4th attempt at clean plots for data documentation

dataMaid_cleanPlot.R

#'dataMaid_cleanPlot.R
#'
#'These functions makes the default graphics prettier/easier to read:
#'
#'  1. Minimal Theme
#'  2. Angled Axis Text
#'
#' @example 

cleanPlotHelper <- function(data, vnam, sideways) {
   p <- ggplot(aes(x = mids, y = counts), data = data)  +
    geom_bar(stat = "identity") +
    labs(x = vnam, y = "Frequency") +
    theme_minimal() +
    theme(axis.text.x = element_text(angle = 30, hjust = 1)) 

  if (sideways) {
    p <- p + coord_flip()
  }   
     
  return(p)
}

cleanPlot <- function(v, vnam, doEval = TRUE) {
  
  sideways <- TRUE
  
  if (length(unique(v)) > 20 && ("numeric" %in% class(v) | "integer" %in% class(v))) {
    tmp <- hist(v, plot = FALSE)
    tmp <- as.data.frame(tmp[c("mids", "counts")])
    sideways <- FALSE
  } else {
    tmp <- data.frame("mids" = v) %>% 
      dplyr::group_by(mids) %>% 
      dplyr::count(.) %>% 
      dplyr::rename(counts = n)
  }
  
  if ((!is.ordered(tmp$mids) && is.factor(tmp$mids)) || is.character(tmp$mids)) {
    tmp$mids <- forcats::fct_reorder(tmp$mids, tmp$counts)
  }
  
  thisCall <- call("cleanPlotHelper", data = tmp, vnam = vnam, sideways = sideways)
  
  if (doEval) {
    return(eval(thisCall))
  } else {
    return(deparse(thisCall))
  }
}

cleanPlot <- visualFunction(cleanPlot, 
                            description = "Cleaned Plots for Data Documentation",
                            classes = c("character", "factor", "labelled", "numeric", "integer", "logical", "Date"))