Check with devel statsExpressions (#885)

* use devel statsExpressions

* minor cleanup

* fix example

* YAGNI grouped_list helper

API

@@ -8,7 +8,7 @@ extract_stats(p, ...)
 extract_subtitle(p)
 ggbarstats(data, x, y, counts = NULL, type = "parametric", paired = FALSE, results.subtitle = TRUE, label = "percentage", label.args = list(alpha = 1, fill = "white"), sample.size.label.args = list(size = 4), k = 2L, proportion.test = results.subtitle, perc.k = 0L, bf.message = TRUE, ratio = NULL, conf.level = 0.95, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, title = NULL, subtitle = NULL, caption = NULL, legend.title = NULL, xlab = NULL, ylab = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
 ggbetweenstats(data, x, y, type = "parametric", pairwise.display = "significant", p.adjust.method = "holm", effsize.type = "unbiased", bf.prior = 0.707, bf.message = TRUE, results.subtitle = TRUE, xlab = NULL, ylab = NULL, caption = NULL, title = NULL, subtitle = NULL, k = 2L, var.equal = FALSE, conf.level = 0.95, nboot = 100L, tr = 0.2, centrality.plotting = TRUE, centrality.type = type, centrality.point.args = list(size = 5, color = "darkred"), centrality.label.args = list(size = 3, nudge_x = 0.4, segment.linetype = 4, min.segment.length = 0), point.args = list(position = ggplot2::position_jitterdodge(dodge.width = 0.6), alpha = 0.4, size = 3, stroke = 0, na.rm = TRUE), boxplot.args = list(width = 0.3, alpha = 0.2, na.rm = TRUE), violin.args = list(width = 0.5, alpha = 0.2, na.rm = TRUE), ggsignif.args = list(textsize = 3, tip_length = 0.01, na.rm = TRUE), ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
-ggcoefstats(x, statistic = NULL, conf.int = TRUE, conf.level = 0.95, k = 2L, exclude.intercept = FALSE, effectsize.type = "eta", meta.analytic.effect = FALSE, meta.type = "parametric", bf.message = TRUE, sort = "none", xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, only.significant = FALSE, point.args = list(size = 3, color = "blue", na.rm = TRUE), errorbar.args = list(height = 0, na.rm = TRUE), vline = TRUE, vline.args = list(linewidth = 1, linetype = "dashed"), stats.labels = TRUE, stats.label.color = NULL, stats.label.args = list(size = 3, direction = "y", min.segment.length = 0), package = "RColorBrewer", palette = "Dark2", ggtheme = ggstatsplot::theme_ggstatsplot(), ...)
+ggcoefstats(x, statistic = NULL, conf.int = TRUE, conf.level = 0.95, k = 2L, exclude.intercept = FALSE, effectsize.type = "eta", meta.analytic.effect = FALSE, meta.type = "parametric", bf.message = TRUE, sort = "none", xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, only.significant = FALSE, point.args = list(size = 3, color = "blue", na.rm = TRUE), errorbar.args = list(height = 0, na.rm = TRUE), vline = TRUE, vline.args = list(linewidth = 1, linetype = "dashed"), stats.labels = TRUE, stats.label.color = NULL, stats.label.args = list(size = 3, direction = "y", min.segment.length = 0, na.rm = TRUE), package = "RColorBrewer", palette = "Dark2", ggtheme = ggstatsplot::theme_ggstatsplot(), ...)
 ggcorrmat(data, cor.vars = NULL, cor.vars.names = NULL, matrix.type = "upper", type = "parametric", tr = 0.2, partial = FALSE, k = 2L, sig.level = 0.05, conf.level = 0.95, bf.prior = 0.707, p.adjust.method = "holm", pch = "cross", ggcorrplot.args = list(method = "square", outline.color = "black", pch.cex = 14), package = "RColorBrewer", palette = "Dark2", colors = c("#E69F00", "white", "#009E73"), ggtheme = ggstatsplot::theme_ggstatsplot(), ggplot.component = NULL, title = NULL, subtitle = NULL, caption = NULL, ...)
 ggdotplotstats(data, x, y, xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, type = "parametric", test.value = 0, bf.prior = 0.707, bf.message = TRUE, effsize.type = "g", conf.level = 0.95, tr = 0.2, k = 2L, results.subtitle = TRUE, point.args = list(color = "black", size = 3, shape = 16), centrality.plotting = TRUE, centrality.type = type, centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"), ggplot.component = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), ...)
 gghistostats(data, x, binwidth = NULL, xlab = NULL, title = NULL, subtitle = NULL, caption = NULL, type = "parametric", test.value = 0, bf.prior = 0.707, bf.message = TRUE, effsize.type = "g", conf.level = 0.95, tr = 0.2, k = 2L, ggtheme = ggstatsplot::theme_ggstatsplot(), results.subtitle = TRUE, bin.args = list(color = "black", fill = "grey50", alpha = 0.7), centrality.plotting = TRUE, centrality.type = type, centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"), normal.curve = FALSE, normal.curve.args = list(linewidth = 2), ggplot.component = NULL, ...)

CITATION.cff

@@ -8,7 +8,7 @@ message: 'To cite package "ggstatsplot" in publications use:'
 type: software
 license: GPL-3.0-only
 title: 'ggstatsplot: ''ggplot2'' Based Plots with Statistical Details'
-version: 0.12.1
+version: 0.12.1.9000
 doi: 10.21105/joss.03167
 abstract: 'Extension of ''ggplot2'', ''ggstatsplot'' creates graphics with details
   from statistical tests included in the plots themselves. It provides an easier syntax
@@ -447,8 +447,8 @@ references:
     given-names: Indrajeet
     email: [email protected]
     orcid: https://orcid.org/0000-0003-1995-6531
-  version: '>= 1.5.2'
   year: '2023'
+  version: '>= 1.5.2.9000'
 - type: software
   title: tidyr
   abstract: 'tidyr: Tidy Messy Data'
@@ -511,7 +511,7 @@ references:
     given-names: Jeffrey N.
     email: [email protected]
   year: '2023'
-  version: '>= 0.9.12-4.4'
+  version: '>= 0.9.12-4.5'
 - type: software
   title: gapminder
   abstract: 'gapminder: Data from Gapminder'
@@ -736,7 +736,7 @@ references:
     given-names: Vaudor
     email: [email protected]
   year: '2023'
-  version: '>= 1.0.6'
+  version: '>= 1.0.7'
 - type: software
   title: withr
   abstract: 'withr: Run Code ''With'' Temporarily Modified Global State'

DESCRIPTION

@@ -48,12 +48,12 @@ Imports:
     purrr (>= 1.0.2),
     rlang,
     stats,
-    statsExpressions (>= 1.5.2),
+    statsExpressions (>= 1.5.2.9000),
     tidyr,
     utils
 Suggests:
     afex,
-    BayesFactor (>= 0.9.12-4.4),
+    BayesFactor (>= 0.9.12-4.5),
     gapminder,
     knitr,
     lme4,
@@ -67,9 +67,11 @@ Suggests:
     survival,
     testthat (>= 3.1.10),
     tibble,
-    vdiffr (>= 1.0.6),
+    vdiffr (>= 1.0.7),
     withr,
     WRS2
+Remotes:
+    IndrajeetPatil/statsExpressions
 VignetteBuilder: 
     knitr
 Encoding: UTF-8

R/ggbarstats.R

@@ -106,12 +106,12 @@ ggbarstats <- function(data,
     )
 
     subtitle_df <- .eval_f(contingency_table, !!!.f.args, type = type)
-    subtitle <- extract_expression(subtitle_df)
+    subtitle <- .extract_expression(subtitle_df)
 
     # Bayes Factor caption
     if (type != "bayes" && bf.message && isFALSE(paired)) {
       caption_df <- .eval_f(contingency_table, !!!.f.args, type = "bayes")
-      caption <- extract_expression(caption_df)
+      caption <- .extract_expression(caption_df)
     }
   }
 
@@ -124,13 +124,13 @@ ggbarstats <- function(data,
   onesample_df <- onesample_data(data, {{ x }}, {{ y }}, k)
 
   # if no. of factor levels is greater than the default palette color count
-  .palette_message(package, palette, nlevels(data %>% pull({{ x }})))
+  .is_palette_sufficient(package, palette, nlevels(data %>% pull({{ x }})))
 
   # plot
   plotBar <- ggplot(descriptive_df, aes({{ y }}, perc, fill = {{ x }})) +
     geom_bar(stat = "identity", position = "fill", color = "black") +
     scale_y_continuous(
-      labels       = function(x) paste0(x * 100L, "%"),
+      labels       = ~ insight::format_percent(., digits = 0L),
       breaks       = seq(from = 0.0, to = 1.0, by = 0.10),
       minor_breaks = seq(from = 0.05, to = 0.95, by = 0.10)
     ) +

R/ggbetweenstats.R

@@ -220,11 +220,11 @@ ggbetweenstats <- function(data,
 
     .f <- .f_switch(test)
     subtitle_df <- .eval_f(.f, !!!.f.args, type = type)
-    subtitle <- extract_expression(subtitle_df)
+    subtitle <- .extract_expression(subtitle_df)
 
     if (type == "parametric" && bf.message) {
       caption_df <- .eval_f(.f, !!!.f.args, type = "bayes")
-      caption <- extract_expression(caption_df)
+      caption <- .extract_expression(caption_df)
     }
   }
 

R/ggbetweenstats_helpers.R

@@ -235,7 +235,7 @@
                              ggplot.component = NULL,
                              ...) {
   # if no. of factor levels is greater than the default palette color count
-  .palette_message(package, palette, nlevels(x))
+  .is_palette_sufficient(package, palette, nlevels(x))
 
   plot +
     labs(

R/ggcoefstats.R

@@ -139,7 +139,12 @@ ggcoefstats <- function(x,
                         vline.args = list(linewidth = 1.0, linetype = "dashed"),
                         stats.labels = TRUE,
                         stats.label.color = NULL,
-                        stats.label.args = list(size = 3.0, direction = "y", min.segment.length = 0),
+                        stats.label.args = list(
+                          size = 3.0,
+                          direction = "y",
+                          min.segment.length = 0,
+                          na.rm = TRUE
+                        ),
                         package = "RColorBrewer",
                         palette = "Dark2",
                         ggtheme = ggstatsplot::theme_ggstatsplot(),
@@ -164,8 +169,7 @@ ggcoefstats <- function(x,
       ci              = conf.level,
       table_wide      = TRUE,
       ...
-    ) %>%
-      rename_all(~ gsub("omega2.|eta2.", "", .x))
+    )
 
     # anova objects need further cleaning
     if (all(c("df", "df.error") %in% names(tidy_df))) tidy_df %<>% mutate(effectsize = paste0("partial ", effectsize.type, "-squared"))
@@ -178,7 +182,7 @@ ggcoefstats <- function(x,
   }
 
   # create a new term column if it's not present
-  if (!"term" %in% names(tidy_df)) tidy_df %<>% mutate(term = paste("term", row_number(), sep = "_"))
+  if (!"term" %in% names(tidy_df)) tidy_df %<>% mutate(term = paste0("term_", row_number()))
 
   # check for duplicate terms and columns -------------------------
 
@@ -225,7 +229,7 @@ ggcoefstats <- function(x,
 
   tidy_df %<>% parameters::sort_parameters(sort = sort, column = "estimate")
 
-  # `term` needs to be a factor column; otherwise, ggplot2 will sort the x-axis
+  # `term` needs to be a factor column; otherwise, ggplot2 will sort the `x`-axis
   # labels alphabetically and terms won't appear in the expected order
   tidy_df %<>% dplyr::mutate(term = factor(term, tidy_df$term))
 
@@ -235,22 +239,22 @@ ggcoefstats <- function(x,
 
   if (!is.null(glance_df) && all(c("AIC", "BIC") %in% names(glance_df))) {
     glance_df %<>% mutate(expression = list(parse(text = glue("list(AIC=='{format_value(AIC, 0L)}', BIC=='{format_value(BIC, 0L)}')"))))
-    caption <- glance_df$expression[[1L]]
+    caption <- .extract_expression(glance_df)
   }
 
   # meta analysis -------------------------
 
   if (meta.analytic.effect) {
     meta.type <- stats_type_switch(meta.type)
 
-    # results from frequentist random-effects meta-analysis
+    # frequentist
     subtitle_df <- meta_analysis(tidy_df, type = meta.type, k = k)
-    subtitle <- subtitle_df$expression[[1L]]
+    subtitle <- .extract_expression(subtitle_df)
 
-    # results from Bayesian random-effects meta-analysis (only for parametric)
+    # Bayesian
     if (meta.type == "parametric" && bf.message) {
       caption_df <- suppressWarnings(meta_analysis(tidy_df, type = "bayes", k = k))
-      caption <- caption_df$expression[[1L]]
+      caption <- .extract_expression(caption_df)
     }
   }
 
@@ -276,7 +280,7 @@ ggcoefstats <- function(x,
   # ggrepel labels -------------------------
 
   if (stats.labels) {
-    if (is.null(stats.label.color) && .palette_message(package, palette, length(tidy_df$term))) {
+    if (is.null(stats.label.color) && .is_palette_sufficient(package, palette, length(tidy_df$term))) {
       stats.label.color <- paletteer::paletteer_d(paste0(package, "::", palette), length(tidy_df$term))
     }
 
@@ -287,7 +291,6 @@ ggcoefstats <- function(x,
         mapping = aes(x = estimate, y = term, label = expression),
         parse   = TRUE,
         color   = stats.label.color %||% "black",
-        na.rm   = TRUE,
         !!!stats.label.args
       )
   }

R/ggdotplotstats.R

@@ -106,11 +106,11 @@ ggdotplotstats <- function(data,
     )
 
     subtitle_df <- .eval_f(one_sample_test, !!!.f.args, type = type)
-    subtitle <- extract_expression(subtitle_df)
+    subtitle <- .extract_expression(subtitle_df)
 
     if (type == "parametric" && bf.message) {
       caption_df <- .eval_f(one_sample_test, !!!.f.args, type = "bayes")
-      caption <- extract_expression(caption_df)
+      caption <- .extract_expression(caption_df)
     }
   }
 

R/gghistostats.R

@@ -110,12 +110,12 @@ gghistostats <- function(data,
 
     # subtitle with statistical results
     subtitle_df <- .eval_f(one_sample_test, !!!.f.args, type = type)
-    subtitle <- extract_expression(subtitle_df)
+    subtitle <- .extract_expression(subtitle_df)
 
     # BF message
     if (type == "parametric" && bf.message) {
       caption_df <- .eval_f(one_sample_test, !!!.f.args, type = "bayes")
-      caption <- extract_expression(caption_df)
+      caption <- .extract_expression(caption_df)
     }
   }
 
@@ -131,7 +131,7 @@ gghistostats <- function(data,
     scale_y_continuous(
       sec.axis = sec_axis(
         trans  = ~ . / nrow(data),
-        labels = function(x) paste0(x * 100, "%"),
+        labels = function(x) insight::format_percent(x, digits = 0L),
         name   = "proportion"
       )
     ) +

R/ggpiestats.R

@@ -138,12 +138,12 @@ ggpiestats <- function(data,
     )
 
     subtitle_df <- .eval_f(contingency_table, !!!.f.args, type = type)
-    subtitle <- extract_expression(subtitle_df)
+    subtitle <- .extract_expression(subtitle_df)
 
     # Bayes Factor caption
     if (type != "bayes" && bf.message && isFALSE(paired)) {
       caption_df <- .eval_f(contingency_table, !!!.f.args, type = "bayes")
-      caption <- extract_expression(caption_df)
+      caption <- .extract_expression(caption_df)
     }
   }
 
@@ -156,7 +156,7 @@ ggpiestats <- function(data,
   if (test == "two.way") onesample_df <- onesample_data(data, {{ x }}, {{ y }}, k)
 
   # if no. of factor levels is greater than the default palette color count
-  .palette_message(package, palette, min_length = x_levels)
+  .is_palette_sufficient(package, palette, min_length = x_levels)
 
   # creating the basic plot
   plotPie <- ggplot(descriptive_df, mapping = aes(x = "", y = perc)) +

R/ggscatterstats.R

@@ -130,12 +130,12 @@ ggscatterstats <- function(data,
     )
 
     subtitle_df <- .eval_f(corr_test, !!!.f.args, type = type)
-    subtitle <- extract_expression(subtitle_df)
+    subtitle <- .extract_expression(subtitle_df)
 
     # BF message for null hypothesis support
     if (type == "parametric" && bf.message) {
       caption_df <- .eval_f(corr_test, !!!.f.args, type = "bayes")
-      caption <- extract_expression(caption_df)
+      caption <- .extract_expression(caption_df)
     }
   }
 

R/ggwithinstats.R

@@ -151,13 +151,13 @@ ggwithinstats <- function(data,
     # styler: off
     .f          <- .f_switch(test)
     subtitle_df <- .eval_f(.f, !!!.f.args, type = type)
-    subtitle    <- extract_expression(subtitle_df)
+    subtitle    <- .extract_expression(subtitle_df)
     # styler: on
 
     if (type == "parametric" && bf.message) {
       # styler: off
       caption_df <- .eval_f(.f, !!!.f.args, type = "bayes")
-      caption    <- extract_expression(caption_df)
+      caption    <- .extract_expression(caption_df)
       # styler: on
     }
   }

R/utils.R

@@ -1,4 +1,4 @@
-#' @title Split data frame into a list by grouping variable.
+#' @title Split data frame into a list by grouping variable
 #'
 #' @description
 #'
@@ -12,27 +12,27 @@
 #' @examplesIf identical(Sys.getenv("NOT_CRAN"), "true")
 #' ggstatsplot:::.grouped_list(ggplot2::msleep, grouping.var = vore)
 #' @keywords internal
-.grouped_list <- function(data, grouping.var = NULL) {
-  data <- as_tibble(data)
-
-  if (quo_is_null(enquo(grouping.var))) {
-    return(data)
-  }
-
-  data %>%
+.grouped_list <- function(data, grouping.var) {
+  as_tibble(data) %>%
     split(f = new_formula(NULL, enquo(grouping.var)), drop = TRUE) %>%
     list(data = ., title = names(.))
 }
 
 
-#' @title Message if palette doesn't have enough number of colors.
-#' @name .palette_message
-#' @description Informs the user about not using the default color palette
+#' @title Check if palette has enough number of colors
+#'
+#' @description
+#' Informs the user about not using the default color palette
 #'   when the number of factor levels is greater than 8, the maximum number of
-#'   colors allowed by `"Dark2"` palette from the `RColorBrewer` package.
+#'   colors allowed by `"Dark2"` palette from the `{RColorBrewer}` package.
+#'
+#' @examples
+#' ggstatsplot:::.is_palette_sufficient("RColorBrewer", "Dark2", 6L)
+#' ggstatsplot:::.is_palette_sufficient("RColorBrewer", "Dark2", 12L)
+#'
 #' @autoglobal
-#' @noRd
-.palette_message <- function(package, palette, min_length) {
+#' @keywords internal
+.is_palette_sufficient <- function(package, palette, min_length) {
   palette_length <- paletteer::palettes_d_names %>%
     filter(package == !!package, palette == !!palette) %$%
     length[[1L]]
@@ -49,6 +49,7 @@
   return(are_enough_colors_available)
 }
 
+
 #' @noRd
 .eval_f <- function(.f, ...) {
   tryCatch(
@@ -57,5 +58,6 @@
   )
 }
 
+
 #' @noRd
-extract_expression <- function(data) purrr::pluck(data, "expression", 1L, .default = NULL)
+.extract_expression <- function(data) purrr::pluck(data, "expression", 1L, .default = NULL)