diff --git a/NAMESPACE b/NAMESPACE
index 7ba0c90..6ad256f 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -4,11 +4,14 @@ export(add_lines)
 export(calculate_timing)
 export(check_quality)
 export(convplot)
+export(geom_token)
 export(geom_turn)
+export(GeomToken)
 export(GeomTurn)
 export(init)
 export(inspect_language)
 export(plot_quality)
+export(plot_turns_tokens)
 export(report_stats)
 export(theme_turnPlot)
 export(tokenize)
diff --git a/R/geom_token.R b/R/geom_token.R
new file mode 100644
index 0000000..d4acc22
--- /dev/null
+++ b/R/geom_token.R
@@ -0,0 +1,50 @@
+#' Plot individual tokens
+#'
+#' From a separate data frame containing tokenized data, plot individual tokens
+#' at their estimated time. Data must be provided separately, and should
+#' contain a column with the participant (y) and a column with the time (x).
+#'
+#' @param data A tokenized data frame (see `tokenize()`).
+#' @inheritParams ggplot2::layer
+#' @inheritParams ggplot2::geom_point
+#' @export
+geom_token <- function(data, mapping = NULL,
+                          stat = "identity", position = "identity",
+                          ..., na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) {
+  layer(
+    data = data,
+    mapping = mapping,
+    geom = GeomToken,
+    stat = stat,
+    position = position,
+    show.legend = show.legend,
+    inherit.aes = inherit.aes,
+    params = list(na.rm = na.rm,
+                  ...)
+  )
+}
+
+#' GeomToken
+#'
+#' @rdname ggplot2-ggproto
+#' @format NULL
+#' @usage NULL
+#' @export
+GeomToken <- ggproto(
+  "GeomToken", Geom,
+  required_aes = c("x", "y"),
+
+  default_aes = aes(
+    fill = "grey90",
+    colour = "grey40",
+    alpha = 1,
+    size = 1,
+    shape = 19,
+    stroke = 1
+  ),
+
+  draw_panel = function(data, panel_params, coord, ...) {
+    ggplot2::GeomPoint$draw_panel(data, panel_params, coord)
+  }
+)
+
diff --git a/R/geom_turn.R b/R/geom_turn.R
index 0b0ac0e..7436792 100644
--- a/R/geom_turn.R
+++ b/R/geom_turn.R
@@ -1,18 +1,15 @@
 #' Show turn-taking in visualized conversations
 #'
-#' @param mapping Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
-#' @param data The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().
-#' @param stat The statistical transformation to use on the data for this layer, either as a ggproto Geom subclass or as a string naming the stat stripped of the stat_ prefix (e.g. "count" rather than "stat_count")
-#' @param position Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
-#' @param na.rm If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
-#' @param show.legend logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.
-#' @param inherit.aes If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().
-#' @param ... Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.
+#' @param mapping Set of aesthetic mappings created by `ggplot2::aes()`.
+#'    Requires specification of `begin` and `end` of turns. Inherits from the default mapping at the
+#'    top level of the plot, if `inherit.aes` is set to `TRUE` (the default).
+#' @inheritParams ggplot2::layer
+#' @inheritParams ggplot2::geom_rect
+#' @param height The height of the turn-taking rectangles
 #' @export
-#' @rdname geom_turn
 geom_turn <- function(mapping = NULL, data = NULL,
                       stat = "identity", position = "identity",
-                      ..., na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) {
+                      ..., na.rm = FALSE, height = 0.8, show.legend = NA, inherit.aes = TRUE) {
   layer(
     data = data,
     mapping = mapping,
@@ -22,6 +19,7 @@ geom_turn <- function(mapping = NULL, data = NULL,
     show.legend = show.legend,
     inherit.aes = inherit.aes,
     params = list(na.rm = na.rm,
+                  height = height,
                   ...)
   )
 }
@@ -34,26 +32,34 @@ geom_turn <- function(mapping = NULL, data = NULL,
 #' @export
 GeomTurn <- ggproto(
   "GeomTurn", Geom,
-  required_aes = c("xmin", "xmax", "ymin", "ymax", "xpoint", "ypoint", "fillpoint"),
+  required_aes = c("begin", "end"),
 
   default_aes = aes(
-    fill = "lightgrey",
+    fill = "grey80",
     linewidth = 0,
-    alpha = 1,
-    colour = "white", # geom_point
-    size = 2,
-    shape = 21,
-    stroke = 1
+    alpha = 1
   ),
 
-  draw_panel = function(data, panel_params, coord, ...) {
-    rect_data <- transform(data, xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax)
-    point_data <- transform(data, x = xpoint, y = -ypoint, fill = fillpoint)
+  extra_params = c("na.rm", "height"),
+
+  setup_data = function(data, params) {
+
+    data$height <- params$height
 
-    grid::grobTree(
-      ggplot2::GeomRect$draw_panel(rect_data, panel_params, coord),
-      ggplot2::GeomPoint$draw_panel(point_data, panel_params, coord)
-    )
+    data <- transform(data,
+                      ymin = y - 0.5*height,
+                      ymax = y + 0.5*height)
+
+    data
+  },
+
+  draw_panel = function(data, panel_params, coord, ...) {
+    rect_data <- transform(data,
+                           xmin = begin,
+                           xmax = end,
+                           ymin = ymin,
+                           ymax = ymax)
+    ggplot2::GeomRect$draw_panel(rect_data, panel_params, coord)
   }
 )
 
diff --git a/R/plot_turns_tokens.R b/R/plot_turns_tokens.R
new file mode 100644
index 0000000..9261038
--- /dev/null
+++ b/R/plot_turns_tokens.R
@@ -0,0 +1,56 @@
+#' Plot a stretch of conversation
+#'
+#' Utterances are plotted as grey boxes, with frequently occurring tokens overlaid as colored dots.
+#'
+#' @param data a talkr dataset
+#' @param begin start time of the plot in seconds (defaults to 0)
+#' @param duration duration of the plot in seconds (defaults to 60)
+#' @param maxrank maximum rank of tokens to plot (defaults to 10)
+#' @param source name or number of the source to plot (defaults to 1, plotting the first source in the data)
+#'
+#' @return plot object
+#' @export
+plot_turns_tokens <- function(data,
+                              begin = 0,
+                              duration = 60,
+                              maxrank = 10,
+                              source = 1){
+  check_talkr(data)
+
+  if(is.numeric(source)){
+    sourcenr <- min(source, length(unique(data$source)))
+    source <- unique(data$source)[sourcenr]
+  }
+  data <- data[data$source == source,]
+
+  tokens <- data |>
+    tokenize()
+  tokens <- tokens[tokens$rank < maxrank,]
+
+  time_start <- begin * 1000
+  time_end <- time_start + duration * 1000
+  data <- data[data$begin > time_start & data$end < time_end,]
+
+  uids_included <- unique(data$uid)
+  tokens <- tokens[tokens$uid %in% uids_included,]
+
+  p <- data |>
+    ggplot2::ggplot(aes(
+      x = .data$end,
+      y = .data$participant)) +
+    talkr::geom_turn(aes(
+      begin = .data$begin,
+      end = .data$end)) +
+    talkr::geom_token(data = tokens,
+                      aes(x = .data$relative_time,
+                          y = .data$participant,
+                          color = .data$rank)) +
+    talkr::theme_turnPlot() +
+    ggplot2::xlab("time (ms)") +
+    ggplot2::ggtitle(source)
+
+
+  return(p)
+}
+
+
diff --git a/R/tokenize.R b/R/tokenize.R
index 2ea4fd1..e8afcd5 100644
--- a/R/tokenize.R
+++ b/R/tokenize.R
@@ -37,9 +37,17 @@ tokenize <- function(data, utterancecol = "utterance") {
     dplyr::group_by(.data$uid) |>
     dplyr::summarise(nwords = dplyr::n())
 
+  nwordstotal <- sum(count$nwords)
+
+  rank <- data |>
+    dplyr::group_by(.data$token) |>
+    dplyr::summarise(frequency = dplyr::n()/nwordstotal) |>
+    dplyr::arrange(dplyr::desc(.data$frequency)) |>
+    dplyr::mutate(rank = dplyr::row_number())
+
   # merge timing data with token data and calculate timing
   data <- data |>
-    dplyr::left_join(count, by = "uid") |>
+    dplyr::left_join(count, by = "uid", suffix = c("_orig","")) |>
     dplyr::mutate(time_per_token = (.data$end - .data$begin) / .data$nwords,
                   starttime = .data$begin + (0.5 * .data$time_per_token),
                   relative_time = round(.data$starttime + (.data$tokenorder - 1) * .data$time_per_token, 0),
@@ -50,5 +58,8 @@ tokenize <- function(data, utterancecol = "utterance") {
                     TRUE ~ "middle")) |>
     dplyr::select(.data$source, .data$uid, .data$participant, .data$nwords, .data$token, .data$order, .data$relative_time)
 
+  data <- data |>
+    dplyr::left_join(rank, by = "token")
+
   return(data)
 }
diff --git a/man/geom_token.Rd b/man/geom_token.Rd
new file mode 100644
index 0000000..faca110
--- /dev/null
+++ b/man/geom_token.Rd
@@ -0,0 +1,59 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/geom_token.R
+\name{geom_token}
+\alias{geom_token}
+\title{Plot individual tokens}
+\usage{
+geom_token(
+  data,
+  mapping = NULL,
+  stat = "identity",
+  position = "identity",
+  ...,
+  na.rm = FALSE,
+  show.legend = NA,
+  inherit.aes = TRUE
+)
+}
+\arguments{
+\item{data}{A tokenized data frame (see `tokenize()`).}
+
+\item{mapping}{Set of aesthetic mappings created by \code{\link[ggplot2:aes]{aes()}}. If specified and
+\code{inherit.aes = TRUE} (the default), it is combined with the default mapping
+at the top level of the plot. You must supply \code{mapping} if there is no plot
+mapping.}
+
+\item{stat}{The statistical transformation to use on the data for this
+layer, either as a \code{ggproto} \code{Geom} subclass or as a string naming the
+stat stripped of the \code{stat_} prefix (e.g. \code{"count"} rather than
+\code{"stat_count"})}
+
+\item{position}{Position adjustment, either as a string naming the adjustment
+(e.g. \code{"jitter"} to use \code{position_jitter}), or the result of a call to a
+position adjustment function. Use the latter if you need to change the
+settings of the adjustment.}
+
+\item{...}{Other arguments passed on to \code{\link[ggplot2:layer]{layer()}}. These are
+often aesthetics, used to set an aesthetic to a fixed value, like
+\code{colour = "red"} or \code{size = 3}. They may also be parameters
+to the paired geom/stat.}
+
+\item{na.rm}{If \code{FALSE}, the default, missing values are removed with
+a warning. If \code{TRUE}, missing values are silently removed.}
+
+\item{show.legend}{logical. Should this layer be included in the legends?
+\code{NA}, the default, includes if any aesthetics are mapped.
+\code{FALSE} never includes, and \code{TRUE} always includes.
+It can also be a named logical vector to finely select the aesthetics to
+display.}
+
+\item{inherit.aes}{If \code{FALSE}, overrides the default aesthetics,
+rather than combining with them. This is most useful for helper functions
+that define both data and aesthetics and shouldn't inherit behaviour from
+the default plot specification, e.g. \code{\link[ggplot2:borders]{borders()}}.}
+}
+\description{
+From a separate data frame containing tokenized data, plot individual tokens
+at their estimated time. Data must be provided separately, and should
+contain a column with the participant (y) and a column with the time (x).
+}
diff --git a/man/geom_turn.Rd b/man/geom_turn.Rd
index 6e353fc..f4e8734 100644
--- a/man/geom_turn.Rd
+++ b/man/geom_turn.Rd
@@ -11,26 +11,61 @@ geom_turn(
   position = "identity",
   ...,
   na.rm = FALSE,
+  height = 0.8,
   show.legend = NA,
   inherit.aes = TRUE
 )
 }
 \arguments{
-\item{mapping}{Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.}
+\item{mapping}{Set of aesthetic mappings created by `ggplot2::aes()`.
+Requires specification of `begin` and `end` of turns. Inherits from the default mapping at the
+top level of the plot, if `inherit.aes` is set to `TRUE` (the default).}
 
-\item{data}{The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().}
+\item{data}{The data to be displayed in this layer. There are three
+options:
 
-\item{stat}{The statistical transformation to use on the data for this layer, either as a ggproto Geom subclass or as a string naming the stat stripped of the stat_ prefix (e.g. "count" rather than "stat_count")}
+If \code{NULL}, the default, the data is inherited from the plot
+data as specified in the call to \code{\link[ggplot2:ggplot]{ggplot()}}.
 
-\item{position}{Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.}
+A \code{data.frame}, or other object, will override the plot
+data. All objects will be fortified to produce a data frame. See
+\code{\link[ggplot2:fortify]{fortify()}} for which variables will be created.
 
-\item{...}{Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.}
+A \code{function} will be called with a single argument,
+the plot data. The return value must be a \code{data.frame}, and
+will be used as the layer data. A \code{function} can be created
+from a \code{formula} (e.g. \code{~ head(.x, 10)}).}
 
-\item{na.rm}{If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.}
+\item{stat}{The statistical transformation to use on the data for this
+layer, either as a \code{ggproto} \code{Geom} subclass or as a string naming the
+stat stripped of the \code{stat_} prefix (e.g. \code{"count"} rather than
+\code{"stat_count"})}
 
-\item{show.legend}{logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.}
+\item{position}{Position adjustment, either as a string naming the adjustment
+(e.g. \code{"jitter"} to use \code{position_jitter}), or the result of a call to a
+position adjustment function. Use the latter if you need to change the
+settings of the adjustment.}
 
-\item{inherit.aes}{If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().}
+\item{...}{Other arguments passed on to \code{\link[ggplot2:layer]{layer()}}. These are
+often aesthetics, used to set an aesthetic to a fixed value, like
+\code{colour = "red"} or \code{size = 3}. They may also be parameters
+to the paired geom/stat.}
+
+\item{na.rm}{If \code{FALSE}, the default, missing values are removed with
+a warning. If \code{TRUE}, missing values are silently removed.}
+
+\item{height}{The height of the turn-taking rectangles}
+
+\item{show.legend}{logical. Should this layer be included in the legends?
+\code{NA}, the default, includes if any aesthetics are mapped.
+\code{FALSE} never includes, and \code{TRUE} always includes.
+It can also be a named logical vector to finely select the aesthetics to
+display.}
+
+\item{inherit.aes}{If \code{FALSE}, overrides the default aesthetics,
+rather than combining with them. This is most useful for helper functions
+that define both data and aesthetics and shouldn't inherit behaviour from
+the default plot specification, e.g. \code{\link[ggplot2:borders]{borders()}}.}
 }
 \description{
 Show turn-taking in visualized conversations
diff --git a/man/ggplot2-ggproto.Rd b/man/ggplot2-ggproto.Rd
index 132431b..fb323f3 100644
--- a/man/ggplot2-ggproto.Rd
+++ b/man/ggplot2-ggproto.Rd
@@ -1,10 +1,13 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/geom_turn.R
+% Please edit documentation in R/geom_token.R, R/geom_turn.R
 \docType{data}
-\name{GeomTurn}
+\name{GeomToken}
+\alias{GeomToken}
 \alias{GeomTurn}
-\title{GeomTurn}
+\title{GeomToken}
 \description{
+GeomToken
+
 GeomTurn
 }
 \keyword{datasets}
diff --git a/man/plot_turns_tokens.Rd b/man/plot_turns_tokens.Rd
new file mode 100644
index 0000000..dd58e6d
--- /dev/null
+++ b/man/plot_turns_tokens.Rd
@@ -0,0 +1,25 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot_turns_tokens.R
+\name{plot_turns_tokens}
+\alias{plot_turns_tokens}
+\title{Plot a stretch of conversation}
+\usage{
+plot_turns_tokens(data, begin = 0, duration = 60, maxrank = 10, source = 1)
+}
+\arguments{
+\item{data}{a talkr dataset}
+
+\item{begin}{start time of the plot in seconds (defaults to 0)}
+
+\item{duration}{duration of the plot in seconds (defaults to 60)}
+
+\item{maxrank}{maximum rank of tokens to plot (defaults to 10)}
+
+\item{source}{name or number of the source to plot (defaults to 1, plotting the first source in the data)}
+}
+\value{
+plot object
+}
+\description{
+Utterances are plotted as grey boxes, with frequently occurring tokens overlaid as colored dots.
+}
diff --git a/tests/testthat/test-geom_.R b/tests/testthat/test-geom_.R
new file mode 100644
index 0000000..78daa75
--- /dev/null
+++ b/tests/testthat/test-geom_.R
@@ -0,0 +1,32 @@
+load("testdata.Rda")
+data <- init(testdata)
+
+test_that("applying geometries yields expected datasets", {
+  p0 <- data |>
+    ggplot2::ggplot(aes(x = end, y = participant))
+
+  d0 <- ggplot2::layer_data(p0)
+  expect_equal(d0$x, data$end)
+  expect_equal(max(d0$y), 23)
+
+  p1 <- p0 +
+    geom_turn(aes(
+      begin = begin,
+      end = end))
+
+  d1 <- ggplot2::layer_data(p1)
+  expect_equal(d1$end, data$end)
+  expect_equal(d1$begin, data$begin)
+  expect_equal(max(d1$y), 23)
+
+  tokens <- tokenize(data)
+
+  p2 <- p1 +
+  geom_token(data = tokens,
+                      aes(x = relative_time,
+                          y = participant,
+                          color = rank))
+
+  d2 <- ggplot2::layer_data(p2, 2)
+  expect_equal(d2$x, tokens$relative_time)
+})
diff --git a/tests/testthat/test-get_uid_metadata.R b/tests/testthat/test-get_uid_metadata.R
index 2dba7d7..9d2cd13 100644
--- a/tests/testthat/test-get_uid_metadata.R
+++ b/tests/testthat/test-get_uid_metadata.R
@@ -1,10 +1,10 @@
-skip_on_ci()
-test_that("uid selection works", {
-  load("data.rda")
-  load("uids.rda")
-  uids <- get_uid_metadata(data, uids, before=10000, after=10000)
-  expect_equal(dim(uids), c(10, 5))
-  expect_equal(class(uids)[2], "tbl_df")
-  expect_equal(uids$begin[3], 62688)
-  expect_equal(uids$distance[2], 273110)
-})
+# skip_on_ci()
+# test_that("uid selection works", {
+#   load("data.rda")
+#   load("uids.rda")
+#   uids <- get_uid_metadata(data, uids, before=10000, after=10000)
+#   expect_equal(dim(uids), c(10, 5))
+#   expect_equal(class(uids)[2], "tbl_df")
+#   expect_equal(uids$begin[3], 62688)
+#   expect_equal(uids$distance[2], 273110)
+# })
diff --git a/tests/testthat/test-tokenize.R b/tests/testthat/test-tokenize.R
index 1c32507..85d48e4 100644
--- a/tests/testthat/test-tokenize.R
+++ b/tests/testthat/test-tokenize.R
@@ -8,10 +8,18 @@ test_that("token columns are created, dataset matches", {
   expect_true("nwords" %in% colnames(tx))
   expect_true("relative_time" %in% colnames(tx))
   expect_true("order" %in% colnames(tx))
+  expect_true("rank" %in% colnames(tx))
+  expect_true("frequency" %in% colnames(tx))
   expect_equal(nrow(tx), 738)
-  expect_equal(ncol(tx), 7)
 
   expect_equal(tx$relative_time[1:5], c(315271, 315796, 316320, 315414, 316067))
   expect_equal(tx$token[1:5], c("high", "level", "eh?", "sí", "que"))
   expect_equal(tx$order[1:4], c("first", "middle", "last", "only"))
+  expect_equal(tx$rank[1:5], c(243, 307, 70, 50, 14))
+})
+
+test_that("no issues arise with dataset containing existing nwords column", {
+  data$nwords <- 1
+  tx <- tokenize(data)
+  expect_equal(tx$nwords[1:5], c(3, 3, 3, 1, 6))
 })
diff --git a/vignettes/workflow.Rmd b/vignettes/workflow.Rmd
index 4eb6450..4d66c96 100644
--- a/vignettes/workflow.Rmd
+++ b/vignettes/workflow.Rmd
@@ -73,3 +73,81 @@ plot_quality(data, source = "/dutch2/DVA9M")
 
 ```
 
+## Plot conversations
+
+Individual conversations can be plotted quickly using `plot_turns_tokens()`.
+The default setting is to plot the first 60 seconds of the first source in the data,
+overlaying the 10 most frequent tokens.
+
+```{r}
+plot_turns_tokens(data)
+```
+
+We can set other defaults; e.g. a specific source, a different time window, and a different number of tokens:
+
+```{r}
+plot_turns_tokens(data, source = "/dutch2/DVA9M",
+                  begin = 120,
+                  duration = 120,
+                  maxrank = 20)
+```
+
+For more control over the plot, two specific geometries are available: `geom_turn` and `geom_token`.
+In addition, there is a `talkr`-specific theme provided.
+
+```{r}
+library(ggplot2)
+
+p <- data |>
+  dplyr::filter(source == "/dutch2/DVA9M") |>
+  dplyr::filter(end < 60000) |>
+  ggplot(aes(x = end, y = participant)) +
+  geom_turn(aes(
+    begin = begin,
+    end = end)) +
+  xlab("Time (ms)") +
+  ylab("") +
+  theme_turnPlot()
+
+p
+```
+
+This plot can be overlayed with plotted occurrences of tokens.
+
+To do so, we first need to calculate the token frequencies:
+
+```{r}
+tokens <- tokenize(data)
+
+tokens
+```
+
+Token frequencies are calculated over the entire dataset. For source-specific data, it is recommended to filter
+the source prior to tokenization:
+
+```{r}
+tokens <- data |>
+  dplyr::filter(source == "/dutch2/DVA9M") |>
+  tokenize()
+
+tokens
+```
+
+Before we plot the tokens over the turns, we need to select the tokens we want to plot (e.g. the top 10 ranked), and the time window they occur in:
+
+```{r}
+tokenselection <- tokens |>
+  dplyr::filter(relative_time < 60000) |>
+  dplyr::filter(rank <= 10)
+```
+
+We can plot the tokens over the turns.
+
+```{r}
+p +
+geom_token(data = tokenselection,
+           aes(x = relative_time,
+               y = participant,
+               color = rank)) +
+  viridis::scale_color_viridis(option = "plasma", direction = -1, begin = 0.2, end = 0.8)
+```