graph')
    offa01   <- pp_stackedbar(data,  var2, var1, 'bw', 'stack')
    offa02   <- pp_stackedbar(data2, var2, var1, 'bw', 'stack')
    offa03   <- pp_stackedbar(data4, var2, var1, 'bw', 'stack')
    add_float_patchwork("offa0", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe  <- c('color stacked bar graph', 'color freq. reordered stacked bar graph', 'color alphab. reordered stacked bar graph')
    offa11   <- pp_stackedbar(data,  var2, var1, 'color', 'stack', 'ordinal')
    offa12   <- pp_stackedbar(data2, var2, var1, 'color', 'stack', 'ordinal')
    offa13   <- pp_stackedbar(data4, var2, var1, 'color', 'stack', 'ordinal')
    add_float_patchwork("offa1", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    write(paste0("#+ facord_2, fig.width=12, fig.height=", length(unique(unlist(data[, var1]))) / 3.7 + 1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('transposed color stacked bar graph')
    offa211   <- pp_stackedbar(data,  var1, var2, 'color', 'stack')
    add_float_patchwork("offa21", 1, "w", "h2", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    write(paste0("#+ facord_3, fig.width=12, fig.height=", length(unique(unlist(data[, var2]))) / 3.7 + 1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('bw 100% stacked bar graph', 'bw freq. reordered 100% stacked bar graph', 'bw alphab. reordered 100% stacked bar graph')
    offa21   <- pp_stackedbar(data, var2, var1, pp_color = 'bw', pp_position = 'fill')
    offa22   <- pp_stackedbar(data2, var2, var1, pp_color = 'bw', pp_position = 'fill')
    offa23   <- pp_stackedbar(data4, var2, var1, pp_color = 'bw', pp_position = 'fill')
    add_float_patchwork("offa2", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe  <- c('color 100% stacked bar graph', 'color freq. reordered 100% stacked bar graph', 'color alphab. reordered 100% stacked bar graph')
    offa31   <- pp_stackedbar(data, var2, var1, pp_color = 'color', pp_position = 'fill', 'ordinal')
    offa32   <- pp_stackedbar(data2, var2, var1, pp_color = 'color', pp_position = 'fill', 'ordinal')
    offa33   <- pp_stackedbar(data4, var2, var1, pp_color = 'color', pp_position = 'fill', 'ordinal')
    add_float_patchwork("offa3", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    write(paste0("#+ facord_4, fig.width=12, fig.height=", length(unique(unlist(data[, var1]))) / 3.7 + 1), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    stripe  <- c('transposed color 100% stacked bar graph')
    offa221   <- pp_stackedbar(data,  var1, var2, 'color', 'fill')
    add_float_patchwork("offa22", 1, "w", "h2", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    write(paste0("#+ facord_5, fig.width=12, fig.height=", length(unique(unlist(data[, var2]))) / 3.7 + 1.5), file.path(dir, "brinton_outcomes", "longplot.R"), append=TRUE)
    panel.w2 <- unit(nrow(unique(data[vars[1]]))*0.7, "cm")
    stripe  <- c('bw heatmap', 'bw freq. reordered heatmap', 'bw alphab. reordered heatmap')
    offa41   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'observed')
    offa42   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'observed')
    offa43   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'observed')
    add_float_patchwork("offa4", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe  <- c('color heatmap', 'color freq. reordered heatmap', 'color alphab. reordered heatmap')
    offa51   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'observed')
    offa52   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'observed')
    offa53   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'observed')
    add_float_patchwork("offa5", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe  <- c('color residuals heatmap', 'color freq. reordered residuals heatmap', 'color alphab. reordered residuals heatmap')
    offa61   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'residuals')
    offa62   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'residuals')
    offa63   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'residuals')
    add_float_patchwork("offa6", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe    <- c('bw contribution to x2 heatmap', 'color contribution to x2 heatmap')
    offa81    <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'contrib')
    offa82    <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'contrib')
    offa83    <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'contrib')
    add_float_patchwork("offa8", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe    <- c('bw freq. reordered contribution to x2 heatmap', 'color freq. reordered contribution to x2 heatmap')
    offa91    <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'contrib')
    offa92    <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'contrib')
    offa93    <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'contrib')
    add_float_patchwork("offa9", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe    <- c('bw balloon plot', 'bw freq. reordered balloon plot', 'bw alphab. reordered balloon plot')
    offa101   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'observed', pp_geom = "point")
    offa102   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'observed', pp_geom = "point")
    offa103   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'observed', pp_geom = "point")
    add_float_patchwork("offa10", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe    <- c('color balloon plot', 'color freq. reordered balloon plot', 'color alphab. reordered balloon plot')
    offa111   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'observed', pp_geom = "point")
    offa112   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'observed', pp_geom = "point")
    offa113   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'observed', pp_geom = "point")
    add_float_patchwork("offa11", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe    <- c('color residuals balloon plot', 'color freq. reordered residuals balloon plot', 'color alphab. reordered residuals balloon plot')
    offa121   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'residuals', pp_geom = "point")
    offa122   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'residuals', pp_geom = "point")
    offa123   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'residuals', pp_geom = "point")
    add_float_patchwork("offa12", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe  <- c('bw contribution to x2 balloon plot', 'bw freq. reordered contribution to x2 balloon plot', 'bw alphab. reordered contribution to x2 balloon plot')
    offa141   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'bw', 'contrib', pp_geom = "point")
    offa142   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'bw', 'contrib', pp_geom = "point")
    offa143   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'bw', 'contrib', pp_geom = "point")
    add_float_patchwork("offa14", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    stripe  <- c('color contribution to x2 balloon plot', 'color freq. reordered contribution to x2 balloon plot', 'color alphab. reordered contribution to x2 balloon plot')
    offa151   <- pp_contingency(data, colnames(data[vars][1]), colnames(data[vars][2]), 'color', 'contrib', pp_geom = "point")
    offa152   <- pp_contingency(data2, colnames(data2[vars][1]), colnames(data2[vars][2]), 'color', 'contrib', pp_geom = "point")
    offa153   <- pp_contingency(data4, colnames(data4[vars][1]), colnames(data4[vars][2]), 'color', 'contrib', pp_geom = "point")
    add_float_patchwork("offa15", 3, "w", "h", 3)
    if (label == TRUE) {add_label("offa", stripe)}
    rmarkdown::render(file.path(dir, "brinton_outcomes", "longplot.R"),"html_document")
    pander::openFileInOS(file.path(dir, "brinton_outcomes", "longplot.html"))
  }
  else {print("This combination of variable types has not been considered yet")}
    }
  }
}