diff --git a/.github/workflows/test-coverage.yaml b/.github/workflows/test-coverage.yaml
index 988226098e..eb448e9c28 100644
--- a/.github/workflows/test-coverage.yaml
+++ b/.github/workflows/test-coverage.yaml
@@ -35,14 +35,16 @@ jobs:
             clean = FALSE,
             install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
           )
+          print(cov)
           covr::to_cobertura(cov)
         shell: Rscript {0}
 
-      - uses: codecov/codecov-action@v4
+      - uses: codecov/codecov-action@v5
         with:
-          fail_ci_if_error: ${{ github.event_name != 'pull_request' && true || false }}
-          file: ./cobertura.xml
-          plugin: noop
+          # Fail if error if not on PR, or if on PR and token is given
+          fail_ci_if_error: ${{ github.event_name != 'pull_request' || secrets.CODECOV_TOKEN }}
+          files: ./cobertura.xml
+          plugins: noop
           disable_search: true
           token: ${{ secrets.CODECOV_TOKEN }}
 
diff --git a/DESCRIPTION b/DESCRIPTION
index 6b64da806e..be9f013c4a 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -20,7 +20,8 @@ Authors@R: c(
            comment = c(ORCID = "0000-0002-9415-4582")),
     person("Teun", "van den Brand", role = "aut",
            comment = c(ORCID = "0000-0002-9335-7468")),
-    person("Posit, PBC", role = c("cph", "fnd"))
+    person("Posit, PBC", role = c("cph", "fnd"),
+           comment = c(ROR = "03wc8by49"))
   )
 Description: A system for 'declaratively' creating graphics, based on "The
     Grammar of Graphics". You provide the data, tell 'ggplot2' how to map
@@ -30,7 +31,7 @@ License: MIT + file LICENSE
 URL: https://ggplot2.tidyverse.org, https://github.com/tidyverse/ggplot2
 BugReports: https://github.com/tidyverse/ggplot2/issues
 Depends:
-    R (>= 4.0)
+    R (>= 4.1)
 Imports:
     cli,
     grDevices,
@@ -77,7 +78,7 @@ VignetteBuilder:
     knitr
 Config/Needs/website: ggtext, tidyr, forcats, tidyverse/tidytemplate
 Config/testthat/edition: 3
-Config/usethis/last-upkeep: 2024-10-24
+Config/usethis/last-upkeep: 2025-04-23
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
diff --git a/LICENSE b/LICENSE
index f4515a155b..b0469670b3 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,2 +1,2 @@
-YEAR: 2024
+YEAR: 2025
 COPYRIGHT HOLDER: ggplot2 core developer team
diff --git a/LICENSE.md b/LICENSE.md
index ce73598634..7c6a53d75e 100644
--- a/LICENSE.md
+++ b/LICENSE.md
@@ -1,6 +1,6 @@
 # MIT License
 
-Copyright (c) 2024 ggplot2 core developer team
+Copyright (c) 2025 ggplot2 core developer team
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
diff --git a/R/annotation-logticks.R b/R/annotation-logticks.R
index 97caad7495..7fa69aa843 100644
--- a/R/annotation-logticks.R
+++ b/R/annotation-logticks.R
@@ -43,11 +43,11 @@
 #' a <- ggplot(msleep, aes(bodywt, brainwt)) +
 #'  geom_point(na.rm = TRUE) +
 #'  scale_x_log10(
-#'    breaks = scales::trans_breaks("log10", function(x) 10^x),
+#'    breaks = scales::trans_breaks("log10", \(x) 10^x),
 #'    labels = scales::trans_format("log10", scales::math_format(10^.x))
 #'  ) +
 #'  scale_y_log10(
-#'    breaks = scales::trans_breaks("log10", function(x) 10^x),
+#'    breaks = scales::trans_breaks("log10", \(x) 10^x),
 #'    labels = scales::trans_format("log10", scales::math_format(10^.x))
 #'  ) +
 #'  theme_bw()
diff --git a/R/geom-function.R b/R/geom-function.R
index 4b9c09fa0e..ba595da7c3 100644
--- a/R/geom-function.R
+++ b/R/geom-function.R
@@ -65,11 +65,9 @@ GeomFunction <- ggproto("GeomFunction", GeomPath,
 #'   geom_function(aes(colour = "t, df = 1"), fun = dt, args = list(df = 1))
 #'
 #' # Using a custom anonymous function
-#' base + geom_function(fun = function(x) 0.5 * exp(-abs(x)))
+#' base + geom_function(fun = \(x) 0.5 * exp(-abs(x)))
 #' # or using lambda syntax:
 #' # base + geom_function(fun = ~ 0.5 * exp(-abs(.x)))
-#' # or in R4.1.0 and above:
-#' # base + geom_function(fun = \(x) 0.5 * exp(-abs(x)))
 #' # or using a custom named function:
 #' # f <- function(x) 0.5 * exp(-abs(x))
 #' # base + geom_function(fun = f)
diff --git a/R/geom-histogram.R b/R/geom-histogram.R
index 8272d818f9..a922a54dd7 100644
--- a/R/geom-histogram.R
+++ b/R/geom-histogram.R
@@ -132,7 +132,7 @@
 #' # different ranges because the function will be called once per facet
 #' ggplot(economics_long, aes(value)) +
 #'   facet_wrap(~variable, scales = 'free_x') +
-#'   geom_histogram(binwidth = function(x) 2 * IQR(x) / (length(x)^(1/3)))
+#'   geom_histogram(binwidth = \(x) 2 * IQR(x) / (length(x)^(1/3)))
 geom_histogram <- make_constructor(
   GeomBar, stat = "bin", position = "stack",
   # Passed to bin stat:
diff --git a/R/geom-map.R b/R/geom-map.R
index 8d9e415c2f..026bb94e6b 100644
--- a/R/geom-map.R
+++ b/R/geom-map.R
@@ -55,7 +55,7 @@ NULL
 #'
 #'   crimes <- data.frame(state = tolower(rownames(USArrests)), USArrests)
 #'
-#'   # Equivalent to crimes %>% tidyr::pivot_longer(Murder:Rape)
+#'   # Equivalent to crimes |> tidyr::pivot_longer(Murder:Rape)
 #'   vars <- lapply(names(crimes)[-1], function(j) {
 #'     data.frame(state = crimes$state, variable = j, value = crimes[[j]])
 #'   })
diff --git a/R/labeller.R b/R/labeller.R
index 6d3c1b10ae..ad57a4f283 100644
--- a/R/labeller.R
+++ b/R/labeller.R
@@ -85,7 +85,7 @@
 #' p + facet_grid(. ~ cyl2, labeller = label_parsed)
 #'
 #' # Include optional argument in label function
-#' p + facet_grid(. ~ cyl, labeller = function(x) label_both(x, sep = "="))
+#' p + facet_grid(. ~ cyl, labeller = \(x) label_both(x, sep = "="))
 #' }
 #' @name labellers
 NULL
diff --git a/R/stat-summary-2d.R b/R/stat-summary-2d.R
index 16319db269..84e79c63d9 100644
--- a/R/stat-summary-2d.R
+++ b/R/stat-summary-2d.R
@@ -99,7 +99,7 @@ StatSummary2d <- ggproto(
 #' d + stat_summary_2d()
 #'
 #' # Specifying function
-#' d + stat_summary_2d(fun = function(x) sum(x^2))
+#' d + stat_summary_2d(fun = \(x) sum(x^2))
 #' d + stat_summary_2d(fun = ~ sum(.x^2))
 #' d + stat_summary_2d(fun = var)
 #' d + stat_summary_2d(fun = "quantile", fun.args = list(probs = 0.1))
diff --git a/R/utilities-tidy-eval.R b/R/utilities-tidy-eval.R
index eac1085256..41895f4fcb 100644
--- a/R/utilities-tidy-eval.R
+++ b/R/utilities-tidy-eval.R
@@ -23,8 +23,8 @@
 #'
 #'   ```
 #'   my_function <- function(data, var, ...) {
-#'     data %>%
-#'       group_by(...) %>%
+#'     data |>
+#'       group_by(...) |>
 #'       summarise(mean = mean({{ var }}))
 #'   }
 #'   ```
@@ -43,8 +43,8 @@
 #'     dots <- enquos(...)
 #'
 #'     # Inject
-#'     data %>%
-#'       group_by(!!!dots) %>%
+#'     data |>
+#'       group_by(!!!dots) |>
 #'       summarise(mean = mean(!!var))
 #'   }
 #'   ```
@@ -60,7 +60,7 @@
 #'
 #'   ```
 #'   my_var <- "disp"
-#'   mtcars %>% summarise(mean = mean(.data[[my_var]]))
+#'   mtcars |> summarise(mean = mean(.data[[my_var]]))
 #'   ```
 #'
 #' * Another tidy eval operator is `:=`. It makes it possible to use
@@ -72,7 +72,7 @@
 #'   my_function <- function(data, var, suffix = "foo") {
 #'     # Use `{{` to tunnel function arguments and the usual glue
 #'     # operator `{` to interpolate plain strings.
-#'     data %>%
+#'     data |>
 #'       summarise("{{ var }}_mean_{suffix}" := mean({{ var }}))
 #'   }
 #'   ```
@@ -87,7 +87,7 @@
 #'   my_function <- function(data, var, suffix = "foo") {
 #'     var <- enquo(var)
 #'     prefix <- as_label(var)
-#'     data %>%
+#'     data |>
 #'       summarise("{prefix}_mean_{suffix}" := mean(!!var))
 #'   }
 #'   ```
diff --git a/man/annotation_logticks.Rd b/man/annotation_logticks.Rd
index b37a54560d..aae0172de3 100644
--- a/man/annotation_logticks.Rd
+++ b/man/annotation_logticks.Rd
@@ -73,11 +73,11 @@ These tick marks probably make sense only for base 10.
 a <- ggplot(msleep, aes(bodywt, brainwt)) +
  geom_point(na.rm = TRUE) +
  scale_x_log10(
-   breaks = scales::trans_breaks("log10", function(x) 10^x),
+   breaks = scales::trans_breaks("log10", \(x) 10^x),
    labels = scales::trans_format("log10", scales::math_format(10^.x))
  ) +
  scale_y_log10(
-   breaks = scales::trans_breaks("log10", function(x) 10^x),
+   breaks = scales::trans_breaks("log10", \(x) 10^x),
    labels = scales::trans_format("log10", scales::math_format(10^.x))
  ) +
  theme_bw()
diff --git a/man/geom_function.Rd b/man/geom_function.Rd
index f9bf5cb0b2..7198e9e5ca 100644
--- a/man/geom_function.Rd
+++ b/man/geom_function.Rd
@@ -197,11 +197,9 @@ base +
   geom_function(aes(colour = "t, df = 1"), fun = dt, args = list(df = 1))
 
 # Using a custom anonymous function
-base + geom_function(fun = function(x) 0.5 * exp(-abs(x)))
+base + geom_function(fun = \(x) 0.5 * exp(-abs(x)))
 # or using lambda syntax:
 # base + geom_function(fun = ~ 0.5 * exp(-abs(.x)))
-# or in R4.1.0 and above:
-# base + geom_function(fun = \(x) 0.5 * exp(-abs(x)))
 # or using a custom named function:
 # f <- function(x) 0.5 * exp(-abs(x))
 # base + geom_function(fun = f)
diff --git a/man/geom_histogram.Rd b/man/geom_histogram.Rd
index 686ebc98c9..b298a092a2 100644
--- a/man/geom_histogram.Rd
+++ b/man/geom_histogram.Rd
@@ -337,7 +337,7 @@ m +
 # different ranges because the function will be called once per facet
 ggplot(economics_long, aes(value)) +
   facet_wrap(~variable, scales = 'free_x') +
-  geom_histogram(binwidth = function(x) 2 * IQR(x) / (length(x)^(1/3)))
+  geom_histogram(binwidth = \(x) 2 * IQR(x) / (length(x)^(1/3)))
 }
 \seealso{
 \code{\link[=stat_count]{stat_count()}}, which counts the number of cases at each x
diff --git a/man/geom_map.Rd b/man/geom_map.Rd
index 22f9598833..f287efe53e 100644
--- a/man/geom_map.Rd
+++ b/man/geom_map.Rd
@@ -143,7 +143,7 @@ if (require(maps)) {
 
   crimes <- data.frame(state = tolower(rownames(USArrests)), USArrests)
 
-  # Equivalent to crimes \%>\% tidyr::pivot_longer(Murder:Rape)
+  # Equivalent to crimes |> tidyr::pivot_longer(Murder:Rape)
   vars <- lapply(names(crimes)[-1], function(j) {
     data.frame(state = crimes$state, variable = j, value = crimes[[j]])
   })
diff --git a/man/ggplot2-package.Rd b/man/ggplot2-package.Rd
index 23ed67a2a5..4a57a87766 100644
--- a/man/ggplot2-package.Rd
+++ b/man/ggplot2-package.Rd
@@ -37,7 +37,7 @@ Authors:
 
 Other contributors:
 \itemize{
-  \item Posit, PBC [copyright holder, funder]
+  \item Posit, PBC (03wc8by49) [copyright holder, funder]
 }
 
 }
diff --git a/man/labellers.Rd b/man/labellers.Rd
index 09f160bf40..70ac8bf712 100644
--- a/man/labellers.Rd
+++ b/man/labellers.Rd
@@ -110,7 +110,7 @@ p + facet_grid(. ~ cyl2)
 p + facet_grid(. ~ cyl2, labeller = label_parsed)
 
 # Include optional argument in label function
-p + facet_grid(. ~ cyl, labeller = function(x) label_both(x, sep = "="))
+p + facet_grid(. ~ cyl, labeller = \(x) label_both(x, sep = "="))
 }
 }
 \seealso{
diff --git a/man/stat_summary_2d.Rd b/man/stat_summary_2d.Rd
index d0a6f4da31..41517514cc 100644
--- a/man/stat_summary_2d.Rd
+++ b/man/stat_summary_2d.Rd
@@ -217,7 +217,7 @@ d <- ggplot(diamonds, aes(carat, depth, z = price))
 d + stat_summary_2d()
 
 # Specifying function
-d + stat_summary_2d(fun = function(x) sum(x^2))
+d + stat_summary_2d(fun = \(x) sum(x^2))
 d + stat_summary_2d(fun = ~ sum(.x^2))
 d + stat_summary_2d(fun = var)
 d + stat_summary_2d(fun = "quantile", fun.args = list(probs = 0.1))
diff --git a/man/tidyeval.Rd b/man/tidyeval.Rd
index 41fed21ef8..36266b4153 100644
--- a/man/tidyeval.Rd
+++ b/man/tidyeval.Rd
@@ -35,8 +35,8 @@ passed from function arguments inside other tidy eval functions.
 arguments contained in dots, use \code{...} in the normal way.
 
 \if{html}{\out{<div class="sourceCode">}}\preformatted{my_function <- function(data, var, ...) \{
-  data \%>\%
-    group_by(...) \%>\%
+  data |>
+    group_by(...) |>
     summarise(mean = mean(\{\{ var \}\}))
 \}
 }\if{html}{\out{</div>}}
@@ -53,8 +53,8 @@ into an evaluation context with \verb{!!} (for a single expression) and
   dots <- enquos(...)
 
   # Inject
-  data \%>\%
-    group_by(!!!dots) \%>\%
+  data |>
+    group_by(!!!dots) |>
     summarise(mean = mean(!!var))
 \}
 }\if{html}{\out{</div>}}
@@ -68,7 +68,7 @@ slice of data. If you have a variable name in a string, use the
 \code{.data} pronoun to subset that variable with \code{[[}.
 
 \if{html}{\out{<div class="sourceCode">}}\preformatted{my_var <- "disp"
-mtcars \%>\% summarise(mean = mean(.data[[my_var]]))
+mtcars |> summarise(mean = mean(.data[[my_var]]))
 }\if{html}{\out{</div>}}
 \item Another tidy eval operator is \verb{:=}. It makes it possible to use
 glue and curly-curly syntax on the LHS of \code{=}. For technical
@@ -78,7 +78,7 @@ the left of \code{=}, so we use \verb{:=} as a workaround.
 \if{html}{\out{<div class="sourceCode">}}\preformatted{my_function <- function(data, var, suffix = "foo") \{
   # Use `\{\{` to tunnel function arguments and the usual glue
   # operator `\{` to interpolate plain strings.
-  data \%>\%
+  data |>
     summarise("\{\{ var \}\}_mean_\{suffix\}" := mean(\{\{ var \}\}))
 \}
 }\if{html}{\out{</div>}}
@@ -91,7 +91,7 @@ can be reproduced manually with:
 \if{html}{\out{<div class="sourceCode">}}\preformatted{my_function <- function(data, var, suffix = "foo") \{
   var <- enquo(var)
   prefix <- as_label(var)
-  data \%>\%
+  data |>
     summarise("\{prefix\}_mean_\{suffix\}" := mean(!!var))
 \}
 }\if{html}{\out{</div>}}
diff --git a/tests/testthat/test-facet-.R b/tests/testthat/test-facet-.R
index a24a5e4ca5..71f78c1cf2 100644
--- a/tests/testthat/test-facet-.R
+++ b/tests/testthat/test-facet-.R
@@ -230,7 +230,7 @@ test_that("facet variables", {
 test_that("facet gives clear error if ", {
   df <- data_frame(x = 1)
   expect_snapshot_error(print(ggplot(df, aes(x)) + facet_grid(x ~ x)))
-  expect_snapshot_error(print(ggplot(df, aes(x)) %>% facet_grid(. ~ x)))
+  expect_snapshot_error(print(ggplot(df, aes(x)) |> facet_grid(. ~ x)))
   expect_snapshot_error(print(ggplot(df, aes(x)) + facet_grid(list(1, 2, 3))))
   expect_snapshot_error(print(ggplot(df, aes(x)) + facet_grid(vars(x), "free")))
 })
diff --git a/tests/testthat/test-stat-bin.R b/tests/testthat/test-stat-bin.R
index de1c941b1e..3568faa819 100644
--- a/tests/testthat/test-stat-bin.R
+++ b/tests/testthat/test-stat-bin.R
@@ -73,7 +73,7 @@ test_that("fuzzy breaks are used when cutting", {
   p <- ggplot(df, aes(x)) +
     geom_histogram(binwidth = 0.1, boundary = 0.1, closed = "left")
 
-  bins <- get_layer_data(p) %>% subset(count > 0) %>% .[1:5]
+  bins <- get_layer_data(p) |> subset(count > 0) |> head(5)
   expect_equal(bins$count, c(1, 1, 1, 1))
 })
 
diff --git a/vignettes/articles/faq-annotation.Rmd b/vignettes/articles/faq-annotation.Rmd
index ff382d40b3..6057b63fbd 100644
--- a/vignettes/articles/faq-annotation.Rmd
+++ b/vignettes/articles/faq-annotation.Rmd
@@ -142,8 +142,8 @@ Note that we expanded the y axis limit to get the numbers to fit on the plot.
 ```{r}
 #| fig.alt: "A bar chart showing the number of cars for each of three types
 #|  of drive train. The count values are displayed on top of the bars as text."
-mpg %>%
-  dplyr::count(drv) %>%
+mpg |>
+  dplyr::count(drv) |>
   ggplot(aes(x = drv, y = n)) +
   geom_col() +
   geom_text(aes(label = n), vjust = -0.5) +
@@ -184,7 +184,7 @@ ggplot(mpg, aes(x = class, fill = drv)) +
 You can first calculate the counts for each segment with `dplyr::count()`, which will place these values in a column called `n`.
 
 ```{r}
-mpg %>%
+mpg |>
   count(class, drv) 
 ```
 
@@ -195,8 +195,8 @@ You can then pass this result directly to `ggplot()`, draw the segments with app
 #|  types of cars. The fill colour of the bars indicate the type of drive 
 #|  train. In the middle of each filled part, the count value is displayed as 
 #|  text."
-mpg %>%
-  count(class, drv) %>%
+mpg |>
+  count(class, drv) |>
   ggplot(aes(x = class, fill = drv, y = n)) +
   geom_col() +
   geom_text(aes(label = n), size = 3, position = position_stack(vjust = 0.5))
@@ -226,9 +226,9 @@ One option is to calculate the proportions with `dplyr::count()` and then use `g
 ```{r}
 #| fig.alt: "A bar chart showing the proportion of cars for each of three types
 #|  of drive train."
-mpg %>%
-  dplyr::count(drv) %>%
-  mutate(prop = n / sum(n)) %>%
+mpg |>
+  dplyr::count(drv) |>
+  mutate(prop = n / sum(n)) |>
   ggplot(aes(x = drv, y = prop)) +
   geom_col()
 ```
diff --git a/vignettes/articles/faq-bars.Rmd b/vignettes/articles/faq-bars.Rmd
index daae53ef58..1ba10653c9 100644
--- a/vignettes/articles/faq-bars.Rmd
+++ b/vignettes/articles/faq-bars.Rmd
@@ -258,7 +258,7 @@ poll <- tribble(
 You can first pivot the data longer to obtain a data frame with one row per party/opinion combination and a new column, `n`, for the number of responses that fall into that category.
 
 ```{r}
-poll_longer <- poll %>%
+poll_longer <- poll |>
   pivot_longer(
     cols = -party,
     names_to = "opinion",
@@ -318,12 +318,12 @@ Then, pass the resulting longer data frame to `ggplot()` group responses for eac
 #| fig.alt: "A grouped bar chart showing the number of responses to three 
 #|  questions. Within each question, two bars denote an 'Agree' or 'Disagree' 
 #|  response."
-survey %>%
+survey |>
   tidyr::pivot_longer(
     cols = -respondent,
     names_to = "question",
     values_to = "response"
-  ) %>%
+  ) |>
   ggplot(aes(x = question, fill = response)) +
   geom_bar(position = "dodge")
 ```
@@ -344,9 +344,9 @@ Then, you can pass the resulting data frame to `ggplot()` and plot bars using `g
 ```{r}
 #| fig.alt: "A bar chart showing the average highway miles per gallon for 
 #|  three types of drive train."
-mpg %>%
-  group_by(drv) %>%
-  summarise(mean_hwy = mean(hwy)) %>%
+mpg |>
+  group_by(drv) |>
+  summarise(mean_hwy = mean(hwy)) |>
   ggplot(aes(x = drv, y = mean_hwy)) +
   geom_col()
 ```
diff --git a/vignettes/articles/faq-faceting.Rmd b/vignettes/articles/faq-faceting.Rmd
index d5a6926d83..25ad44e174 100644
--- a/vignettes/articles/faq-faceting.Rmd
+++ b/vignettes/articles/faq-faceting.Rmd
@@ -121,8 +121,8 @@ First, calculate these means and save them in a new data frame.
 ```{r}
 library(dplyr)
 
-mpg_summary <- mpg %>%
-  group_by(drv) %>%
+mpg_summary <- mpg |>
+  group_by(drv) |>
   summarise(hwy_mean = mean(hwy))
 
 mpg_summary
diff --git a/vignettes/articles/faq-reordering.Rmd b/vignettes/articles/faq-reordering.Rmd
index 964dd6ba08..1cdfa2571c 100644
--- a/vignettes/articles/faq-reordering.Rmd
+++ b/vignettes/articles/faq-reordering.Rmd
@@ -234,9 +234,9 @@ Now the blue circle is over the yellow triangle since 0.01 comes after 0 and sim
 #|  four x-positions, of which two are very distinct. Every point has a distinct 
 #|  shape and colour. A blue circle is plotted on top of a yellow triangle. A 
 #|  red square is plotted on top of a black asterisk."
-df_arranged <- df %>% dplyr::arrange(x)
+df_arranged <- df |> dplyr::arrange(x)
 
-df_arranged %>%
+df_arranged |>
   ggplot(aes(x = x, y = y, fill = fill, shape = shape)) +
   geom_point(size = 8) +
   scale_shape_identity() +
@@ -257,14 +257,14 @@ If you wanted to make sure that the observation identified with an asterisk is a
 #|  asterisk is plotted on top of a red square."
 
 ggplot(mapping = aes(x = x, y = y, fill = fill, shape = shape)) +
-  geom_point(data = df %>% filter(shape != "asterisk"), size = 8) +
-  geom_point(data = df %>% filter(shape == "asterisk"), size = 8) +
+  geom_point(data = df |> filter(shape != "asterisk"), size = 8) +
+  geom_point(data = df |> filter(shape == "asterisk"), size = 8) +
   scale_shape_identity() +
   scale_fill_identity()
 
 ggplot(mapping = aes(x = x, y = y, fill = fill, shape = shape)) +
-  geom_point(data = df_arranged %>% filter(shape != "asterisk"), size = 8) +
-  geom_point(data = df_arranged %>% filter(shape == "asterisk"), size = 8) +
+  geom_point(data = df_arranged |> filter(shape != "asterisk"), size = 8) +
+  geom_point(data = df_arranged |> filter(shape == "asterisk"), size = 8) +
   scale_shape_identity() +
   scale_fill_identity()
 ```