I have a problem regarding alignment when using geom_col. I attach a reproducible example and the plot. What I would like to get are bars on top of each other on different weapons but aligned to the bottom without empty space, to make the plot more compact, even if this ignore some kind of ordering of y-axis. Solutions like transforming missing or 0 values to NA didn’t work (ggplot2 does ignore NA automatically), I think the problem is some kind of conflict with facet_grid2, since specifying one particular year and room, there is not this problem.

   library(dplyr)
   library(ggplot2)
   library(ggiraph)
   library(ggh4x)

    # Data with Cluedo theme
    set.seed(123)
    cluedo_data <- data.frame(
      SUSPECT_ID = 1:100,
      YEAR = sample(2018:2020, 100, replace = TRUE),
      ROOM = sample(c("Library", "Kitchen", "Conservatory"), 100, replace = TRUE),
      GENDER = sample(c("M", "F"), 100, replace = TRUE),
      CLUEDO_PATH = sample(c("New", "Old"), 100, replace = TRUE),
      WEAPON_ID = paste0("weapon_", sample(1:10, 100, replace = TRUE)),
      CLUE_TYPE = sample(c("OPEN", "MCQ"), 100, replace = TRUE),
      EVIDENCE = sample(c(-1, 0, 1), 100, replace = TRUE),
      SCORE = sample(0:10, 100, replace = TRUE)
    )
    
    # Filter and transform data
    open_scores <- cluedo_data %>%
      filter(CLUE_TYPE == "OPEN", CLUEDO_PATH == "New") %>%
      group_by(YEAR, SUSPECT_ID, ROOM, WEAPON_ID) %>%
      filter(sum(abs(EVIDENCE)) != 0) %>%
      distinct(SUSPECT_ID, .keep_all = TRUE) %>% 
      mutate(TOTAL = max(sum(SCORE), 0)) %>%
      ungroup() %>%
      group_by(YEAR, ROOM, WEAPON_ID) %>%
      top_n(1, TOTAL) %>%
      distinct(YEAR, WEAPON_ID, ROOM, GENDER, TOTAL) %>%
      ungroup()
    
    open_scores$WEAPON_ID <- gsub('weapon_', 'w', open_scores$WEAPON_ID)
    
    color_table <- tibble(gender = c("M", "F"), Color = c("#795695", "#00868b"))
    open_scores$GENDER <- factor(open_scores$GENDER, levels = color_table$gender)
    
    plt <- ggplot(open_scores) +
      geom_col(aes(TOTAL, WEAPON_ID, fill = GENDER), width = 0.6, position = "stack") +
      geom_text(data = open_scores, aes(x = 1, y = WEAPON_ID, label = WEAPON_ID), hjust = "inward", nudge_x = -0.5, colour = "white", size = 4) +
      geom_text(data = open_scores, aes(x = TOTAL, y = WEAPON_ID, label = ifelse(TOTAL == 0, NA, TOTAL), fill = GENDER), position = position_stack(vjust = 0.6), colour = "white", size = 4) + 
      facet_grid2(vars(ROOM), vars(YEAR), render_empty = FALSE, axes = "all", scales = "free", space = "free") +
      scale_fill_manual(values = color_table$Color) +
      theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.ticks.x = element_blank(), axis.ticks.y = element_blank()) +
      scale_x_continuous(breaks = NULL) +
      scale_y_discrete(breaks = NULL) +
      theme(axis.title.x = element_text(size = 15), axis.title.y = element_text(size = 15), strip.text.x = element_text(size = 13), strip.text.y = element_text(size = 13), legend.text = element_text(size = 20), legend.title = element_text(size = 20)) + 
      theme(legend.position = "top", plot.title = element_text(hjust = 0.5)) +
      xlab("Mean SCORE of Clues per WEAPON through YEAR") +
      ylab("WEAPON") +
      theme(text = element_text(family = "mono"))
    
    plt <- girafe(ggobj = plt, width_svg = 18, height_svg = 11,
      options = list(
        opts_hover_inv(css = "opacity:0.7;"),
        opts_hover(css = "stroke-width:2;")
      ))
    
    # Print plot
    print(plt)