Use dplyr to summarise()

DESCRIPTION

@@ -31,7 +31,7 @@ Depends:
     R (>= 3.1),
     ggplot2 (>= 3.4.4)
 Imports:
-    dplyr (>= 1.0.0),
+    dplyr (>= 1.1.0),
     tidyr (>= 1.3.0),
     grDevices,
     grid,

NAMESPACE

@@ -136,7 +136,10 @@ import(RColorBrewer)
 import(ggplot2)
 import(utils)
 importFrom(dplyr,all_of)
+importFrom(dplyr,arrange)
 importFrom(dplyr,group_by)
+importFrom(dplyr,n)
+importFrom(dplyr,pick)
 importFrom(dplyr,rename)
 importFrom(dplyr,summarise)
 importFrom(ggstats,StatCross)
@@ -170,7 +173,6 @@ importFrom(lifecycle,deprecate_soft)
 importFrom(lifecycle,deprecated)
 importFrom(magrittr,"%>%")
 importFrom(plyr,ddply)
-importFrom(plyr,summarize)
 importFrom(rlang,"%||%")
 importFrom(stats,anova)
 importFrom(stats,complete.cases)

R/gg-plots.R

@@ -1319,6 +1319,7 @@ ggally_facetbar <- function(data, mapping, ...) {
 #'   tips, ggplot2::aes(sex, day),
 #'   floor = 20, ceiling = 50
 #' ) + ggplot2::theme(aspect.ratio = 4 / 2))
+#' @importFrom dplyr all_of arrange n pick summarise
 ggally_ratio <- function(
     data,
     mapping = ggplot2::aes(!!!stats::setNames(lapply(colnames(data)[1:2], as.name), c("x", "y"))),
@@ -1329,7 +1330,9 @@ ggally_ratio <- function(
   xName <- mapping_string(mapping$x)
   yName <- mapping_string(mapping$y)
 
-  countData <- plyr::count(data, vars = c(xName, yName))
+  countData <- data %>%
+    summarise(freq = n(), .by = all_of(c(xName, yName))) %>%
+    arrange(pick(c(xName, yName)))
 
   # overwrite names so name clashes don't happen
   colnames(countData)[1:2] <- c("x", "y")
@@ -1756,6 +1759,7 @@ ggally_autopointDiag <- function(data, mapping, ...) {
 #'   }
 #'   p_(ggally_summarise_by(tips, mapping = aes(x = total_bill, y = day), text_fn = weighted_sum))
 #' }
+#' @importFrom dplyr arrange summarise
 ggally_summarise_by <- function(
     data,
     mapping,
@@ -1767,17 +1771,14 @@ ggally_summarise_by <- function(
 
   horizontal <- is_horizontal(data, mapping)
   if (horizontal) {
-    res <- ddply(
-      data.frame(
-        x = eval_data_col(data, mapping$x),
-        y = eval_data_col(data, mapping$y),
-        weight = eval_data_col(data, mapping$weight) %||% 1,
-        stringsAsFactors = FALSE
-      ),
-      c("y"),
-      plyr::here(summarize),
-      label = text_fn(x, weight)
-    )
+    res <- data.frame(
+      x = eval_data_col(data, mapping$x),
+      y = eval_data_col(data, mapping$y),
+      weight = eval_data_col(data, mapping$weight) %||% 1,
+      stringsAsFactors = FALSE
+    ) %>%
+      summarise(label = text_fn(x, weight), .by = y) %>%
+      arrange(y)
     # keep colour if matching the discrete variable
     if (mapping_string(mapping$colour) == mapping_string(mapping$y)) {
       col <- as.name("y")

R/ggparcoord.R

@@ -77,7 +77,8 @@ if (getRversion() >= "2.15.1") {
 #' @param title character string denoting the title of the plot
 #' @author Jason Crowley, Barret Schloerke, Dianne Cook, Heike Hofmann, Hadley Wickham
 #' @return ggplot object that if called, will print
-#' @importFrom plyr ddply summarize
+#' @importFrom dplyr arrange summarise
+#' @importFrom plyr ddply
 #' @importFrom stats complete.cases sd median mad lm spline
 #' @importFrom tidyr pivot_longer
 #' @export
@@ -512,10 +513,9 @@ ggparcoord <- function(
 
   if (!is.null(shadeBox)) {
     # Fix so that if missing = "min10", the box only goes down to the true min
-    d.sum <- ddply(data.m, c("variable"), summarize,
-      min = min(value),
-      max = max(value)
-    )
+    d.sum <- data.m %>%
+      summarise(min = min(value), max = max(value), .by = variable) %>%
+      arrange(variable)
     p <- p + geom_linerange(
       data = d.sum, linewidth = I(10), col = shadeBox,
       inherit.aes = FALSE,

tests/testthat/test-zzz_ggpairs.R

@@ -609,7 +609,10 @@ test_that("strip-top and strip-right", {
   data(tips)
 
   double_strips <- function(data, mapping, ...) {
-    dt <- plyr::count(data, c(mapping_string(mapping$x), mapping_string(mapping$y)))
+    cols <- c(mapping_string(mapping$x), mapping_string(mapping$y))
+    dt <- data %>%
+      summarise(freq = n(), .by = all_of(cols)) %>%
+      arrange(pick(cols))
     ggplot(dt, aes(xmin = 0.25, xmax = 0.75, ymin = 1, ymax = freq)) +
       geom_rect() +
       ggplot2::facet_grid(paste0(mapping_string(mapping$y), " ~ ", mapping_string(mapping$x))) +