Reverse 'missingness' plot to 'complete entries'

[steinjm]

Hi,

I have lots of colleagues without data background for which the missingness is quite confusing. Would it be possible to have an argument in the create_report() function that reverses this plot? I've changed up the function to do this quick and dirty, but integrating it into the create_report function is a bit much for me. Here's an example plot and the example function:

plot_missing2 = function (data, group = list(Good = 1, OK = 0.6, Bad = 0.2, 
                             Remove = 0), group_color = list(Good = "#1B9E77", OK = "#E6AB02", 
                                                             Bad = "#D95F02", Remove = "#E41A1C"), missing_only = FALSE, 
          geom_label_args = list(), title = NULL, ggtheme = theme_gray(), 
          theme_config = list(legend.position = c("bottom"))){
  num_missing <- pct_missing <- Band <- NULL
  missing_value <- data.table(profile_missing(data))
  missing_value$pct_missing = 1-missing_value$pct_missing
  missing_value$num_missing = nrow(data)-missing_value$num_missing
  if (missing_only) {
    missing_value <- missing_value[num_missing > 0]}
  group <- group[sort.list(unlist(group))]
  invisible(lapply(seq_along(group), function(i) {
    if (i == 1) {
      missing_value[pct_missing <= group[[i]], `:=`(Band, 
                                                    names(group)[i])]
    } else {
      missing_value[pct_missing > group[[i - 1]] & pct_missing <= 
                      group[[i]], `:=`(Band, names(group)[i])]
    }
  }))
  ordinal_levels <- names(group[sort.list(unlist(group))])
  missing_value[, `:=`(Band, factor(Band, levels = ordinal_levels, 
                                    ordered = TRUE))]
  if (length(setdiff(names(group), names(group_color))) > 0) {
    bar_fill <- scale_fill_discrete("Band")
  } else {
    bar_fill <- scale_fill_manual(values = group_color)
  }
  output <- ggplot(missing_value, aes_string(x = "feature", 
                                             y = "num_missing", fill = "Band")) + geom_bar(stat = "identity") + 
    bar_fill + coord_flip() + xlab("Features") + ylab("Complete Entries") + 
    guides(fill = guide_legend(override.aes = aes(label = "")))
  geom_label_args_list <- list(mapping = aes(label = paste0(round(100 * 
                                                                    pct_missing, 2), "%")))
  output <- output + do.call("geom_label", c(geom_label_args_list, 
                                             geom_label_args))
  class(output) <- c("single", class(output))
  plotDataExplorer(plot_obj = output, title = title, ggtheme = ggtheme, 
                   theme_config = theme_config)
}

[boxuancui]

Thank you for the suggestion, but both profile_missing and plot_missing are designed towards detecting "missingness". Unfortunately, there is no plan to add a similar function for "completeness", since it really duplicates the function of plot_missing.

To address your concern, you can always update this code chunk so that you can incorporate your proposed plot_missing2. However, I'd propose naming it something like plot_completeness or similar, so that it doesn't create confusion later.

[steinjm]

Alright, that's fair! Thanks for the tips, and keep up the good work!

[boxuancui]

Thank you for using DataExplorer!