diff --git a/DESCRIPTION b/DESCRIPTION
index aa08b33..6b79f11 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -2,7 +2,7 @@ Package: consequencestools
 Type: Package
 Title: Provides Support Tools for Data Analysis and Visualization 
     from the Ultimate Consequences Database
-Version: 0.0.0.9010
+Version: 0.0.0.9011
 Authors@R: 
     person(
     "Carwil", "Bjork-James",
@@ -28,6 +28,7 @@ Imports:
     assertthat,
     dplyr,
     forcats,
+    ggplot2,
     grDevices,
     incase,
     lubridate,
@@ -42,6 +43,7 @@ Imports:
     tidyselect,
     transcats (>= 0.0.0.9002),
     utils,
+    waffle (>= 1.0.2),
     zoo
 Depends: 
     R (>= 3.5)
diff --git a/NAMESPACE b/NAMESPACE
index d8d9695..dd1e510 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -29,11 +29,14 @@ export(clean_pt_variables)
 export(col2hex)
 export(combine_dates)
 export(combine_names)
+export(complete_x_values)
 export(count_events_in_month)
 export(count_ongoing_events)
 export(count_range_by)
 export(department_name_from_id)
 export(displayed_date_string)
+export(domain_filename)
+export(domain_filename_es)
 export(estimated_date)
 export(estimated_date_string)
 export(event_counts_by)
@@ -54,6 +57,8 @@ export(id_for_event)
 export(id_for_municipality)
 export(id_for_municipality_2)
 export(id_for_president)
+export(make_waffle_chart)
+export(make_waffle_chart_tall)
 export(muni_counts_by)
 export(muni_list_with_counts_by)
 export(municipality_name_from_id)
@@ -66,6 +71,7 @@ export(perp_pal)
 export(province_name_from_id)
 export(quasilogical_as_binary)
 export(red_pal)
+export(relabel_pres_admin)
 export(rename_anexo_columns)
 export(render_age)
 export(render_age_es)
@@ -77,6 +83,8 @@ export(repair_name_line_es)
 export(sep_pal)
 export(set_maximums)
 export(share_of_largest_n)
+export(sorted_by_most_frequent)
+export(sorted_by_widest_appearance)
 export(standard_filter)
 export(str_equivalent)
 export(str_equivalent_list)
@@ -85,6 +93,7 @@ export(sv_pal)
 export(top_values_string)
 export(truncate_event_list)
 export(truncate_muni_list)
+export(waffle_counts)
 export(wide_event_outcomes_reactable)
 export(wide_event_outcomes_table)
 import(dplyr)
@@ -113,6 +122,22 @@ importFrom(forcats,fct_collapse)
 importFrom(forcats,fct_explicit_na)
 importFrom(forcats,fct_na_value_to_level)
 importFrom(forcats,fct_relevel)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,coord_equal)
+importFrom(ggplot2,element_blank)
+importFrom(ggplot2,element_line)
+importFrom(ggplot2,element_text)
+importFrom(ggplot2,facet_wrap)
+importFrom(ggplot2,geom_vline)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,guide_legend)
+importFrom(ggplot2,scale_fill_manual)
+importFrom(ggplot2,scale_x_continuous)
+importFrom(ggplot2,scale_x_discrete)
+importFrom(ggplot2,scale_y_continuous)
+importFrom(ggplot2,scale_y_discrete)
+importFrom(ggplot2,theme)
+importFrom(ggplot2,theme_minimal)
 importFrom(grDevices,col2rgb)
 importFrom(grDevices,colorRamp)
 importFrom(grDevices,rgb)
@@ -124,7 +149,9 @@ importFrom(reactable,colDef)
 importFrom(reactablefmtr,nytimes)
 importFrom(rlang,"!!!")
 importFrom(rlang,.data)
+importFrom(rlang,enquo)
 importFrom(rlang,list2)
+importFrom(rlang,quo_name)
 importFrom(rlang,sym)
 importFrom(stringi,stri_trans_general)
 importFrom(stringr,str_c)
@@ -141,4 +168,5 @@ importFrom(tidyselect,any_of)
 importFrom(tidyselect,last_col)
 importFrom(transcats,translated_join_vars)
 importFrom(utils,head)
+importFrom(waffle,geom_waffle)
 importFrom(zoo,as.Date.yearmon)
diff --git a/R/consequencestools-package.R b/R/consequencestools-package.R
index 2e42bb0..d49642a 100644
--- a/R/consequencestools-package.R
+++ b/R/consequencestools-package.R
@@ -22,6 +22,22 @@
 #' @importFrom forcats fct_explicit_na
 #' @importFrom forcats fct_na_value_to_level
 #' @importFrom forcats fct_relevel
+#' @importFrom ggplot2 aes
+#' @importFrom ggplot2 coord_equal
+#' @importFrom ggplot2 element_blank
+#' @importFrom ggplot2 element_line
+#' @importFrom ggplot2 element_text
+#' @importFrom ggplot2 facet_wrap
+#' @importFrom ggplot2 geom_vline
+#' @importFrom ggplot2 ggplot
+#' @importFrom ggplot2 guide_legend
+#' @importFrom ggplot2 scale_fill_manual
+#' @importFrom ggplot2 scale_x_continuous
+#' @importFrom ggplot2 scale_x_discrete
+#' @importFrom ggplot2 scale_y_continuous
+#' @importFrom ggplot2 scale_y_discrete
+#' @importFrom ggplot2 theme
+#' @importFrom ggplot2 theme_minimal
 #' @importFrom grDevices col2rgb
 #' @importFrom grDevices colorRamp
 #' @importFrom grDevices rgb
@@ -31,7 +47,9 @@
 #' @importFrom reactablefmtr nytimes
 #' @importFrom rlang !!!
 #' @importFrom rlang .data
+#' @importFrom rlang enquo
 #' @importFrom rlang list2
+#' @importFrom rlang quo_name
 #' @importFrom rlang sym
 #' @importFrom stringi stri_trans_general
 #' @importFrom stringr str_c
@@ -48,6 +66,7 @@
 #' @importFrom tidyselect last_col
 #' @importFrom transcats translated_join_vars
 #' @importFrom utils head
+#' @importFrom waffle geom_waffle
 #' @importFrom zoo as.Date.yearmon
 ## usethis namespace: end
 NULL
diff --git a/R/filename-tools-subset.R b/R/filename-tools-subset.R
new file mode 100644
index 0000000..0963b81
--- /dev/null
+++ b/R/filename-tools-subset.R
@@ -0,0 +1,42 @@
+#' Generate protest domain filename
+#'
+#' @param protest_domain The protest domain name
+#' @return The corresponding filename for the domain page,
+#'         relative to the root of the website.
+#' @export
+#'
+#' @examples
+#' domain_filename("Rural land")
+domain_filename <- function(protest_domain){
+  # No files for overlapping domains like "Rural land, Partisan politics"
+  name <- stringr::str_replace_all(protest_domain, "\\s+", "-") %>%
+    stringr::str_to_lower() %>%
+    stringi::stri_trans_general("Latin-ASCII")
+  filename <-  str_glue("/domain/{name}.html")
+  return(if_else(stringr::str_detect(protest_domain, ","),
+                 "", # No files for overlapping domains
+                 filename
+  ))
+}
+
+#' Generate Spanish domain filename
+#'
+#' @param protest_domain The protest domain name in Spanish
+#' @return The corresponding filename for the Spanish domain page,
+#'   relative to the root of the website.
+#'
+#' @export
+#'
+#' @examples
+#' domain_filename_es("Campesino")
+domain_filename_es <- function(protest_domain){
+  name <- stringr::str_replace_all(protest_domain, "\\s+", "-") %>%
+    stringr::str_to_lower() %>%
+    stringi::stri_trans_general("Latin-ASCII")
+  filename <-  str_glue("/dominio/{name}.html")
+
+  return(if_else(stringr::str_detect(protest_domain, ","),
+                 "", # No files for overlapping domains
+                 filename
+  ))
+}
diff --git a/R/relabel-pres-admin.R b/R/relabel-pres-admin.R
new file mode 100644
index 0000000..98c4a86
--- /dev/null
+++ b/R/relabel-pres-admin.R
@@ -0,0 +1,52 @@
+#' Relabel presidential administration using presidency_name_table
+#'
+#' Replaces pres_admin values with corresponding values from a specified column
+#' in presidency_name_table (e.g., presidency_year, presidency_initials, etc.)
+#'
+#' @param dataframe The input dataframe containing a pres_admin column
+#' @param output_column The column from presidency_name_table to use for new labels
+#'   (unquoted column name)
+#' @param .input_column The column from presidency_name_table to match against
+#'   pres_admin (default "presidency")
+#' @param keep_original Logical indicating whether to keep the original pres_admin
+#'   column as pres_admin_original (default TRUE)
+#'
+#' @return The dataframe with pres_admin relabeled according to output_column
+#'
+#' @export
+#'
+#' @examples
+#' def <- assign_presidency_levels(deaths_aug24)
+#' def_labeled <- relabel_pres_admin(def, presidency_year)
+#' def_labeled <- relabel_pres_admin(def, presidency_initials)
+#' def_labeled <- relabel_pres_admin(def, presidency_fullname_es, keep_original = TRUE)
+relabel_pres_admin <- function(dataframe, output_column, .input_column="presidency", keep_original = TRUE) {
+  output_col_name <- rlang::ensym(output_column)
+  input_col_name <- rlang::ensym(.input_column)
+
+  result <- dataframe %>%
+    left_join(select(presidency_name_table, {{input_col_name}}, {{output_column}}),
+              by = join_by(pres_admin == {{input_col_name}}))
+
+  if (keep_original) {
+    result <- result %>%
+      rename(pres_admin_original = pres_admin)
+  } else {
+    result <- result %>%
+      select(-pres_admin)
+  }
+
+  result <- result %>%
+    rename(pres_admin = {{output_column}})
+
+  if(length(unique(presidency_name_table[[rlang::as_name(output_col_name)]])) < nrow(presidency_name_table)) {
+    warning("Some new values are ambiguous. pres_admin not returned as a factor.")
+  } else {
+    result <- result %>%
+      # Make pres_admin a factor in the order specified in presidency_name_table
+      mutate(pres_admin = factor(pres_admin,
+                                 levels = presidency_name_table[[rlang::as_name(output_col_name)]]))
+  }
+
+  return(result)
+}
diff --git a/R/sort-var-description.R b/R/sort-var-description.R
new file mode 100644
index 0000000..ad326ad
--- /dev/null
+++ b/R/sort-var-description.R
@@ -0,0 +1,129 @@
+#' Sort variable description by widest appearance across groups
+#'
+#' Reorders the levels and colors in a variable description list based on how
+#' widely each level appears across a grouping variable. Levels that appear in
+#' more groups are ranked higher. For example, sorting protest domains by how
+#' many presidential administrations each domain appears in.
+#'
+#' @param var_description A list containing variable metadata with elements:
+#'   \itemize{
+#'     \item \code{r_variable}: Name of the variable in the dataframe
+#'     \item \code{levels}: Character vector of level names
+#'     \item \code{colors}: Named vector of colors for each level
+#'     \item \code{levels_es}: (Optional) Spanish translations of levels
+#'     \item \code{colors_es}: (Optional) Spanish-named color vector
+#'   }
+#' @param def The dataframe containing the data to analyze
+#' @param grouping_var The variable to group by when calculating width of
+#'   appearance (e.g., pres_admin, year). Use unquoted variable name.
+#'
+#' @return A modified variable description list with levels and colors reordered
+#'   by widest appearance. Includes a new \code{$ranked} element with the
+#'   sorted levels.
+#'
+#' @export
+#' @examples
+#' \dontrun{
+#' # Sort protest domains by how many presidential administrations they appear in
+#' deaths <- assign_protest_domain_levels(deaths_aug24)
+#' pd_sorted <- sorted_by_widest_appearance(
+#'   var_description = lev$protest_domain,
+#'   def = deaths,
+#'   grouping_var = pres_admin
+#' )
+#' }
+sorted_by_widest_appearance <- function(var_description, def, grouping_var) {
+  var_name <- var_description$r_variable
+  var_description$ranked <-
+    count(def, {{grouping_var}}, !!sym(var_name)) %>%  # 2-var frequency table
+    count(!!sym(var_name)) %>% # frequency table of number of
+    # values of the grouping variable, with deaths in each value of the variable
+    arrange(desc(n)) %>%              # ranked downward
+    pull(!!sym(var_name))      # vector of the groups
+  new_var_description <- var_description
+
+  # Get the new order based on ranked
+  new_order <- match(new_var_description$ranked, var_description$levels)
+
+  # Reorder levels
+  new_var_description$levels <- var_description$ranked
+
+  # Reorder levels_es if it exists
+  if (!is.null(var_description$levels_es)) {
+    new_var_description$levels_es <- var_description$levels_es[new_order]
+  }
+
+  # Reorder colors
+  new_var_description$colors <- var_description$colors[new_order]
+
+  # Reorder colors_es if it exists
+  if (!is.null(var_description$colors_es)) {
+    new_var_description$colors_es <- var_description$colors_es[new_order]
+  }
+
+  new_var_description
+}
+
+
+#' Sort variable description by frequency
+#'
+#' Reorders the levels and colors in a variable description list based on
+#' the frequency of each level in the data. More frequent levels are ranked
+#' higher.
+#'
+#' @param var_description A list containing variable metadata with elements:
+#'   \itemize{
+#'     \item \code{r_variable}: Name of the variable in the dataframe
+#'     \item \code{levels}: Character vector of level names
+#'     \item \code{colors}: Named vector of colors for each level
+#'     \item \code{levels_es}: (Optional) Spanish translations of levels
+#'     \item \code{colors_es}: (Optional) Spanish-named color vector
+#'   }
+#' @param def The dataframe containing the data to analyze
+#' @param grouping_var Optional grouping variable (not used, included for
+#'   consistency with \code{sorted_by_widest_appearance})
+#'
+#' @return A modified variable description list with levels and colors reordered
+#'   by frequency. Includes a new \code{$ranked} element with the sorted levels.
+#'
+#' @export
+#' @examples
+#' \dontrun{
+#' deaths <- assign_protest_domain_levels(deaths_aug24)
+#' # Sort protest domains by total frequency
+#' pd_sorted <- sorted_by_most_frequent(
+#'   var_description = lev$protest_domain,
+#'   def = deaths
+#' )
+#' }
+sorted_by_most_frequent <- function(var_description, def, grouping_var = NULL) {
+  # Note: grouping_var parameter is not used but included for API consistency
+
+  var_name <- var_description$r_variable
+  var_description$ranked <-
+    count(def, !!sym(var_name)) %>% # frequency table for the variable in question
+    arrange(desc(n)) %>%              # ranked downward
+    pull(!!sym(var_name))      # vector of the groups
+  new_var_description <- var_description
+
+  # Get the new order based on ranked
+  new_order <- match(new_var_description$ranked, var_description$levels)
+
+  # Reorder levels
+  new_var_description$levels <- var_description$ranked
+
+  # Reorder levels_es if it exists
+  if (!is.null(var_description$levels_es)) {
+    new_var_description$levels_es <- var_description$levels_es[new_order]
+  }
+
+  # Reorder colors
+  new_var_description$colors <- var_description$colors[new_order]
+
+  # Reorder colors_es if it exists
+  if (!is.null(var_description$colors_es)) {
+    new_var_description$colors_es <- var_description$colors_es[new_order]
+  }
+
+  new_var_description
+}
diff --git a/R/waffle-plot-functions.R b/R/waffle-plot-functions.R
new file mode 100644
index 0000000..a15ebcc
--- /dev/null
+++ b/R/waffle-plot-functions.R
@@ -0,0 +1,336 @@
+#' Helper function to create counts dataframe for waffle charts
+#'
+#' @param dataframe The input dataframe containing the data.
+#' @param x_var The variable to facet the waffle chart by (e.g., year).
+#' @param fill_var The variable to color the waffle chart blocks by (e.g.,
+#'   state_responsibility).
+#' @param fill_var_description A list containing the title, levels, and colors
+#'  for the fill variable. Can be taken from our level description list, lev.
+#'
+#' @return A dataframe with counts of occurrences for each combination of x_var
+#'   and fill_var.
+#'
+#' @export
+#' @examples
+#' waffle_counts(dataframe = assign_state_responsibility_levels(deaths_aug24, simplify = TRUE),
+#'  x_var = year, fill_var = state_responsibility,
+#'               fill_var_description = lev$state_responsibility)
+waffle_counts <- function(dataframe, x_var,
+                          fill_var, fill_var_description) {
+  # Ensure the fill variable is properly factored with the correct levels
+  dataframe <- dataframe %>%
+    mutate(across({{ fill_var }},
+                  ~factor(., levels = fill_var_description$levels)))
+
+  # Create the counts dataframe
+  counts_df <- dataframe %>%
+    filter(!is.na(year)) %>%
+    filter(!is.na({{ x_var }})) %>%
+    filter({{ x_var }} != "Unknown") %>%
+    filter(!is.na({{ fill_var }})) %>%
+    dplyr::count({{ x_var }}, {{ fill_var }})
+
+  return(counts_df)
+}
+
+#' New helper function to add null/missing x values
+#'
+#' @param counts_df The counts dataframe from waffle_counts
+#' @param x_var The variable to facet the waffle chart by (e.g., year).
+#' @param fill_var The variable to color the waffle chart blocks by (e.g.,
+#'   state_responsibility).
+#' @param all_levels Optional: All possible levels for the x variable (needed
+#'   for pres_admin)
+#' @param .verbose Logical indicating whether to print debug information
+#' @return The counts dataframe with missing x values added
+#'
+#' @export
+#'
+#' @examples
+#' \donttest{
+#' deaths <- assign_levels(deaths_aug24, "standard", .simplify=TRUE)  %>%
+#'   dplyr::filter(year != 2012)  # Remove 2012
+#' waffle_counts_df <- waffle_counts(deaths,
+#'                                  x_var = year,
+#'                                   fill_var = protest_domain,
+#'                                   fill_var_description = lev$protest_domain)
+#' waffle_counts_df_completed <- complete_x_values(waffle_counts_df,
+#'                                                 x_var = year,
+#'                                                 fill_var = protest_domain,
+#'                                                 all_levels = NULL,
+#'                                                 .verbose = FALSE)
+#' }
+complete_x_values <- function(counts_df, x_var, fill_var,
+                              all_levels = NULL, .verbose = FALSE) {
+  x_var_name <- quo_name(enquo(x_var))
+  existing_values <- unique(counts_df[[x_var_name]])
+
+  null_x_values <- c()
+  range_of_x_levels <- c()
+
+  # Handle year variable
+  if (x_var_name == "year") {
+    min_val <- min(existing_values)
+    max_val <- max(existing_values)
+    range_of_x_levels <- min_val:max_val
+    null_x_values <- setdiff(range_of_x_levels, existing_values)
+
+    if (.verbose) {
+      print(paste("Null values: ", paste(null_x_values, collapse = ", ")))
+    }
+  }
+
+  # Handle pres_admin variable (requires all_levels)
+  if (x_var_name == "pres_admin") {
+    if (is.null(all_levels)) {
+      stop("all_levels must be provided for pres_admin variable")
+    }
+
+    min_idx <- min(match(existing_values, all_levels))
+    max_idx <- max(match(existing_values, all_levels))
+    range_of_x_levels <- all_levels[min_idx:max_idx]
+    null_x_values <- setdiff(range_of_x_levels, existing_values)
+  }
+
+  # Add null rows if any missing values found
+  if (length(null_x_values) > 0) {
+    null_rows <- tibble(
+      {{ x_var }} := null_x_values,
+      {{ fill_var }} := " ",
+      n = 1
+    )
+    counts_df <- bind_rows(counts_df, null_rows)
+  }
+
+  # Re-factor x variable with complete range of levels
+  if (length(range_of_x_levels) > 0) {
+    counts_df <- counts_df %>%
+      mutate(across(1, ~factor(., levels = range_of_x_levels)))
+  }
+
+  if (.verbose) {
+    print(utils::str(counts_df))
+  }
+
+  return(counts_df)
+}
+
+#' Create a waffle chart with facets
+#'
+#' Creates a waffle chart from an overall dataset, both calculating
+#' the relevant counts and formatting the chart.
+#'
+#' @param dataframe The input dataframe containing the data.
+#' @param x_var The variable to facet the waffle chart by (e.g., year
+#'  or pres_admin). This will name the facets.
+#' @param fill_var The variable to color the waffle chart blocks by (e.g.,
+#'   state_responsibility).
+#' @param fill_var_description A list containing the title, levels, and colors
+#'  for the fill variable. Can be taken from our level description list, lev.
+#' @param n_columns Number of columns for the facet wrap.
+#' @param waffle_width Number of rows in each waffle chart (default 10).
+#' @param complete_x Logical indicating whether to complete missing x values
+#'   with a single null block. Only implemented for year and pres_admin.
+#' @param lang Language for the legend labels ("en" or "es"). Default is "en".
+#'   Only affects the legend and not the x-axis label, which should be
+#'   handled before calling the function.
+#' @param .verbose Logical indicating whether to print debug information.
+#'
+#' @return A ggplot object representing the waffle chart.
+#' @export
+#'
+#' @examples
+#' \dontrun{
+#' deaths <- assign_levels(deaths_aug24, "standard", .simplify = TRUE)
+#' make_waffle_chart(deaths,
+#'   x_var = pres_admin,
+#'   fill_var = state_responsibility,
+#'   fill_var_description = state_resp,
+#'   complete_x = TRUE, n_columns = 7)
+#' }
+make_waffle_chart <- function(dataframe, x_var, fill_var,
+                              fill_var_description,
+                              n_columns = 5,
+                              waffle_width = 10,
+                              complete_x = FALSE,
+                              lang = "en",
+                              .verbose = FALSE) {
+  # Get the color palette from the corresponding description variable
+  fill_colors <- fill_var_description$colors
+  fill_legend <- fill_colors
+  if (lang=="es" & "colors_es" %in% names(fill_var_description)){
+    fill_legend <- fill_var_description$colors_es
+    fill_var_description$title <- fill_var_description$title_es
+  }
+
+  x_var_name <- quo_name(enquo(x_var))
+  range_of_x_levels <- list()
+  if(is.factor(dataframe[[x_var_name]])){
+    all_levels <- levels(dataframe[[x_var_name]])
+    range_of_x_levels <- all_levels
+  }
+
+  counts_df <- waffle_counts(dataframe, {{x_var}}, {{fill_var}},
+                             {{fill_var_description}})
+
+  # Complete with null blocks if requested
+  if (complete_x) {
+    # code only implemented for these two variables for now
+    if (x_var_name %in% c("year", "pres_admin")){
+      counts_df <- complete_x_values(counts_df, {{x_var}}, {{fill_var}},
+                                     all_levels = range_of_x_levels,
+                                     .verbose = .verbose)
+
+      # Add null to the color set but not to the legend
+      fill_colors <- c(fill_colors, ' ' = "white")
+      fill_legend <- c(fill_legend, ' ' = "white")
+    }
+  }
+
+  # Create the plot
+  ggplot(counts_df, aes(fill = {{ fill_var }}, values = n)) +
+    waffle::geom_waffle(color = "white", size = .25, n_rows = waffle_width,
+                flip = TRUE, na.rm = TRUE) +
+    facet_wrap(ggplot2::vars({{ x_var }}), ncol = n_columns,
+               labeller = ggplot2::label_wrap_gen(20),
+               strip.position = "bottom") +
+    scale_x_discrete() +
+    scale_y_continuous(breaks = c(0.5, 5.5, 10.5),
+                       labels = function(x) (x-0.5) * waffle_width, # make this multiplier the same as n_rows
+                       expand = c(0,0)) +
+    coord_equal() +
+    scale_fill_manual(name = fill_var_description$title,
+                      values = fill_colors,
+                      limits = names(fill_colors),
+                      labels = names(fill_legend),  # Language specific
+                      breaks = names(fill_colors)) +
+    theme_minimal(base_family = "Roboto Condensed") +
+    theme(panel.grid = element_blank(), axis.ticks.y = element_line(),
+          legend.text = element_text(size = 12),
+          axis.text = element_text(size = 12),
+          strip.text.x = element_text(size = 12)) +
+    ggplot2::guides(fill = guide_legend(reverse = TRUE))
+}
+
+#' Create a tall waffle chart with facets
+#'
+#' Creates a tall-oriented waffle chart from an overall dataset, both calculating
+#' the relevant counts and formatting the chart. Facets are arranged vertically.
+#'
+#' @param dataframe The input dataframe containing the data.
+#' @param x_var The variable to facet the waffle chart by (e.g., year
+#'  or pres_admin). This will name the facets.
+#' @param fill_var The variable to color the waffle chart blocks by (e.g.,
+#'   state_responsibility).
+#' @param fill_var_description A list containing the title, levels, and colors
+#'  for the fill variable. Can be taken from our level description list, lev.
+#' @param n_columns Number of rows for the facet wrap (displayed vertically).
+#' @param complete_x Logical indicating whether to complete missing x values
+#'   with a single null block. Only implemented for year and pres_admin.
+#' @param lang Language for the legend labels ("en" or "es"). Default is "en".
+#'   Only affects the legend and not the x-axis label, which should be
+#'   handled before calling the function.
+#' @param .verbose Logical indicating whether to print debug information.
+#'
+#' @return A ggplot object representing the tall waffle chart.
+#' @export
+#'
+#' @examples
+#' \dontrun{
+#' deaths <- assign_levels(deaths_aug24, "standard", .simplify = TRUE)
+#' make_waffle_chart_tall(deaths,
+#'   x_var = pres_admin,
+#'   fill_var = state_responsibility,
+#'   fill_var_description = lev$state_responsibility,
+#'   complete_x = TRUE, n_columns = 7)
+#'  make_waffle_chart_tall(deaths,
+#'    x_var = pres_admin, fill_var = state_responsibility,
+#'    fill_var_description = lev$state_responsibility,
+#'    complete_x = FALSE, n_columns = 6)
+#'  make_waffle_chart_tall(deaths,
+#'    x_var = pres_admin, fill_var = state_responsibility,
+#'    fill_var_description = lev$state_responsibility,
+#'    complete_x = FALSE, n_columns = 6, lang="es")
+#' }
+make_waffle_chart_tall <- function(dataframe, x_var, fill_var, fill_var_description,
+                                   n_columns = 5,
+                                   complete_x = FALSE,
+                                   lang = "en",
+                                   .verbose = FALSE) {
+  # Get the color palette from the corresponding description variable
+  fill_colors <- fill_var_description$colors
+  fill_legend <- fill_colors
+  if (lang=="es" & "colors_es" %in% names(fill_var_description)){
+    fill_legend <- fill_var_description$colors_es
+    fill_var_description$title <- fill_var_description$title_es
+  }
+
+  x_var_name <- quo_name(enquo(x_var))
+  range_of_x_levels <- list()
+  if(is.factor(dataframe[[x_var_name]])){
+    all_levels <- levels(dataframe[[x_var_name]])
+    range_of_x_levels <- all_levels
+  }
+
+  counts_df <- waffle_counts(dataframe, {{x_var}}, {{fill_var}},
+                             {{fill_var_description}})
+
+  # Complete with null blocks if requested
+  if (complete_x) {
+    # code only implemented for these two variables for now
+    if (x_var_name %in% c("year", "pres_admin")){
+      counts_df <- complete_x_values(counts_df, {{x_var}}, {{fill_var}},
+                                     all_levels = range_of_x_levels,
+                                     .verbose = .verbose)
+
+      # Add null to the color set but not to the legend
+      fill_colors <- c(fill_colors, ' ' = "white")
+      fill_legend <- c(fill_legend, ' ' = "white")
+    }
+  }
+
+  # Define waffle chart parameters
+  waffle_width <- 5
+
+  legend_orientation <- "horizontal"
+  if ((nrow(counts_df) / n_columns) <= 1) {
+    legend_orientation <- "vertical"
+  }
+
+  # Create the plot
+  ggplot(counts_df, aes(fill = {{ fill_var }}, values = n)) +
+    # Remove flip=TRUE to make bars build left to right
+    geom_waffle(color = "white", size = .25, n_rows = waffle_width, na.rm = TRUE) +
+    # Change strip.position to "left" and use nrow instead of ncol
+    facet_wrap(ggplot2::vars({{ x_var }}), nrow = n_columns,
+               labeller = ggplot2::label_wrap_gen(20),
+               strip.position = "left",
+               dir = "v") +
+    scale_x_continuous(breaks = c(0.5, 5.5, 10.5, 15.5, 20.5, 25.5),
+                       labels = function(x) (x-0.5) * waffle_width,
+                       expand = c(0,0)) +
+    # Use scale_y_discrete() instead of scale_x_discrete()
+    scale_y_discrete() +
+    coord_equal() +
+    scale_fill_manual(name = fill_var_description$title,
+                      values = fill_colors,
+                      breaks = names(fill_colors),
+                      labels = names(fill_legend),  # Language specific
+                      guide = guide_legend(reverse = FALSE)) +
+    theme_minimal(base_family = "Roboto Condensed") +
+    # Change axis.ticks.y to axis.ticks.x
+    theme(panel.grid = element_blank(),
+          axis.ticks.x = element_line(),
+          legend.text = element_text(size = 12),
+          axis.text = element_text(size = 12),
+          legend.position = "top",
+          legend.direction = legend_orientation,
+          # Change strip.text.x to strip.text.y
+          strip.text.y.left = element_text(size = 14,
+                                           angle = 0, hjust = 0),
+          strip.placement = "outside",
+          plot.margin = ggplot2::margin(5, 20, 5, 35)) +
+    # add a 1pt solid line at x=0.5 and 1pt grey line at x =20.5
+    geom_vline(xintercept = 0.5, color = "black", linewidth = 0.5) +
+    geom_vline(xintercept = 20.5, color = "darkgrey", linewidth = 0.25)
+}
diff --git a/data-raw/level-variables.R b/data-raw/level-variables.R
index 828b0d4..0ce8a39 100644
--- a/data-raw/level-variables.R
+++ b/data-raw/level-variables.R
@@ -3,6 +3,7 @@ lev <- list()
 president <- list()
 
 president$title <- "Presidential Administration"
+president$title_es <- "Administración presidencial"
 president$r_variable <- "pres_admin"
 president$levels <- c(
   "Hernán Siles Zuazo", "Víctor Paz Estenssoro", "Jaime Paz Zamora",
@@ -35,6 +36,7 @@ usethis::use_data(president, overwrite=TRUE)
 
 location_precision <- list()
 location_precision$title <- "Location Precision"
+location_precision$title_es <- "Precisión de la ubicación"
 location_precision$r_variable <- "location_precision"
 location_precision$levels <- c(
   "address", "poi_small", "intersection",
@@ -47,11 +49,12 @@ lev$location_precision <- location_precision
 
 state_resp <- list()
 state_resp$title <- "State Responsibility"
+state_resp$title_es <- "Responsabilidad del Estado"
 state_resp$r_variable <- "state_responsibility"
 state_resp$levels <- c("Perpetrator", "Victim", "Involved", "Separate", "Unintentional", "Unknown")
 state_resp$colors <-  c(
   Perpetrator = "forestgreen",
-  Victim = "#cd6600",                  # "darkorange3",
+  Victim = "#8B1A1A",                  # "firebrick4",
   Involved = "#90ee90",                # "lightgreen",
   Separate = "#eeb422",                # "goldenrod2",
   Unintentional = "darkgray",
@@ -59,7 +62,7 @@ state_resp$colors <-  c(
 
 state_resp$colors_es <-  c(
   Perpetrador = "forestgreen",
-  Victima = "#cd6600",                  # "darkorange3",
+  Victima = "#8B1A1A",                  # "firebrick4",
   Involucrado = "#90ee90",                # "lightgreen",
   Separado = "#eeb422",                # "goldenrod2",
   "No Intencional" = "darkgray",
@@ -124,11 +127,12 @@ assign_protest_domain.colors <- function() {
 
 protest_domains <- list()
 protest_domains$title <- "Protest Domain"
+protest_domains$title_es <- "Dominio de protesta"
 protest_domains$r_variable <- "protest_domain"
 protest_domains$levels <- protest_domain.grouped
 protest_domains$colors <- assign_protest_domain.colors()
 
-lev$protest_domain <- protest_domain
+lev$protest_domain <- protest_domains
 usethis::use_data(protest_domains, overwrite=TRUE)
 
 # Affiliations
@@ -244,6 +248,7 @@ assign_affiliation.colors <- function() {
 
 affiliations <- list()
 affiliations$title <- "Affiliation"
+affiliations$title_es <- "Afiliación"
 affiliations$r_variable <- "affiliation"
 affiliations$levels <- affiliation.grouped
 affiliations$levels_es <- affiliation.grouped_es
@@ -253,14 +258,17 @@ usethis::use_data(affiliations, overwrite = TRUE)
 
 lev$dec_affiliation <- affiliations
 lev$dec_affiliation$title <- "Deceased Affiliation"
+lev$dec_affiliation$title_es <- "Afiliación del fallecido"
 lev$dec_affiliation$r_variable <- "dec_affiliation"
 lev$perp_affiliation <- affiliations
 lev$perp_affiliation$title <- "Perpetrator Affiliation"
+lev$perp_affiliation$title_es <- "Afiliación del perpetrador"
 lev$perp_affiliation$r_variable <- "perp_affiliation"
 
 departments <- list()
 
 departments$title <- "Department"
+departments$title_es <- "Departamento"
 departments$r_variable <- "department"
 departments$levels <- c("Beni", "Chuquisaca", "Cochabamba", "La Paz", "Oruro", "Pando",
                         "Potosí", "Santa Cruz", "Tarija", "Unknown")
diff --git a/data/affiliations.rda b/data/affiliations.rda
index 64852dc..b5f2617 100644
Binary files a/data/affiliations.rda and b/data/affiliations.rda differ
diff --git a/data/departments.rda b/data/departments.rda
index eb912e8..2eeb09a 100644
Binary files a/data/departments.rda and b/data/departments.rda differ
diff --git a/data/president.rda b/data/president.rda
index 7732de9..89df703 100644
Binary files a/data/president.rda and b/data/president.rda differ
diff --git a/data/protest_domains.rda b/data/protest_domains.rda
index b76ba6e..11d3ce6 100644
Binary files a/data/protest_domains.rda and b/data/protest_domains.rda differ
diff --git a/data/state_resp.rda b/data/state_resp.rda
index 614a1c6..fdcf2ee 100644
Binary files a/data/state_resp.rda and b/data/state_resp.rda differ
diff --git a/man/complete_x_values.Rd b/man/complete_x_values.Rd
new file mode 100644
index 0000000..c41339a
--- /dev/null
+++ b/man/complete_x_values.Rd
@@ -0,0 +1,48 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/waffle-plot-functions.R
+\name{complete_x_values}
+\alias{complete_x_values}
+\title{New helper function to add null/missing x values}
+\usage{
+complete_x_values(
+  counts_df,
+  x_var,
+  fill_var,
+  all_levels = NULL,
+  .verbose = FALSE
+)
+}
+\arguments{
+\item{counts_df}{The counts dataframe from waffle_counts}
+
+\item{x_var}{The variable to facet the waffle chart by (e.g., year).}
+
+\item{fill_var}{The variable to color the waffle chart blocks by (e.g.,
+state_responsibility).}
+
+\item{all_levels}{Optional: All possible levels for the x variable (needed
+for pres_admin)}
+
+\item{.verbose}{Logical indicating whether to print debug information}
+}
+\value{
+The counts dataframe with missing x values added
+}
+\description{
+New helper function to add null/missing x values
+}
+\examples{
+\donttest{
+deaths <- assign_levels(deaths_aug24, "standard", .simplify=TRUE)  \%>\%
+  dplyr::filter(year != 2012)  # Remove 2012
+waffle_counts_df <- waffle_counts(deaths,
+                                 x_var = year,
+                                  fill_var = protest_domain,
+                                  fill_var_description = lev$protest_domain)
+waffle_counts_df_completed <- complete_x_values(waffle_counts_df,
+                                                x_var = year,
+                                                fill_var = protest_domain,
+                                                all_levels = NULL,
+                                                .verbose = FALSE)
+}
+}
diff --git a/man/domain_filename.Rd b/man/domain_filename.Rd
new file mode 100644
index 0000000..fb3c4d2
--- /dev/null
+++ b/man/domain_filename.Rd
@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/filename-tools-subset.R
+\name{domain_filename}
+\alias{domain_filename}
+\title{Generate protest domain filename}
+\usage{
+domain_filename(protest_domain)
+}
+\arguments{
+\item{protest_domain}{The protest domain name}
+}
+\value{
+The corresponding filename for the domain page,
+        relative to the root of the website.
+}
+\description{
+Generate protest domain filename
+}
+\examples{
+domain_filename("Rural land")
+}
diff --git a/man/domain_filename_es.Rd b/man/domain_filename_es.Rd
new file mode 100644
index 0000000..1251f28
--- /dev/null
+++ b/man/domain_filename_es.Rd
@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/filename-tools-subset.R
+\name{domain_filename_es}
+\alias{domain_filename_es}
+\title{Generate Spanish domain filename}
+\usage{
+domain_filename_es(protest_domain)
+}
+\arguments{
+\item{protest_domain}{The protest domain name in Spanish}
+}
+\value{
+The corresponding filename for the Spanish domain page,
+  relative to the root of the website.
+}
+\description{
+Generate Spanish domain filename
+}
+\examples{
+domain_filename_es("Campesino")
+}
diff --git a/man/make_waffle_chart.Rd b/man/make_waffle_chart.Rd
new file mode 100644
index 0000000..eb75ba5
--- /dev/null
+++ b/man/make_waffle_chart.Rd
@@ -0,0 +1,60 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/waffle-plot-functions.R
+\name{make_waffle_chart}
+\alias{make_waffle_chart}
+\title{Create a waffle chart with facets}
+\usage{
+make_waffle_chart(
+  dataframe,
+  x_var,
+  fill_var,
+  fill_var_description,
+  n_columns = 5,
+  waffle_width = 10,
+  complete_x = FALSE,
+  lang = "en",
+  .verbose = FALSE
+)
+}
+\arguments{
+\item{dataframe}{The input dataframe containing the data.}
+
+\item{x_var}{The variable to facet the waffle chart by (e.g., year
+or pres_admin). This will name the facets.}
+
+\item{fill_var}{The variable to color the waffle chart blocks by (e.g.,
+state_responsibility).}
+
+\item{fill_var_description}{A list containing the title, levels, and colors
+for the fill variable. Can be taken from our level description list, lev.}
+
+\item{n_columns}{Number of columns for the facet wrap.}
+
+\item{waffle_width}{Number of rows in each waffle chart (default 10).}
+
+\item{complete_x}{Logical indicating whether to complete missing x values
+with a single null block. Only implemented for year and pres_admin.}
+
+\item{lang}{Language for the legend labels ("en" or "es"). Default is "en".
+Only affects the legend and not the x-axis label, which should be
+handled before calling the function.}
+
+\item{.verbose}{Logical indicating whether to print debug information.}
+}
+\value{
+A ggplot object representing the waffle chart.
+}
+\description{
+Creates a waffle chart from an overall dataset, both calculating
+the relevant counts and formatting the chart.
+}
+\examples{
+\dontrun{
+deaths <- assign_levels(deaths_aug24, "standard", .simplify = TRUE)
+make_waffle_chart(deaths,
+  x_var = pres_admin,
+  fill_var = state_responsibility,
+  fill_var_description = state_resp,
+  complete_x = TRUE, n_columns = 7)
+}
+}
diff --git a/man/make_waffle_chart_tall.Rd b/man/make_waffle_chart_tall.Rd
new file mode 100644
index 0000000..d3560b2
--- /dev/null
+++ b/man/make_waffle_chart_tall.Rd
@@ -0,0 +1,65 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/waffle-plot-functions.R
+\name{make_waffle_chart_tall}
+\alias{make_waffle_chart_tall}
+\title{Create a tall waffle chart with facets}
+\usage{
+make_waffle_chart_tall(
+  dataframe,
+  x_var,
+  fill_var,
+  fill_var_description,
+  n_columns = 5,
+  complete_x = FALSE,
+  lang = "en",
+  .verbose = FALSE
+)
+}
+\arguments{
+\item{dataframe}{The input dataframe containing the data.}
+
+\item{x_var}{The variable to facet the waffle chart by (e.g., year
+or pres_admin). This will name the facets.}
+
+\item{fill_var}{The variable to color the waffle chart blocks by (e.g.,
+state_responsibility).}
+
+\item{fill_var_description}{A list containing the title, levels, and colors
+for the fill variable. Can be taken from our level description list, lev.}
+
+\item{n_columns}{Number of rows for the facet wrap (displayed vertically).}
+
+\item{complete_x}{Logical indicating whether to complete missing x values
+with a single null block. Only implemented for year and pres_admin.}
+
+\item{lang}{Language for the legend labels ("en" or "es"). Default is "en".
+Only affects the legend and not the x-axis label, which should be
+handled before calling the function.}
+
+\item{.verbose}{Logical indicating whether to print debug information.}
+}
+\value{
+A ggplot object representing the tall waffle chart.
+}
+\description{
+Creates a tall-oriented waffle chart from an overall dataset, both calculating
+the relevant counts and formatting the chart. Facets are arranged vertically.
+}
+\examples{
+\dontrun{
+deaths <- assign_levels(deaths_aug24, "standard", .simplify = TRUE)
+make_waffle_chart_tall(deaths,
+  x_var = pres_admin,
+  fill_var = state_responsibility,
+  fill_var_description = lev$state_responsibility,
+  complete_x = TRUE, n_columns = 7)
+ make_waffle_chart_tall(deaths,
+   x_var = pres_admin, fill_var = state_responsibility,
+   fill_var_description = lev$state_responsibility,
+   complete_x = FALSE, n_columns = 6)
+ make_waffle_chart_tall(deaths,
+   x_var = pres_admin, fill_var = state_responsibility,
+   fill_var_description = lev$state_responsibility,
+   complete_x = FALSE, n_columns = 6, lang="es")
+}
+}
diff --git a/man/relabel_pres_admin.Rd b/man/relabel_pres_admin.Rd
new file mode 100644
index 0000000..448d0b6
--- /dev/null
+++ b/man/relabel_pres_admin.Rd
@@ -0,0 +1,38 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/relabel-pres-admin.R
+\name{relabel_pres_admin}
+\alias{relabel_pres_admin}
+\title{Relabel presidential administration using presidency_name_table}
+\usage{
+relabel_pres_admin(
+  dataframe,
+  output_column,
+  .input_column = "presidency",
+  keep_original = TRUE
+)
+}
+\arguments{
+\item{dataframe}{The input dataframe containing a pres_admin column}
+
+\item{output_column}{The column from presidency_name_table to use for new labels
+(unquoted column name)}
+
+\item{.input_column}{The column from presidency_name_table to match against
+pres_admin (default "presidency")}
+
+\item{keep_original}{Logical indicating whether to keep the original pres_admin
+column as pres_admin_original (default TRUE)}
+}
+\value{
+The dataframe with pres_admin relabeled according to output_column
+}
+\description{
+Replaces pres_admin values with corresponding values from a specified column
+in presidency_name_table (e.g., presidency_year, presidency_initials, etc.)
+}
+\examples{
+def <- assign_presidency_levels(deaths_aug24)
+def_labeled <- relabel_pres_admin(def, presidency_year)
+def_labeled <- relabel_pres_admin(def, presidency_initials)
+def_labeled <- relabel_pres_admin(def, presidency_fullname_es, keep_original = TRUE)
+}
diff --git a/man/sorted_by_most_frequent.Rd b/man/sorted_by_most_frequent.Rd
new file mode 100644
index 0000000..2ea8097
--- /dev/null
+++ b/man/sorted_by_most_frequent.Rd
@@ -0,0 +1,42 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/sort-var-description.R
+\name{sorted_by_most_frequent}
+\alias{sorted_by_most_frequent}
+\title{Sort variable description by frequency}
+\usage{
+sorted_by_most_frequent(var_description, def, grouping_var = NULL)
+}
+\arguments{
+\item{var_description}{A list containing variable metadata with elements:
+\itemize{
+  \item \code{r_variable}: Name of the variable in the dataframe
+  \item \code{levels}: Character vector of level names
+  \item \code{colors}: Named vector of colors for each level
+  \item \code{levels_es}: (Optional) Spanish translations of levels
+  \item \code{colors_es}: (Optional) Spanish-named color vector
+}}
+
+\item{def}{The dataframe containing the data to analyze}
+
+\item{grouping_var}{Optional grouping variable (not used, included for
+consistency with \code{sorted_by_widest_appearance})}
+}
+\value{
+A modified variable description list with levels and colors reordered
+  by frequency. Includes a new \code{$ranked} element with the sorted levels.
+}
+\description{
+Reorders the levels and colors in a variable description list based on
+the frequency of each level in the data. More frequent levels are ranked
+higher.
+}
+\examples{
+\dontrun{
+deaths <- assign_protest_domain_levels(deaths_aug24)
+# Sort protest domains by total frequency
+pd_sorted <- sorted_by_most_frequent(
+  var_description = lev$protest_domain,
+  def = deaths
+)
+}
+}
diff --git a/man/sorted_by_widest_appearance.Rd b/man/sorted_by_widest_appearance.Rd
new file mode 100644
index 0000000..4e72e46
--- /dev/null
+++ b/man/sorted_by_widest_appearance.Rd
@@ -0,0 +1,45 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/sort-var-description.R
+\name{sorted_by_widest_appearance}
+\alias{sorted_by_widest_appearance}
+\title{Sort variable description by widest appearance across groups}
+\usage{
+sorted_by_widest_appearance(var_description, def, grouping_var)
+}
+\arguments{
+\item{var_description}{A list containing variable metadata with elements:
+\itemize{
+  \item \code{r_variable}: Name of the variable in the dataframe
+  \item \code{levels}: Character vector of level names
+  \item \code{colors}: Named vector of colors for each level
+  \item \code{levels_es}: (Optional) Spanish translations of levels
+  \item \code{colors_es}: (Optional) Spanish-named color vector
+}}
+
+\item{def}{The dataframe containing the data to analyze}
+
+\item{grouping_var}{The variable to group by when calculating width of
+appearance (e.g., pres_admin, year). Use unquoted variable name.}
+}
+\value{
+A modified variable description list with levels and colors reordered
+  by widest appearance. Includes a new \code{$ranked} element with the
+  sorted levels.
+}
+\description{
+Reorders the levels and colors in a variable description list based on how
+widely each level appears across a grouping variable. Levels that appear in
+more groups are ranked higher. For example, sorting protest domains by how
+many presidential administrations each domain appears in.
+}
+\examples{
+\dontrun{
+# Sort protest domains by how many presidential administrations they appear in
+deaths <- assign_protest_domain_levels(deaths_aug24)
+pd_sorted <- sorted_by_widest_appearance(
+  var_description = lev$protest_domain,
+  def = deaths,
+  grouping_var = pres_admin
+)
+}
+}
diff --git a/man/waffle_counts.Rd b/man/waffle_counts.Rd
new file mode 100644
index 0000000..3f8a76f
--- /dev/null
+++ b/man/waffle_counts.Rd
@@ -0,0 +1,31 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/waffle-plot-functions.R
+\name{waffle_counts}
+\alias{waffle_counts}
+\title{Helper function to create counts dataframe for waffle charts}
+\usage{
+waffle_counts(dataframe, x_var, fill_var, fill_var_description)
+}
+\arguments{
+\item{dataframe}{The input dataframe containing the data.}
+
+\item{x_var}{The variable to facet the waffle chart by (e.g., year).}
+
+\item{fill_var}{The variable to color the waffle chart blocks by (e.g.,
+state_responsibility).}
+
+\item{fill_var_description}{A list containing the title, levels, and colors
+for the fill variable. Can be taken from our level description list, lev.}
+}
+\value{
+A dataframe with counts of occurrences for each combination of x_var
+  and fill_var.
+}
+\description{
+Helper function to create counts dataframe for waffle charts
+}
+\examples{
+waffle_counts(dataframe = assign_state_responsibility_levels(deaths_aug24, simplify = TRUE),
+ x_var = year, fill_var = state_responsibility,
+              fill_var_description = lev$state_responsibility)
+}
diff --git a/tests/testthat/_snaps/relabel-pres-admin.md b/tests/testthat/_snaps/relabel-pres-admin.md
new file mode 100644
index 0000000..c5afbeb
--- /dev/null
+++ b/tests/testthat/_snaps/relabel-pres-admin.md
@@ -0,0 +1,52 @@
+# relabel_pres_admin works
+
+    Code
+      def_labeled
+    Output
+      # A tibble: 670 x 52
+         event_title    unconfirmed  year month   day later_year later_month later_day
+         <chr>          <lgl>       <int> <int> <int>      <int>       <int>     <int>
+       1 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       2 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       3 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       4 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       5 Killing of ha~ NA           1984    10    28         NA          NA        NA
+       6 Huayllani roa~ NA           1985     6     3         NA          NA        NA
+       7 Huayllani roa~ NA           1985     6     3         NA          NA        NA
+       8 Huayllani roa~ TRUE         1985     6     3         NA          NA        NA
+       9 COB education~ NA           1986     4     8         NA          NA        NA
+      10 COB education~ NA           1986     4     8       1986           4        10
+      # i 660 more rows
+      # i 44 more variables: dec_firstname <chr>, dec_surnames <chr>, id_indiv <chr>,
+      #   dec_age <dbl>, dec_alt_age <chr>, dec_gender <chr>, dec_residence <chr>,
+      #   dec_nationality <chr>, dec_affiliation <chr>, dec_spec_affiliation <chr>,
+      #   dec_title <chr>, cause_death <chr>, munition <chr>, weapon <chr>,
+      #   va_notes <chr>, perp_category <chr>, perp_group <chr>,
+      #   perp_pol_stalemate <chr>, dec_pol_stalemate <chr>, ...
+
+---
+
+    Code
+      def_labeled2
+    Output
+      # A tibble: 670 x 52
+         event_title    unconfirmed  year month   day later_year later_month later_day
+         <chr>          <lgl>       <int> <int> <int>      <int>       <int>     <int>
+       1 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       2 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       3 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       4 Shooting at S~ NA           1984    10    26         NA          NA        NA
+       5 Killing of ha~ NA           1984    10    28         NA          NA        NA
+       6 Huayllani roa~ NA           1985     6     3         NA          NA        NA
+       7 Huayllani roa~ NA           1985     6     3         NA          NA        NA
+       8 Huayllani roa~ TRUE         1985     6     3         NA          NA        NA
+       9 COB education~ NA           1986     4     8         NA          NA        NA
+      10 COB education~ NA           1986     4     8       1986           4        10
+      # i 660 more rows
+      # i 44 more variables: dec_firstname <chr>, dec_surnames <chr>, id_indiv <chr>,
+      #   dec_age <dbl>, dec_alt_age <chr>, dec_gender <chr>, dec_residence <chr>,
+      #   dec_nationality <chr>, dec_affiliation <chr>, dec_spec_affiliation <chr>,
+      #   dec_title <chr>, cause_death <chr>, munition <chr>, weapon <chr>,
+      #   va_notes <chr>, perp_category <chr>, perp_group <chr>,
+      #   perp_pol_stalemate <chr>, dec_pol_stalemate <chr>, ...
+
diff --git a/tests/testthat/test-filename-tools-subset.R b/tests/testthat/test-filename-tools-subset.R
new file mode 100644
index 0000000..17c6220
--- /dev/null
+++ b/tests/testthat/test-filename-tools-subset.R
@@ -0,0 +1,26 @@
+test_that("domain_filename works", {
+  domain_list <- c("Gas wars", "Economic policies", "Labor", "Education", "Mining",
+                   "Coca", "Peasant", "Rural land",
+                   "Ethno-ecological", "Urban land", "Drug trade", "Contraband",
+                   "Municipal governance", "Local development", "National governance",
+                   "Partisan politics", "Disabled", "Guerrilla", "Paramilitary",
+                   "Unknown")
+  desired_links <- c("/domain/gas-wars.html", "/domain/economic-policies.html",
+                     "/domain/labor.html", "/domain/education.html", "/domain/mining.html",
+                     "/domain/coca.html", "/domain/peasant.html", "/domain/rural-land.html",
+                     "/domain/ethno-ecological.html", "/domain/urban-land.html",
+                     "/domain/drug-trade.html", "/domain/contraband.html",
+                     "/domain/municipal-governance.html",
+                     "/domain/local-development.html", "/domain/national-governance.html",
+                     "/domain/partisan-politics.html", "/domain/disabled.html",
+                     "/domain/guerrilla.html",
+                     "/domain/paramilitary.html", "/domain/unknown.html")
+  expect_equal(domain_filename(domain_list), desired_links)
+})
+test_that("domain_filename handles commas", {
+  expect_equal(domain_filename("Rural land, Partisan politics"), "")
+  expect_equal(domain_filename_es("Campesino, Politica partidaria"), "")
+})
+
+
+
diff --git a/tests/testthat/test-relabel-pres-admin.R b/tests/testthat/test-relabel-pres-admin.R
new file mode 100644
index 0000000..76a6e0a
--- /dev/null
+++ b/tests/testthat/test-relabel-pres-admin.R
@@ -0,0 +1,14 @@
+test_that("relabel_pres_admin works", {
+  def <- deaths_aug24
+  def_labeled <- relabel_pres_admin(def, presidency_year, keep_original = TRUE)
+  expect_equal(ncol(def_labeled), ncol(def) + 1)
+  expect_true("pres_admin_original" %in% colnames(def_labeled))
+  expect_equal(def_labeled$pres_admin_original, def$pres_admin)
+  expect_snapshot(def_labeled)
+
+  def_labeled2 <- relabel_pres_admin(def, presidency_initials) %>% suppressWarnings()
+  expect_equal(ncol(def_labeled2), ncol(def) + 1)
+  expect_true(all(unique(def_labeled2$pres_admin) %in% presidency_name_table$presidency_initials))
+
+  expect_snapshot(def_labeled2)
+})
diff --git a/tests/testthat/test-sort-var-description.R b/tests/testthat/test-sort-var-description.R
new file mode 100644
index 0000000..7abffa2
--- /dev/null
+++ b/tests/testthat/test-sort-var-description.R
@@ -0,0 +1,224 @@
+# tests/testthat/test-sort-var-description.R
+
+test_that("sorted_by_widest_appearance reorders levels correctly", {
+  # Create sample data
+  test_data <- tibble::tibble(
+    year = c(2010, 2010, 2011, 2011, 2012, 2013),
+    category = c("A", "B", "A", "C", "A", "B")
+  )
+
+  # Create sample var_description
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A", "B", "C"),
+    colors = c("A" = "#FF0000", "B" = "#00FF00", "C" = "#0000FF")
+  )
+
+  # Apply function
+  result <- sorted_by_widest_appearance(test_desc, test_data, year)
+
+  # A appears in 3 years, B in 2 years, C in 1 year
+  expect_equal(as.character(result$ranked), c("A", "B", "C"))
+  expect_equal(result$levels, c("A", "B", "C"))
+  expect_equal(names(result$colors), c("A", "B", "C"))
+  expect_equal(as.character(result$colors), c("#FF0000", "#00FF00", "#0000FF"))
+})
+
+test_that("sorted_by_widest_appearance handles tied ranks", {
+  test_data <- tibble::tibble(
+    year = c(2010, 2010, 2011, 2011),
+    category = c("A", "B", "A", "B")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A", "B"),
+    colors = c("A" = "#FF0000", "B" = "#00FF00")
+  )
+
+  result <- sorted_by_widest_appearance(test_desc, test_data, year)
+
+  # Both A and B appear in 2 years
+  expect_equal(length(result$ranked), 2)
+  expect_true(all(c("A", "B") %in% as.character(result$ranked)))
+})
+
+test_that("sorted_by_widest_appearance preserves Spanish levels", {
+  test_data <- tibble::tibble(
+    year = c(2010, 2010, 2011, 2011, 2012),
+    category = c("A", "B", "A", "C", "A")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A", "B", "C"),
+    levels_es = c("Categoría A", "Categoría B", "Categoría C"),
+    colors = c("A" = "#FF0000", "B" = "#00FF00", "C" = "#0000FF")
+  )
+
+  result <- sorted_by_widest_appearance(test_desc, test_data, year)
+
+  # Check that Spanish levels are reordered to match English
+  expect_equal(result$levels, c("A", "B", "C"))
+  expect_equal(result$levels_es, c("Categoría A", "Categoría B", "Categoría C"))
+})
+
+test_that("sorted_by_widest_appearance preserves Spanish colors", {
+  test_data <- tibble::tibble(
+    year = c(2010, 2010, 2011, 2012),
+    category = c("B", "A", "B", "B")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A", "B"),
+    levels_es = c("Categoría A", "Categoría B"),
+    colors = c("A" = "#FF0000", "B" = "#00FF00"),
+    colors_es = c("Categoría A" = "#FF0000", "Categoría B" = "#00FF00")
+  )
+
+  result <- sorted_by_widest_appearance(test_desc, test_data, year)
+
+  # B appears in 3 years, A in 1 year
+  expect_equal(result$levels, c("B", "A"))
+  expect_equal(result$levels_es, c("Categoría B", "Categoría A"))
+  expect_equal(names(result$colors_es), c("Categoría B", "Categoría A"))
+  expect_equal(as.character(result$colors_es), c("#00FF00", "#FF0000"))
+})
+
+test_that("sorted_by_most_frequent reorders by frequency", {
+  test_data <- tibble::tibble(
+    category = c("A", "A", "A", "B", "B", "C")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("C", "B", "A"),
+    colors = c("C" = "#0000FF", "B" = "#00FF00", "A" = "#FF0000")
+  )
+
+  result <- sorted_by_most_frequent(test_desc, test_data)
+
+  # A has 3, B has 2, C has 1
+  expect_equal(as.character(result$ranked), c("A", "B", "C"))
+  expect_equal(result$levels, c("A", "B", "C"))
+  expect_equal(names(result$colors), c("A", "B", "C"))
+  expect_equal(as.character(result$colors), c("#FF0000", "#00FF00", "#0000FF"))
+})
+
+test_that("sorted_by_most_frequent ignores grouping_var parameter", {
+  test_data <- tibble::tibble(
+    year = c(2010, 2010, 2011),
+    category = c("A", "B", "A")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A", "B"),
+    colors = c("A" = "#FF0000", "B" = "#00FF00")
+  )
+
+  result1 <- sorted_by_most_frequent(test_desc, test_data)
+  result2 <- sorted_by_most_frequent(test_desc, test_data, grouping_var = year)
+
+  # Both should give same result (A appears 2x, B appears 1x)
+  expect_equal(result1$ranked, result2$ranked)
+  expect_equal(result1$levels, result2$levels)
+})
+
+test_that("sorted_by_most_frequent preserves Spanish translations", {
+  test_data <- tibble::tibble(
+    category = c("C", "C", "C", "A", "A", "B")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A", "B", "C"),
+    levels_es = c("Categoría A", "Categoría B", "Categoría C"),
+    colors = c("A" = "#FF0000", "B" = "#00FF00", "C" = "#0000FF"),
+    colors_es = c("Categoría A" = "#FF0000",
+                  "Categoría B" = "#00FF00",
+                  "Categoría C" = "#0000FF")
+  )
+
+  result <- sorted_by_most_frequent(test_desc, test_data)
+
+  # C has 3, A has 2, B has 1
+  expect_equal(result$levels, c("C", "A", "B"))
+  expect_equal(result$levels_es, c("Categoría C", "Categoría A", "Categoría B"))
+  expect_equal(names(result$colors_es),
+               c("Categoría C", "Categoría A", "Categoría B"))
+})
+
+test_that("functions work with real package data", {
+  skip_if_not(exists("deaths_aug24"), "deaths_aug24 not available")
+  skip_if_not(exists("lev"), "lev not available")
+  skip_if_not(exists("assign_levels"), "assign_levels not available")
+
+  deaths_filtered <- assign_levels(deaths_aug24, "standard", .simplify = TRUE)
+
+  # Test sorted_by_widest_appearance with real data
+  if ("protest_domain" %in% names(lev)) {
+    result_wide <- sorted_by_widest_appearance(
+      lev$protest_domain,
+      deaths_filtered,
+      pres_admin
+    )
+
+    expect_true("ranked" %in% names(result_wide))
+    expect_equal(length(result_wide$levels), length(result_wide$colors))
+    if (!is.null(result_wide$levels_es)) {
+      expect_equal(length(result_wide$levels), length(result_wide$levels_es))
+    }
+  }
+
+  # Test sorted_by_most_frequent with real data
+  if ("protest_domain" %in% names(lev)) {
+    result_freq <- sorted_by_most_frequent(
+      lev$protest_domain,
+      deaths_filtered
+    )
+
+    expect_true("ranked" %in% names(result_freq))
+    expect_equal(length(result_freq$levels), length(result_freq$colors))
+  }
+})
+
+test_that("functions handle single-level variables", {
+  test_data <- tibble::tibble(
+    year = c(2010, 2011, 2012),
+    category = c("A", "A", "A")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A"),
+    colors = c("A" = "#FF0000")
+  )
+
+  result_wide <- sorted_by_widest_appearance(test_desc, test_data, year)
+  result_freq <- sorted_by_most_frequent(test_desc, test_data)
+
+  expect_equal(length(result_wide$levels), 1)
+  expect_equal(length(result_freq$levels), 1)
+  expect_equal(result_wide$levels, "A")
+  expect_equal(result_freq$levels, "A")
+})
+
+test_that("functions preserve all color values", {
+  test_data <- tibble::tibble(
+    category = c("B", "C", "A")
+  )
+
+  test_desc <- list(
+    r_variable = "category",
+    levels = c("A", "B", "C"),
+    colors = c("A" = "#FF0000", "B" = "#00FF00", "C" = "#0000FF")
+  )
+
+  result <- sorted_by_most_frequent(test_desc, test_data)
+
+  # Check all colors are present (even if reordered)
+  expect_setequal(as.character(result$colors),
+                  c("#FF0000", "#00FF00", "#0000FF"))
+})
diff --git a/tests/testthat/test-waffle-plot-functions.R b/tests/testthat/test-waffle-plot-functions.R
new file mode 100644
index 0000000..e15ea23
--- /dev/null
+++ b/tests/testthat/test-waffle-plot-functions.R
@@ -0,0 +1,210 @@
+# Tests for waffle plot functions
+
+# Setup test data and descriptions
+setup_test_data <- function() {
+  # Create sample fill variable description
+  fill_desc <- list(
+    title = "Test Category",
+    levels = c("Category A", "Category B", "Category C"),
+    colors = c("Category A" = "#FF0000",
+               "Category B" = "#00FF00",
+               "Category C" = "#0000FF")
+  )
+
+  # Create sample dataframe
+  test_df <- tibble::tibble(
+    year = c(2010, 2010, 2012, 2012, 2014, 2014),
+    pres_admin = factor(c("Admin1", "Admin1", "Admin2", "Admin2", "Admin3", "Admin3"),
+                        levels = c("Admin1", "Admin2", "Admin3", "Admin4")),
+    category = factor(c("Category A", "Category B", "Category A",
+                        "Category C", "Category B", "Category C"),
+                      levels = c("Category A", "Category B", "Category C")),
+    value = c(5, 3, 4, 2, 6, 1)
+  )
+
+  list(df = test_df, fill_desc = fill_desc)
+}
+
+test_that("waffle_counts filters and counts correctly", {
+  test_data <- setup_test_data()
+
+  result <- waffle_counts(test_data$df, year, category, test_data$fill_desc)
+
+  # Should have 6 rows (one for each year-category combination)
+  expect_equal(nrow(result), 6)
+
+  # Should have 3 columns: year, category, n
+  expect_equal(ncol(result), 3)
+
+  # Category should be properly factored
+  expect_true(is.factor(result$category))
+  expect_equal(levels(result$category), test_data$fill_desc$levels)
+})
+
+test_that("waffle_counts filters out NA and Unknown values", {
+  test_data <- setup_test_data()
+
+  # Add problematic rows
+  df_with_nas <- test_data$df %>%
+    dplyr::bind_rows(
+      tibble::tibble(year = NA, pres_admin = "Admin1", category = "Category A", value = 1),
+      tibble::tibble(year = 2015, pres_admin = "Unknown", category = "Category A", value = 1),
+      tibble::tibble(year = 2015, pres_admin = "Admin1", category = NA, value = 1)
+    )
+
+  result <- waffle_counts(df_with_nas, pres_admin, category, test_data$fill_desc)
+
+  # Should only have the original 6 rows
+  expect_equal(nrow(result), 6)
+
+  # Should not contain NA or "Unknown"
+  expect_false(any(is.na(result$pres_admin)))
+  expect_false(any(result$pres_admin == "Unknown"))
+  expect_false(any(is.na(result$category)))
+})
+
+test_that("waffle_counts works on standard dataset", {
+  deaths <- deaths_aug24 %>%
+    assign_state_responsibility_levels(simplify = TRUE)
+  result <- waffle_counts(deaths, year, state_responsibility,
+                          lev$state_responsibility)
+
+  # Should have more than 0 rows
+  expect_gt(nrow(result), 0)
+
+  # Should have full range of values
+  expect_equal(sort(unique(result$year)),
+               sort(unique(na.omit(deaths$year))))
+  expect_equal(sort(unique(result$state_responsibility)),
+               sort(unique(deaths$state_responsibility)))
+
+  # Should have 3 columns: year, state_responsibility, n
+  expect_equal(names(result), c("year", "state_responsibility", "n"))
+
+  # state_responsibility should be properly factored
+  expect_true(is.factor(result$state_responsibility))
+  expect_equal(levels(result$state_responsibility), lev$state_responsibility$levels)
+})
+
+test_that("make_waffle_chart returns a ggplot object", {
+  test_data <- setup_test_data()
+
+  result <- make_waffle_chart(test_data$df, year, category,
+                              test_data$fill_desc, complete_x = FALSE)
+
+  expect_s3_class(result, "gg")
+  expect_s3_class(result, "ggplot")
+})
+
+test_that("complete_x_values adds missing years", {
+  test_data <- setup_test_data()
+
+  # Create data with gaps
+  df_with_gaps <- test_data$df %>%
+    dplyr::filter(year != 2012)  # Remove 2012
+
+  counts_df <- waffle_counts(df_with_gaps, year, category, test_data$fill_desc)
+
+  completed_counts <- complete_x_values(counts_df, year, category,
+                                        all_levels = NULL, .verbose = FALSE)
+
+  # Check that 2012 was added
+  expect_true(2012 %in% completed_counts$year)
+})
+
+test_that("complete_x_values fixes missing years in standard data", {
+  deaths <- assign_levels(deaths_aug24, "standard", .simplify=TRUE)
+
+  # Create data with gaps
+  df_with_gaps <- deaths %>%
+    dplyr::filter(year != 2012)  # Remove 2012
+
+  waffle_counts_df <- waffle_counts(df_with_gaps,
+                                    x_var = year,
+                                    fill_var = protest_domain,
+                                    fill_var_description = lev$protest_domain)
+
+  expect_equal(nrow(waffle_counts_df[waffle_counts_df$year == 2012, ]), 0)
+
+  waffle_counts_df_completed <- complete_x_values(waffle_counts_df,
+                    x_var = year,
+                    fill_var = protest_domain,
+                    all_levels = NULL,
+                    .verbose = FALSE)
+  expect_true(2012 %in% waffle_counts_df_completed$year)
+
+  result <- make_waffle_chart(df_with_gaps,
+                              x_var = year,
+                              fill_var = protest_domain,
+                              lev$protest_domain, complete_x = FALSE)
+
+  # Check that the plot data doesn't include 2012
+  plot_data <- ggplot2::ggplot_build(result)$data[[1]]
+  expect_false(2012 %in% plot_data$plot$data$year)
+
+  result_completed <- make_waffle_chart(df_with_gaps,
+                              x_var = year,
+                              fill_var = protest_domain,
+                              lev$protest_domain, complete_x = TRUE)
+  # Check that the plot data includes 2012
+  plot_data_completed <- ggplot2::ggplot_build(result_completed)
+  expect_true(2012 %in% plot_data_completed$plot$data$year)
+})
+
+test_that("make_waffle_chart with complete_x=TRUE fills pres_admin gaps", {
+  deaths <- assign_levels(deaths_aug24, "standard", .simplify=TRUE)
+
+  # verify that there are already missinng values
+  count(deaths, pres_admin, .drop=FALSE) %>% filter(n==0) %>% nrow() -> num_missing
+  expect_gt(num_missing, 0)
+  pres_admin_missing <- count(deaths, pres_admin, .drop=FALSE) %>%
+    filter(n==0) %>% pull(pres_admin)
+
+  # Verify it's missing if not completed
+  result <- make_waffle_chart(deaths, pres_admin, protest_domain,
+                              lev$protest_domain, complete_x = FALSE)
+  plot_data <- ggplot2::ggplot_build(result)$data[[1]]
+  expect_false(any(pres_admin_missing %in% plot_data$plot$data$pres_admin))
+
+  # This should add a null block for our missing president(s)
+  result_completed <- make_waffle_chart(deaths, pres_admin, protest_domain,
+                              lev$protest_domain, complete_x = TRUE)
+  plot_data_completed <- ggplot2::ggplot_build(result_completed)
+  expect_true(any(pres_admin_missing %in% plot_data_completed$plot$data$pres_admin))
+})
+
+test_that("make_waffle_chart_tall returns a ggplot object", {
+  test_data <- setup_test_data()
+
+  result <- make_waffle_chart_tall(test_data$df, year, category,
+                                   test_data$fill_desc)
+
+  expect_s3_class(result, "gg")
+  expect_s3_class(result, "ggplot")
+})
+
+test_that("make_waffle_chart handles different waffle_width values", {
+  test_data <- setup_test_data()
+
+  result1 <- make_waffle_chart(test_data$df, year, category,
+                               test_data$fill_desc, waffle_width = 5)
+  result2 <- make_waffle_chart(test_data$df, year, category,
+                               test_data$fill_desc, waffle_width = 15)
+
+  expect_s3_class(result1, "ggplot")
+  expect_s3_class(result2, "ggplot")
+})
+
+test_that("complete_x verbose mode produces output", {
+  test_data <- setup_test_data()
+
+  df_with_gaps <- test_data$df %>%
+    dplyr::filter(year != 2012)
+
+  # Should print verbose output
+  expect_output(
+    make_waffle_chart(df_with_gaps, year, category,
+                      test_data$fill_desc, complete_x = TRUE, .verbose = TRUE),
+    "Null values"
+  )
+})
diff --git a/vignettes/articles/event-heat-map.Rmd b/vignettes/articles/event-heat-map.Rmd
index 38ad4d5..2616259 100644
--- a/vignettes/articles/event-heat-map.Rmd
+++ b/vignettes/articles/event-heat-map.Rmd
@@ -85,7 +85,7 @@ create_calendar_heatmap <- function(year) {
 
   plot_month <- function(month_num) {
     month_data <- df %>% filter(month == month_num)
-    ggplot(month_data, aes(x = wday, y = week, fill = events)) +
+    ggplot2::ggplot(month_data, aes(x = wday, y = week, fill = events)) +
       geom_tile(color = "white") +
       scale_fill_gradient(low = "white", high = "red") +
       scale_x_continuous(breaks = 1:7, labels = c("S", "M", "T", "W", "T", "F", "S")) +