diff --git a/DESCRIPTION b/DESCRIPTION
index 804387e3f..25385cea2 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -69,6 +69,7 @@ Imports:
     tools,
     utils
 Suggests:
+    formatters (>= 0.5.11),
     knitr (>= 1.42),
     logger (>= 0.4.0),
     nestcolor (>= 0.1.0),
diff --git a/R/teal.modules.general.R b/R/teal.modules.general.R
index 82f61a562..62c385d91 100644
--- a/R/teal.modules.general.R
+++ b/R/teal.modules.general.R
@@ -15,11 +15,11 @@
 #' @keywords internal
 "_PACKAGE"
 
-# nolint start
+# nolint start.
 # Note ggmosaic (version <= 0.3.3) needs to be in DEPENDS as the following does not work if it is imported
 # df <- data.frame(x = c("A", "B", "C", "A"), y = c("Z", "Z", "W", "W"))
 # ggplot(df) + ggmosaic::geom_mosaic(aes(x = ggmosaic::product(x), fill = y))
-# nolint end
+# nolint end.
 
 # Needed to avoid R CMD note on no visible binding
 utils::globalVariables("count")
diff --git a/R/tm_a_pca.R b/R/tm_a_pca.R
index d2dac0c08..ab842dd84 100644
--- a/R/tm_a_pca.R
+++ b/R/tm_a_pca.R
@@ -436,7 +436,7 @@ srv_a_pca <- function(id, data, dat, plot_height, plot_width, ggplot2_args, deco
           teal.reporter::teal_card(obj),
           teal.reporter::teal_card("## Module's output(s)")
         )
-      teal.code::eval_code(obj, 'library("ggplot2");library("dplyr");library("tidyr")') # nolint: quotes
+      teal.code::eval_code(obj, "library(ggplot2);library(dplyr);library(tidyr)")
     })
     anl_merged_q <- reactive({
       req(anl_merged_input())
diff --git a/R/tm_a_regression.R b/R/tm_a_regression.R
index d0ce394b3..9440fc0da 100644
--- a/R/tm_a_regression.R
+++ b/R/tm_a_regression.R
@@ -461,7 +461,7 @@ srv_a_regression <- function(id,
           teal.reporter::teal_card(obj),
           teal.reporter::teal_card("## Module's output(s)")
         )
-      teal.code::eval_code(obj, 'library("ggplot2");library("dplyr")') # nolint: quotes
+      teal.code::eval_code(obj, "library(ggplot2);library(dplyr)")
     })
 
     anl_merged_q <- reactive({
diff --git a/R/tm_data_table.R b/R/tm_data_table.R
index 6fcfe4325..47d21cbfc 100644
--- a/R/tm_data_table.R
+++ b/R/tm_data_table.R
@@ -309,7 +309,7 @@ srv_data_table <- function(id,
       teal::validate_has_data(df, min_nrow = 1L, msg = paste("data", dataname, "is empty"))
       qenv <- teal.code::eval_code(
         data(),
-        'library("dplyr");library("DT")' # nolint: quotes.
+        "library(dplyr);library(DT)"
       )
       teal.code::eval_code(
         qenv,
diff --git a/R/tm_g_association.R b/R/tm_g_association.R
index 13d1c2372..67e5c5c4b 100644
--- a/R/tm_g_association.R
+++ b/R/tm_g_association.R
@@ -151,8 +151,8 @@ tm_g_association <- function(label = "Association",
                              show_association = TRUE,
                              plot_height = c(600, 400, 5000),
                              plot_width = NULL,
-                             distribution_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"), # nolint: line_length.
-                             association_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"), # nolint: line_length.
+                             distribution_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"), # nolint line_length_linter.
+                             association_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"), # nolint line_length_linter.
                              pre_output = NULL,
                              post_output = NULL,
                              ggplot2_args = teal.widgets::ggplot2_args(),
@@ -345,7 +345,7 @@ srv_tm_g_association <- function(id,
           teal.reporter::teal_card(obj),
           teal.reporter::teal_card("## Module's output(s)")
         )
-      teal.code::eval_code(obj, 'library("ggplot2");library("dplyr");library("ggmosaic")') # nolint: quotes
+      teal.code::eval_code(obj, "library(ggplot2);library(dplyr);library(ggmosaic)")
     })
     anl_merged_q <- reactive({
       req(anl_merged_input())
diff --git a/R/tm_g_bivariate.R b/R/tm_g_bivariate.R
index bffecd3f3..ee25950ec 100644
--- a/R/tm_g_bivariate.R
+++ b/R/tm_g_bivariate.R
@@ -558,9 +558,9 @@ srv_g_bivariate <- function(id,
           teal.reporter::teal_card(obj),
           teal.reporter::teal_card("## Module's output(s)")
         )
-      obj %>%
-        teal.code::eval_code('library("ggplot2");library("dplyr")') %>%
-        teal.code::eval_code(as.expression(anl_merged_input()$expr)) # don't mix char with expr in single eval_code
+      obj |>
+        teal.code::eval_code("library(ggplot2);library(dplyr)") |>
+        teal.code::eval_code(as.expression(anl_merged_input()$expr))
     })
 
     merged <- list(
diff --git a/R/tm_g_distribution.R b/R/tm_g_distribution.R
index 5fda712e6..61e4d38f4 100644
--- a/R/tm_g_distribution.R
+++ b/R/tm_g_distribution.R
@@ -523,7 +523,7 @@ srv_distribution <- function(id,
     )
 
     qenv <- reactive(
-      teal.code::eval_code(data(), 'library("ggplot2");library("dplyr")') # nolint quotes
+      teal.code::eval_code(data(), "library(ggplot2);library(dplyr)")
     )
 
     anl_merged_q <- reactive({
@@ -663,7 +663,7 @@ srv_distribution <- function(id,
             "Group by variable must be `factor`, `character`, or `integer`"
           )
         )
-        qenv <- teal.code::eval_code(qenv, 'library("forcats")') # nolint quotes
+        qenv <- teal.code::eval_code(qenv, "library(forcats)")
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
@@ -681,7 +681,7 @@ srv_distribution <- function(id,
           )
         )
 
-        qenv <- teal.code::eval_code(qenv, 'library("forcats")') # nolint quotes
+        qenv <- teal.code::eval_code(qenv, "library(forcats)")
         qenv <- teal.code::eval_code(
           qenv,
           substitute(
@@ -891,7 +891,7 @@ srv_distribution <- function(id,
         }
 
         if (length(t_dist) != 0 && main_type_var == "Density" && length(g_var) == 0 && length(s_var) == 0) {
-          qenv <- teal.code::eval_code(qenv, 'library("ggpp")') # nolint quotes
+          qenv <- teal.code::eval_code(qenv, "library(ggpp)")
           qenv <- teal.code::eval_code(
             qenv,
             substitute(
@@ -1037,7 +1037,7 @@ srv_distribution <- function(id,
         )
 
         if (length(t_dist) != 0 && length(g_var) == 0 && length(s_var) == 0) {
-          qenv <- teal.code::eval_code(qenv, 'library("ggpp")') # nolint quotes
+          qenv <- teal.code::eval_code(qenv, "library(ggpp)")
           qenv <- teal.code::eval_code(
             qenv,
             substitute(
@@ -1233,7 +1233,7 @@ srv_distribution <- function(id,
         qenv <- common_q()
 
         if (length(s_var) == 0 && length(g_var) == 0) {
-          qenv <- teal.code::eval_code(qenv, 'library("generics")') # nolint quotes
+          qenv <- teal.code::eval_code(qenv, "library(generics)")
           qenv <- teal.code::eval_code(
             qenv,
             substitute(
@@ -1247,7 +1247,7 @@ srv_distribution <- function(id,
             )
           )
         } else {
-          qenv <- teal.code::eval_code(qenv, 'library("tidyr")') # nolint quotes
+          qenv <- teal.code::eval_code(qenv, "library(tidyr)")
           qenv <- teal.code::eval_code(
             qenv,
             substitute(
diff --git a/R/tm_g_response.R b/R/tm_g_response.R
index 12c0a96b9..6871565ac 100644
--- a/R/tm_g_response.R
+++ b/R/tm_g_response.R
@@ -387,7 +387,7 @@ srv_g_response <- function(id,
     )
 
     qenv <- reactive(
-      teal.code::eval_code(data(), 'library("ggplot2");library("dplyr")') # nolint quotes
+      teal.code::eval_code(data(), "library(ggplot2);library(dplyr)")
     )
 
     anl_merged_q <- reactive({
@@ -520,7 +520,7 @@ srv_g_response <- function(id,
             resp_cl = resp_cl,
             hjust_value = if (swap_axes) "left" else "middle",
             vjust_value = if (swap_axes) "middle" else -1,
-            position_anl2_value = if (!freq) quote(position_fill(0.5)) else quote(position_stack(0.5)), # nolint: line_length.
+            position_anl2_value = if (!freq) quote(position_fill(0.5)) else quote(position_stack(0.5)), # nolint line_length_linter
             anl3_y = if (!freq) 1.1 else as.name("ns"),
             position_anl3_value = if (!freq) "fill" else "stack"
           )
diff --git a/R/tm_g_scatterplot.R b/R/tm_g_scatterplot.R
index acb5c4890..7afd9f013 100644
--- a/R/tm_g_scatterplot.R
+++ b/R/tm_g_scatterplot.R
@@ -587,7 +587,7 @@ srv_g_scatterplot <- function(id,
         teal.reporter::teal_card(obj),
         teal.reporter::teal_card("## Module's output(s)")
       )
-      teal.code::eval_code(data(), 'library("ggplot2");library("dplyr")') # nolint quotes
+      teal.code::eval_code(data(), "library(ggplot2);library(dplyr)")
     })
 
     anl_merged_q <- reactive({
diff --git a/R/tm_g_scatterplotmatrix.R b/R/tm_g_scatterplotmatrix.R
index 1d7a2eb08..ae7ad79a8 100644
--- a/R/tm_g_scatterplotmatrix.R
+++ b/R/tm_g_scatterplotmatrix.R
@@ -330,7 +330,7 @@ srv_g_scatterplotmatrix <- function(id,
         teal.reporter::teal_card(obj),
         teal.reporter::teal_card("## Module's output(s)")
       )
-      qenv <- teal.code::eval_code(obj, 'library("dplyr");library("lattice")') # nolint quotes
+      qenv <- teal.code::eval_code(obj, "library(dplyr);library(lattice)")
       teal.code::eval_code(qenv, as.expression(anl_merged_input()$expr))
     })
 
diff --git a/R/tm_missing_data.R b/R/tm_missing_data.R
index 46e7afa80..0de1fdb05 100644
--- a/R/tm_missing_data.R
+++ b/R/tm_missing_data.R
@@ -22,6 +22,7 @@
 #' This module generates the following objects, which can be modified in place using decorators:
 #' - `summary_plot` (`ggplot`)
 #' - `combination_plot` (`grob` created with [ggplot2::ggplotGrob()])
+#' - `by_variable_plot` (`ggplot`)
 #' - `by_subject_plot` (`ggplot`)
 #'
 #' A Decorator is applied to the specific output using a named list of `teal_transform_module` objects.
@@ -34,6 +35,7 @@
 #'    decorators = list(
 #'      summary_plot = teal_transform_module(...), # applied only to `summary_plot` output
 #'      combination_plot = teal_transform_module(...), # applied only to `combination_plot` output
+#'      by_variable_plot = teal_transform_module(...) # applied only to `by_variable_plot` output
 #'      by_subject_plot = teal_transform_module(...) # applied only to `by_subject_plot` output
 #'    )
 #' )
@@ -228,6 +230,7 @@ srv_page_missing_data <- function(id, data, datanames, parent_dataname,
     })
 
     output$dataset_encodings <- renderUI({
+      req(ggtheme, datanames, is.logical(if_subject_plot))
       tagList(
         lapply(
           datanames,
@@ -314,8 +317,7 @@ ui_missing_data <- function(id, by_subject_plot = FALSE) {
     ),
     tabPanel(
       "By Variable Levels",
-      teal.widgets::get_dt_rows(ns("levels_table"), ns("levels_table_rows")),
-      DT::dataTableOutput(ns("levels_table"))
+      teal.widgets::plot_with_settings_ui(id = ns("by_variable_plot"))
     )
   )
   if (isTRUE(by_subject_plot)) {
@@ -486,6 +488,7 @@ srv_missing_data <- function(id,
     })
 
     data_parent_keys <- reactive({
+      req(data(), parent_dataname)
       if (length(parent_dataname) > 0 && parent_dataname %in% names(data())) {
         keys <- teal.data::join_keys(data())[[dataname]]
         if (parent_dataname %in% names(keys)) {
@@ -500,7 +503,7 @@ srv_missing_data <- function(id,
 
     common_code_q <- reactive({
       teal::validate_inputs(iv_r())
-
+      req(data(), data_r(), input$summary_type)
       group_var <- input$group_by_var
       anl <- data_r()
       obj <- data()
@@ -510,7 +513,7 @@ srv_missing_data <- function(id,
       )
 
       qenv <- teal.code::eval_code(obj, {
-        'library("dplyr");library("ggplot2");library("tidyr");library("gridExtra")' # nolint quotes
+        "library(dplyr);library(ggplot2);library(tidyr);library(gridExtra)"
       })
 
       qenv <- if (!is.null(selected_vars()) && length(selected_vars()) != ncol(anl)) {
@@ -566,13 +569,14 @@ srv_missing_data <- function(id,
     })
 
     selected_vars <- reactive({
-      req(input$variables_select)
+      req(data_keys(), input$variables_select)
       keys <- data_keys()
       vars <- unique(c(keys, input$variables_select))
       vars
     })
 
     vars_summary <- reactive({
+      req(data_r())
       na_count <- data_r() %>%
         sapply(function(x) mean(is.na(x)), USE.NAMES = TRUE) %>%
         sort(decreasing = TRUE)
@@ -586,6 +590,7 @@ srv_missing_data <- function(id,
 
     # Keep encoding panel up-to-date
     output$variables <- renderUI({
+      req(vars_summary(), data_r())
       choices <- split(x = vars_summary()$key, f = vars_summary()$label, drop = TRUE) %>% rev()
       selected <- choices <- unname(unlist(choices))
 
@@ -600,6 +605,7 @@ srv_missing_data <- function(id,
     })
 
     observeEvent(input$filter_na, {
+      req(vars_summary(), data_r())
       choices <- vars_summary() %>%
         dplyr::select(!!as.name("key")) %>%
         getElement(name = 1)
@@ -618,6 +624,7 @@ srv_missing_data <- function(id,
     })
 
     output$group_by_var_ui <- renderUI({
+      req(data_r())
       all_choices <- teal.transform::variable_choices(data_r())
       cat_choices <- all_choices[!sapply(data_r(), function(x) is.numeric(x) || inherits(x, "POSIXct"))]
       validate(
@@ -638,10 +645,10 @@ srv_missing_data <- function(id,
     })
 
     output$group_by_vals_ui <- renderUI({
-      req(input$group_by_var)
+      req(isolate(prev_group_by_var()), input$group_by_var, data_r())
 
       choices <- teal.transform::value_choices(data_r(), input$group_by_var, input$group_by_var)
-      prev_choices <- isolate(input$group_by_vals)
+      prev_choices <- req(isolate(input$group_by_vals))
 
       # determine selected value based on filtered data
       # display those previously selected values that are still available
@@ -674,8 +681,7 @@ srv_missing_data <- function(id,
     })
 
     combination_cutoff_q <- reactive({
-      req(common_code_q())
-      qenv <- common_code_q()
+      qenv <- req(common_code_q())
       teal.reporter::teal_card(qenv) <- c(teal.reporter::teal_card(qenv), "### Combination Plot")
       teal.code::eval_code(
         qenv,
@@ -690,6 +696,7 @@ srv_missing_data <- function(id,
     })
 
     output$cutoff <- renderUI({
+      req(combination_cutoff_q())
       x <- combination_cutoff_q()[["combination_cutoff"]]$n
 
       # select 10-th from the top
@@ -713,9 +720,9 @@ srv_missing_data <- function(id,
 
     summary_plot_q <- reactive({
       req(input$summary_type == "Summary") # needed to trigger update on tab change
-      teal::validate_has_data(data_r(), 1)
-
-      qenv <- common_code_q()
+      teal::validate_has_data(req(data_r()), 1)
+      req(data_keys(), input$ggtheme)
+      qenv <- req(common_code_q())
       if (input$any_na) {
         new_col_name <- "**anyna**"
         qenv <- teal.code::eval_code(
@@ -764,7 +771,7 @@ srv_missing_data <- function(id,
         )
 
       # always set "**anyna**" level as the last one
-      if (isolate(input$any_na)) {
+      if (req(isolate(input$any_na))) {
         qenv <- teal.code::eval_code(
           qenv,
           quote(x_levels <- c(setdiff(x_levels, "**anyna**"), "**anyna**"))
@@ -920,8 +927,11 @@ srv_missing_data <- function(id,
     })
 
     combination_plot_q <- reactive({
-      req(input$summary_type == "Combinations", input$combination_cutoff, combination_cutoff_q())
-      teal::validate_has_data(data_r(), 1)
+      req(
+        input$summary_type == "Combinations", input$combination_cutoff,
+        combination_cutoff_q(), data_keys(), input$ggtheme
+      )
+      teal::validate_has_data(req(data_r()), 1)
 
       qenv <- teal.code::eval_code(
         combination_cutoff_q(),
@@ -1054,12 +1064,12 @@ srv_missing_data <- function(id,
       })
     })
 
-    summary_table_q <- reactive({
+    by_variable_plot_q <- reactive({
       req(
         input$summary_type == "By Variable Levels", # needed to trigger update on tab change
         common_code_q()
       )
-      teal::validate_has_data(data_r(), 1)
+      teal::validate_has_data(req(data_r()), 1)
 
       # extract the ANL dataset for use in further validation
       anl <- common_code_q()[["ANL"]]
@@ -1090,13 +1100,13 @@ srv_missing_data <- function(id,
         function(x) round(sum(is.na(x)) / length(x), 4)
       }
 
-      qenv <- common_code_q()
+      qenv <- req(common_code_q())
       teal.reporter::teal_card(qenv) <- c(teal.reporter::teal_card(qenv), "### Summary Table")
 
       qenv <- if (!is.null(group_var)) {
         common_code_libraries_q <- teal.code::eval_code(
           qenv,
-          'library("forcats");library("glue")' # nolint
+          "library(forcats);library(glue)"
         )
         teal.code::eval_code(
           common_code_libraries_q,
@@ -1136,21 +1146,124 @@ srv_missing_data <- function(id,
         )
       }
 
-      within(qenv, {
-        table <- rtables::df_to_tt(summary_data)
-        table
-      })
+      dev_ggplot2_args <- teal.widgets::ggplot2_args(
+        labs = list(
+          fill = if (input$count_type == "counts") "Missing counts" else "Missing percentage",
+          y = NULL
+        )
+      )
+
+      all_ggplot2_args <- teal.widgets::resolve_ggplot2_args(
+        user_plot = ggplot2_args[["By Variable Levels"]],
+        user_default = ggplot2_args$default,
+        module_plot = dev_ggplot2_args
+      )
+
+      parsed_ggplot2_args <- teal.widgets::parse_ggplot2_args(
+        all_ggplot2_args,
+        ggtheme = input$ggtheme
+      )
+
+      # convert to ggplot
+      labels <- lapply(qenv$ANL, attr, which = "label")
+      if (!any(lengths(labels))) {
+        ANL_q <- within(qenv, # nolint object_name_linter
+          {
+            keep_columns <- intersect(c(keys, group_var), colnames(ANL))
+            ANL <- ANL %>%
+              filter(group_var_name %in% group_vals) %>%
+              pivot_longer(-keep_columns, values_transform = is.na) %>%
+              summarise(
+                .by = c(group_var_name, name),
+                value = sum(value), perc = value / n()
+              )
+          },
+          keys = join_keys(qenv) |> unlist() |> unique(),
+          group_var_name = as.name(group_var),
+          group_var = group_var,
+          group_vals = group_vals
+        )
+        tile <- within(ANL_q,
+          {
+            by_variable_plot <- ggplot2::ggplot(ANL, ggplot2::aes(group_var_name, name)) +
+              ggplot2::geom_tile(ggplot2::aes(fill = column)) +
+              ggplot2::geom_text(ggplot2::aes(label = scales::percent(perc)),
+                data = . %>% dplyr::filter(perc > 0), color = "white"
+              ) +
+              ggplot2::scale_x_discrete(expand = ggplot2::expansion()) +
+              ggplot2::scale_fill_gradient(high = "#ff2951ff", low = "grey90", labels = labels) +
+              labs +
+              ggthemes
+          },
+          group_var_name = as.name(group_var),
+          column = if (input$count_type == "counts") {
+            as.name("value")
+          } else {
+            as.name("perc")
+          },
+          labs = parsed_ggplot2_args$labs,
+          labels = if (input$count_type == "counts") quote(ggplot2::waiver()) else quote(scales::label_percent()),
+          ggthemes = parsed_ggplot2_args$ggtheme
+        )
+      } else {
+        ANL_q <- within(qenv, # nolint object_name_linter
+          {
+            keep_columns <- intersect(c(keys, group_var), colnames(ANL))
+            labels <- vapply(qenv$ANL, attr, which = "label", FUN.VALUE = character(1L))
+            ANL <- ANL %>%
+              dplyr::filter(group_var_name %in% group_vals) %>%
+              tidyr::pivot_longer(-keep_columns, values_transform = is.na) %>%
+              dplyr::summarise(
+                .by = c(group_var_name, name),
+                value = sum(value), perc = value / n()
+              ) %>%
+              dplyr::mutate(label = labels[name])
+          },
+          keys = join_keys(qenv) |> unlist() |> unique(),
+          group_var_name = as.name(group_var),
+          group_var = group_var,
+          group_vals = group_vals
+        )
+
+        tile <- within(ANL_q,
+          {
+            by_variable_plot <- ggplot2::ggplot(ANL, ggplot2::aes(group_var_name, label)) +
+              ggplot2::geom_tile(ggplot2::aes(fill = column)) +
+              ggplot2::geom_text(ggplot2::aes(label = scales::percent(perc)),
+                data = . %>% dplyr::filter(perc > 0), color = "white"
+              ) +
+              ggplot2::scale_x_discrete(expand = ggplot2::expansion()) +
+              ggplot2::scale_fill_gradient(high = "#ff2951ff", low = "grey90", labels = labels) +
+              labs +
+              ggthemes
+          },
+          group_var_name = as.name(group_var),
+          column = if (input$count_type == "counts") {
+            as.name("value")
+          } else {
+            as.name("perc")
+          },
+          labs = parsed_ggplot2_args$labs,
+          labels = if (input$count_type == "counts") quote(ggplot2::waiver()) else quote(scales::label_percent()),
+          ggthemes = parsed_ggplot2_args$ggtheme
+        )
+      }
+
+      tile
     })
 
     by_subject_plot_q <- reactive({
       # needed to trigger update on tab change
-      req(input$summary_type == "Grouped by Subject", common_code_q())
+      req(
+        input$summary_type == "Grouped by Subject", common_code_q(),
+        input$ggtheme
+      )
 
-      teal::validate_has_data(data_r(), 1)
+      teal::validate_has_data(req(data_r()), 1)
 
       dev_ggplot2_args <- teal.widgets::ggplot2_args(
-        labs = list(x = "", y = ""),
-        theme = list(legend.position = "bottom", axis.text.x = quote(ggplot2::element_blank()))
+        labs = list(x = NULL, y = NULL),
+        theme = list(legend.position = "bottom", axis.text.x = NULL)
       )
 
       all_ggplot2_args <- teal.widgets::resolve_ggplot2_args(
@@ -1171,7 +1284,7 @@ srv_missing_data <- function(id,
         function(x) paste(as.integer(x), collapse = "")
       }
 
-      qenv <- common_code_q()
+      qenv <- req(common_code_q())
       teal.reporter::teal_card(qenv) <- c(teal.reporter::teal_card(qenv), "### By Subject Plot")
 
       qenv <- teal.code::eval_code(
@@ -1285,11 +1398,11 @@ srv_missing_data <- function(id,
       })
     )
 
-    decorated_summary_table_q <- srv_decorate_teal_data(
-      id = "dec_summary_table",
-      data = summary_table_q,
-      decorators = select_decorators(decorators, "table"),
-      expr = quote(table)
+    decorated_by_variable_plot_q <- srv_decorate_teal_data(
+      id = "dec_by_variable_plot",
+      data = by_variable_plot_q,
+      decorators = select_decorators(decorators, "by_variable_plot"),
+      expr = quote(by_variable_plot)
     )
 
     decorated_by_subject_plot_q <- srv_decorate_teal_data(
@@ -1309,22 +1422,8 @@ srv_missing_data <- function(id,
       req(decorated_combination_plot_q())[["combination_plot"]]
     })
 
-    summary_table_r <- reactive({
-      q <- req(decorated_summary_table_q())
-
-      if (length(input$variables_select) == 0) {
-        # so that zeroRecords message gets printed
-        # using tibble as it supports weird column names, such as " "
-        DT::datatable(
-          tibble::tibble(` ` = logical(0)),
-          options = list(
-            language = list(zeroRecords = "No variable selected."),
-            pageLength = input$levels_table_rows
-          )
-        )
-      } else {
-        DT::datatable(q[["summary_data"]])
-      }
+    by_variable_plot_r <- reactive({
+      req(decorated_by_variable_plot_q())[["by_variable_plot"]]
     })
 
     by_subject_plot_r <- reactive({
@@ -1346,9 +1445,14 @@ srv_missing_data <- function(id,
       width = plot_width
     )
 
-    output$levels_table <- DT::renderDataTable(summary_table_r())
-
     pws3 <- teal.widgets::plot_with_settings_srv(
+      id = "by_variable_plot",
+      plot_r = by_variable_plot_r,
+      height = plot_height,
+      width = plot_width
+    )
+
+    pws4 <- teal.widgets::plot_with_settings_srv(
       id = "by_subject_plot",
       plot_r = by_subject_plot_r,
       height = plot_height,
@@ -1360,8 +1464,11 @@ srv_missing_data <- function(id,
     decorated_combination_plot_dims_q <- # nolint: object_length_linter.
       set_chunk_dims(pws2, decorated_combination_plot_q)
 
+    decorated_by_variable_plot_dims_q <- # nolint: object_length_linter.
+      set_chunk_dims(pws3, decorated_by_variable_plot_q)
+
     decorated_by_subject_plot_dims_q <- # nolint: object_length_linter.
-      set_chunk_dims(pws3, decorated_by_subject_plot_q)
+      set_chunk_dims(pws4, decorated_by_subject_plot_q)
 
     decorated_final_q <- reactive({
       sum_type <- req(input$summary_type)
@@ -1370,7 +1477,7 @@ srv_missing_data <- function(id,
       } else if (sum_type == "Combinations") {
         decorated_combination_plot_dims_q()
       } else if (sum_type == "By Variable Levels") {
-        decorated_summary_table_q()
+        decorated_by_variable_plot_dims_q()
       } else if (sum_type == "Grouped by Subject") {
         decorated_by_subject_plot_dims_q()
       }
diff --git a/R/tm_outliers.R b/R/tm_outliers.R
index ff67b4569..e53f021f4 100644
--- a/R/tm_outliers.R
+++ b/R/tm_outliers.R
@@ -452,7 +452,7 @@ srv_outliers <- function(id, data, outlier_var,
       req(anl_merged_input())
       teal.code::eval_code(
         data_obj(),
-        'library("dplyr");library("tidyr");library("tibble");library("ggplot2")' # nolint quotes
+        "library(dplyr);library(tidyr);library(tibble);library(ggplot2)"
       ) %>%
         teal.code::eval_code(as.expression(anl_merged_input()$expr))
     })
@@ -738,10 +738,11 @@ srv_outliers <- function(id, data, outlier_var,
               categorical_var_name = as.name(categorical_var)
             )
           )
-        ) |> within({
-          table <- rtables::df_to_tt(summary_data)
-          table
-        })
+        ) |>
+          within({
+            table <- rtables::df_to_tt(summary_data)
+            table
+          })
       } else {
         msg <- "No categorical variable selected, summary table cannot be created."
         showNotification(msg,
diff --git a/R/tm_t_crosstable.R b/R/tm_t_crosstable.R
index 344326741..d0c8d395a 100644
--- a/R/tm_t_crosstable.R
+++ b/R/tm_t_crosstable.R
@@ -331,7 +331,7 @@ srv_t_crosstable <- function(id, data, label, x, y, remove_zero_columns, basic_t
           teal.reporter::teal_card(obj),
           teal.reporter::teal_card("## Module's output(s)")
         )
-      teal.code::eval_code(obj, 'library("rtables");library("tern");library("dplyr")') # nolint quotes
+      teal.code::eval_code(obj, "library(rtables);library(tern);library(dplyr)")
     })
     anl_merged_q <- reactive({
       req(anl_merged_input())
diff --git a/man/tm_missing_data.Rd b/man/tm_missing_data.Rd
index 25244f9c6..1b9543d2f 100644
--- a/man/tm_missing_data.Rd
+++ b/man/tm_missing_data.Rd
@@ -84,6 +84,7 @@ This module generates the following objects, which can be modified in place usin
 \itemize{
 \item \code{summary_plot} (\code{ggplot})
 \item \code{combination_plot} (\code{grob} created with \code{\link[ggplot2:ggplotGrob]{ggplot2::ggplotGrob()}})
+\item \code{by_variable_plot} (\code{ggplot})
 \item \code{by_subject_plot} (\code{ggplot})
 }
 
@@ -96,6 +97,7 @@ See code snippet below:
    decorators = list(
      summary_plot = teal_transform_module(...), # applied only to `summary_plot` output
      combination_plot = teal_transform_module(...), # applied only to `combination_plot` output
+     by_variable_plot = teal_transform_module(...) # applied only to `by_variable_plot` output
      by_subject_plot = teal_transform_module(...) # applied only to `by_subject_plot` output
    )
 )
diff --git a/tests/testthat/test-shinytest2-tm_misssing_data.R b/tests/testthat/test-shinytest2-tm_missing_data.R
similarity index 99%
rename from tests/testthat/test-shinytest2-tm_misssing_data.R
rename to tests/testthat/test-shinytest2-tm_missing_data.R
index 73d602f2b..4847feeb3 100644
--- a/tests/testthat/test-shinytest2-tm_misssing_data.R
+++ b/tests/testthat/test-shinytest2-tm_missing_data.R
@@ -14,7 +14,7 @@ app_driver_tm_missing_data <- function() {
   })
 
   init_teal_app_driver(
-    teal::init(
+    app = init(
       data = data,
       modules = tm_missing_data(
         label = "Missing data",
@@ -42,7 +42,6 @@ test_that("e2e - tm_missing_data: Initializes without errors", {
   app_driver <- app_driver_tm_missing_data()
 
   app_driver$expect_no_shiny_error()
-
   testthat::expect_equal(app_driver$get_text(".teal-modules-tree .active"), "Missing data")
 
   encoding_dataset <- app_driver$get_text(paste(app_driver$namespaces(TRUE)$wrapper(NULL), ".help-block"))