stat_joy improvements.

NEWS

@@ -0,0 +1,13 @@
+ggjoy 0.2.0
+----------------------------------------------------------------
+Numerous improvements:
+- New stat `binline` that can be used to draw histogram joyplots.
+- Various improvements in `stat_joy`. In particular, it now works properly
+  with multiple panels. It also now has parameters `from` and `to` to limit the
+  range of density estimation, just like `density()`.
+- Improvements in the vignettes
+- New geoms `geom_ridgeline_gradient` and `geom_joy_gradient` that can handle gradient fills.
+
+ggjoy 0.1.0
+----------------------------------------------------------------
+First complete implementation ready for initial release

R/stats.R

@@ -8,12 +8,14 @@
 #'
 #' @param geom The geometric object to use to display the data.
 #' @param bandwidth Bandwidth used for density calculation. If not provided, is estimated from the data.
+#' @param from,to The left and right-most points of the grid at which the density is to be estimated,
+#'   as in [density()]. If not provided, there are estimated from the data range and the bandwidth.
 #' @inheritParams geom_ridgeline
 #' @importFrom ggplot2 layer
 #' @export
 stat_joy <- function(mapping = NULL, data = NULL, geom = "joy",
                      position = "identity", na.rm = FALSE, show.legend = NA,
-                     inherit.aes = TRUE, bandwidth = NULL, ...)
+                     inherit.aes = TRUE, bandwidth = NULL, from = NULL, to = NULL, ...)
 {
   layer(
     stat = StatJoy,
@@ -23,7 +25,10 @@ stat_joy <- function(mapping = NULL, data = NULL, geom = "joy",
     position = position,
     show.legend = show.legend,
     inherit.aes = inherit.aes,
-    params = list(bandwidth = bandwidth, na.rm = na.rm, ...)
+    params = list(bandwidth = bandwidth,
+                  from = from,
+                  to = to,
+                  na.rm = na.rm, ...)
   )
 }
 
@@ -49,18 +54,18 @@ StatJoy <- ggproto("StatJoy", Stat,
       params$bandwidth <- bw
     }
 
-    if (is.null(params$min)) {
-      params$min <- min(data$x, na.rm=TRUE) - 3 * params$bandwidth
+    if (is.null(params$from)) {
+      params$from <- min(data$x, na.rm=TRUE) - 3 * params$bandwidth
     }
 
-    if (is.null(params$max)) {
-      params$max <- max(data$x, na.rm=TRUE) + 3 * params$bandwidth
+    if (is.null(params$to)) {
+      params$to <- max(data$x, na.rm=TRUE) + 3 * params$bandwidth
     }
 
     data.frame(
       bandwidth = params$bandwidth,
-      min = params$min,
-      max = params$max
+      from = params$from,
+      to = params$to
     )
   },
 
@@ -72,13 +77,13 @@ StatJoy <- ggproto("StatJoy", Stat,
 
     list(
       bandwidth = pardata$bandwidth,
-      min = pardata$min,
-      max = pardata$max,
+      from = pardata$from,
+      to = pardata$to,
       na.rm = params$na.rm
     )
   },
 
-  compute_group = function(data, scales, min, max, bandwidth = 1) {
+  compute_group = function(data, scales, from, to, bandwidth = 1) {
     # ignore too small groups
     if(nrow(data) < 3) return(data.frame())
 
@@ -88,7 +93,7 @@ StatJoy <- ggproto("StatJoy", Stat,
     }
     panel_id <- as.numeric(panel)
 
-    d <- density(data$x, bw = bandwidth[panel_id], from = min[panel_id], to = max[panel_id], na.rm = TRUE)
+    d <- density(data$x, bw = bandwidth[panel_id], from = from[panel_id], to = to[panel_id], na.rm = TRUE)
     data.frame(x = d$x, density = d$y)
   }
 )

vignettes/gallery.Rmd

@@ -45,14 +45,15 @@ library(forcats)
 Catalan_elections %>%
   mutate(Alt = (as.numeric(as.factor(Year))-1) %% 2 + 1) %>%
   ggplot(aes(y = as.factor(Year) %>% fct_rev())) +
-  geom_joy(aes(x = Percent, fill = paste(Option, Alt)), alpha = .8, color = "white") +
+  geom_joy(aes(x = Percent, fill = paste(Option, Alt)), 
+           alpha = .8, color = "white", from = 0, to = 100) +
   labs(x = "Vote (%)",
        y = "Election Year",
        title = "Indy vs Unionist vote in Catalan elections",
        subtitle = "Analysis unit: municipalities (n = 949)",
        caption = "Marc Belzunces (@marcbeldata) | Source: Idescat") +
   scale_y_discrete(expand = c(0.01, 0)) +
-  scale_x_continuous(limits = c(0, 100), expand = c(0.01, 0)) +
+  scale_x_continuous(expand = c(0.01, 0)) +
   scale_fill_manual(breaks = c("Indy 1", "Unionist 1"),
                     labels = c(`Indy 1` = "Indy", `Unionist 1` = "Unionist"),
                     values = c("#ff0000", "#ff8080", "#0000ff", "#8080ff"),

vignettes/introduction.Rmd

@@ -103,9 +103,9 @@ ggplot(iris, aes(x = Sepal.Length, y = Species)) +
 ```
 
 
-## Theme
+## Themes
 
-Joyplots tend to require some theme modifications to look good. Most importantly, the y-axis labels should be vertically aligned so that they are flush with the axis ticks rather than vertically centered. The ggjoy package provides a theme `theme_joy` that does this and a few other theme modifications.
+Joyplots tend to require some theme modifications to look good. Most importantly, the y-axis tick labels should be vertically aligned so that they are flush with the axis ticks rather than vertically centered. The ggjoy package provides a theme `theme_joy` that does this and a few other theme modifications.
 
 ```{r message=FALSE}
 ggplot(iris, aes(x = Sepal.Length, y = Species)) + geom_joy() + theme_joy()
@@ -128,6 +128,16 @@ ggplot(iris, aes(x = Sepal.Length, y = Species)) +
   scale_y_discrete(expand = c(0.01, 0))
 ```
 
+If you prefer to use a different theme than `theme_joy`, for example `theme_minimal`, it is still advisable to adjust the alignment of the axis tick labels and the axis scales.
+```{r message=FALSE}
+ ggplot(iris, aes(x = Sepal.Length, y = Species)) + 
+   geom_joy() + 
+   theme_minimal(base_size = 14) + theme(axis.text.y = element_text(vjust = 0)) +
+   scale_x_continuous(expand = c(0.01, 0)) +
+   scale_y_discrete(expand = c(0.01, 0))
+```
+
+
 ## Stats
 
 The default stat used with `geom_joy` is `stat_joy`. However, it may not do exactly what you want it to do, and there are other stats that can be used that may be better for your respective application.