diff --git a/NAMESPACE b/NAMESPACE
index 2b4e328e..6e90e9ef 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -30,6 +30,7 @@ export(type_polypath)
 export(type_qq)
 export(type_rect)
 export(type_ribbon)
+export(type_ridge)
 export(type_segments)
 export(type_spineplot)
 export(type_spline)
@@ -89,6 +90,7 @@ importFrom(stats,glm)
 importFrom(stats,lm)
 importFrom(stats,loess)
 importFrom(stats,loess.control)
+importFrom(stats,median)
 importFrom(stats,model.frame)
 importFrom(stats,na.omit)
 importFrom(stats,ppoints)
diff --git a/NEWS.md b/NEWS.md
index 718e209c..8377ddb9 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -42,12 +42,14 @@ New plot `type` logic and functional equivalents:
 New plot types:
 
   - Visualizations:
-    - `type_spineplot()` (shortcut: `"spineplot"`) type for producing spine
-    plots and spinograms. These are modified versions of a histogram or mosaic
-    plot, and are particularly useful for visualizing factor variables. (#233
+    - `type_spineplot()` (shortcut: `"spineplot"`) spine plots and
+    spinograms. These are modified versions of a histogram or mosaic plot,
+    and are particularly useful for visualizing factor variables. (#233
     @zeileis with contributions from @grantmcdermott)
-    - `type_qq()` (shortcut: "qq") type for quantile-quantile plots. (#251
+    - `type_qq()` (shortcut: "qq") for quantile-quantile plots. (#251
     @vincentarelbundock)
+    - `type_ridge()` (shortcut: `"ridge"`) for ridge plots aka Joy plots.
+    (#252 @vincentarelbundock, @zeileis, and @grantmcdermott)
   - Models:
     - `type_glm()` (shortcut: `"glm"`) (@vincentarelbundock)
     - `type_lm()` (shortcut: `"lm"`) (@vincentarelbundock)
diff --git a/R/draw_legend.R b/R/draw_legend.R
index 0b60edf9..c6032850 100644
--- a/R/draw_legend.R
+++ b/R/draw_legend.R
@@ -159,7 +159,11 @@ draw_legend = function(
   if (is.null(legend_args[["horiz"]])) legend_args[["horiz"]] = FALSE
   if (is.null(legend_args[["xpd"]])) legend_args[["xpd"]] = NA
   if (is.null(legend_args[["pt.bg"]])) {
-    legend_args[["pt.bg"]] = if (identical(type, "spineplot")) legend_args[["col"]] else bg
+    if (identical(type, "ridge") && isFALSE(gradient)) {
+      legend_args[["pt.bg"]] = sapply(legend_args[["col"]], function(ccol) seq_palette(ccol, n = 2)[2])
+    } else {
+      legend_args[["pt.bg"]] = if (identical(type, "spineplot")) legend_args[["col"]] else bg
+    }
   }
   if (
     type %in% c("p", "pointrange", "errorbar") &&
@@ -168,10 +172,10 @@ draw_legend = function(
   ) {
     legend_args[["pt.cex"]] = cex
   }
-  if (type %in% c("rect", "ribbon", "polygon", "polypath", "boxplot", "hist", "histogram", "spineplot") || isTRUE(gradient)) {
+  if (type %in% c("rect", "ribbon", "polygon", "polypath", "boxplot", "hist", "histogram", "spineplot", "ridge") || isTRUE(gradient)) {
     legend_args[["pch"]] = 22
     if (is.null(legend_args[["pt.cex"]])) legend_args[["pt.cex"]] = 3.5
-    if (is.null(legend_args[["pt.lwd"]]) && (!is.null(type) && !(type %in% c("rect", "polygon", "polypath", "boxplot")))) {
+    if (is.null(legend_args[["pt.lwd"]]) && (!is.null(type) && !(type %in% c("rect", "polygon", "polypath", "boxplot", "ridge")))) {
       legend_args[["pt.lwd"]] = 0
     }
     if (is.null(legend_args[["y.intersp"]])) legend_args[["y.intersp"]] = 1.25
diff --git a/R/sanitize.R b/R/sanitize.R
index 699355e3..8f7e14de 100644
--- a/R/sanitize.R
+++ b/R/sanitize.R
@@ -12,7 +12,7 @@ sanitize_type = function(type, x, y) {
   }
 
   types = c(
-    "area", "boxplot", "density", "jitter", "ribbon", "pointrange", "hist",
+    "area", "boxplot", "density", "jitter", "ribbon", "pointrange", "hist", "ridge",
     "histogram", "errorbar", "polygon", "polypath", "rect", "qq", "segments", "points",
     "p", "l", "o", "b", "c", "h", "j", "s", "S", "n", "loess", "spline", "lm", "glm",
     "spineplot"
@@ -48,10 +48,11 @@ sanitize_type = function(type, x, y) {
     "ribbon" = type_ribbon(),
     "histogram" = type_histogram(),
     "spineplot" = type_spineplot(),
-    "qq" = type_qq(),
     "j" = type_jitter(),
     "jitter" = type_jitter(),
     "loess" = type_loess(),
+    "ridge" = type_ridge(),
+    "qq" = type_qq(),
     "spline" = type_spline(),
     "glm" = type_glm(),
     "lm" = type_lm(),
diff --git a/R/tinyplot.R b/R/tinyplot.R
index 444bbb6b..23e2cdc0 100644
--- a/R/tinyplot.R
+++ b/R/tinyplot.R
@@ -581,6 +581,9 @@ tinyplot.default = function(
 
   xlabs = ylabs = NULL
 
+  # type_ridge()
+  ygroup = NULL
+
   # will be overwritten by some type_data() functions and ignored by others
   ribbon.alpha = sanitize_ribbon.alpha(NULL)
 
@@ -638,7 +641,7 @@ tinyplot.default = function(
   if (!is.null(y) && is.character(y)) y = factor(y)
   if (!is.null(by) && is.character(by)) by = factor(by)
 
-  # flag if x==by (currently only used if type = "boxplot")
+  # flag if x==by (currently only used for "boxplot", "spineplot" and "ridges" types)
   x_by = identical(x, by)
 
   facet_dep = deparse1(substitute(facet))
@@ -694,7 +697,7 @@ tinyplot.default = function(
     return(do.call(tinyplot.density, args = fargs))
   }
 
-  datapoints = list(x = x, y = y, xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax)
+  datapoints = list(x = x, y = y, xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, ygroup = ygroup)
   datapoints = Filter(function(z) length(z) > 0, datapoints)
   datapoints = data.frame(datapoints)
   if (nrow(datapoints) > 0) {
@@ -782,7 +785,7 @@ tinyplot.default = function(
 
   # split data
   by_ordered = FALSE
-  by_continuous = !is.null(by) && inherits(by, c("numeric", "integer"))
+  by_continuous = !is.null(by) && inherits(datapoints$by, c("numeric", "integer"))
   if (isTRUE(by_continuous) && type %in% c("l", "b", "o", "ribbon", "polygon", "polypath", "boxplot")) {
     warning("\nContinuous legends not supported for this plot type. Reverting to discrete legend.")
     by_continuous = FALSE
@@ -1076,8 +1079,9 @@ tinyplot.default = function(
 
     ## Inner loop over the "facet" variables
     for (ii in seq_along(idata)) {
-      ix = idata[[ii]]$x
-      iy = idata[[ii]]$y
+      ix = idata[[ii]][["x"]]
+      iy = idata[[ii]][["y"]]
+      iz = idata[[ii]][["z"]]
       ixmin = idata[[ii]]$xmin
       ixmax = idata[[ii]]$xmax
       iymin = idata[[ii]]$ymin
@@ -1134,6 +1138,7 @@ tinyplot.default = function(
           iy = iy,
           iymax = iymax,
           iymin = iymin,
+          iz = iz,
           cex = cex,
           dots = dots,
           type = type,
diff --git a/R/type_ridge.R b/R/type_ridge.R
new file mode 100644
index 00000000..2e5af62d
--- /dev/null
+++ b/R/type_ridge.R
@@ -0,0 +1,405 @@
+#' Ridge plot type
+#'
+#' @description Type function for producing ridge plots (also known as joy plots),
+#' which display density distributions for multiple groups with vertical offsets.
+#' This function uses `tinyplot` scaffolding, which enables added functionality
+#' such as grouping and faceting.
+#'
+#' The line color is controlled by the `col` argument in the `tinyplot()` call.
+#' The fill color is controlled by the `bg` argument in the `tinyplot()` call.
+#'
+#'
+#' @param scale Numeric. Controls the scaling factor of each plot.
+#' Values greater than 1 means that plots overlap.
+#' @param gradient Logical or character. Should a color gradient be used
+#' to shade the area under the density? If a character specification is
+#' used, then it can either be of length 1 and specify the palette to be
+#' used with `gradient = TRUE` corresponding to `gradient = "viridis"`.
+#' If a character vector of length greater than 1 is used, then it
+#' should specifify the colors in the palette, e.g.,
+#' `gradient = hcl.colors(512)`.
+#' @param breaks Numeric. If a color gradient is used for shading, the
+#' breaks between the colors can be modified. The default is to use
+#' equidistant breaks spanning the range of the `x` variable.
+#' @param probs Numeric. Instead of specifying the same `breaks` on the
+#' x-axis for all groups, it is possible to specify group-specific quantiles
+#' at the specified `probs`. The quantiles are computed based on the density
+#' (rather than the raw original variable). Only one of `breaks` or
+#' `probs` must be specified.
+#' @param bw,kernel,... Arguments passed to \code{\link[stats]{density}}.
+#' @param raster Logical. Should the ridges and color gradient, if relevant,
+#' be drawn via a coercion to \code{\link[graphics]{rasterImage}}? Note that
+#' this will result in potential smoothness artifacts at high resolutions.
+#' Defaults to `FALSE`, in which case the ridges and color gradient will be
+#' passed in vectorised fashion to \code{\link[graphics]{polygon}}.
+#' @param col Character string denoting the outline (border) color for all
+#' of the ridge densities. Note that a singular value is expected; if multiple
+#' colors are provided then only the first will be used. This argument is mostly
+#' useful for the aesthetic effect of drawing a common outline color in
+#' combination with gradient fills. See Examples.
+#' @param alpha Numeric in the range `[0,1]` for adjusting the alpha
+#' transparency of the density fills. In most cases, will default to a value of
+#' 1, i.e. fully opaque. But for some `by` grouped plots (excepting the special
+#' cases where `by==y` or `by==x`), will default to 0.6.
+#'
+#' @examples
+#' ## default ridge plot
+#' tinyplot(Species ~ Sepal.Width, data = iris, type = "ridge")
+#'
+#' ## use the same bandwidth for all densities
+#' tinyplot(Species ~ Sepal.Width, data = iris,
+#'   type = type_ridge(bw = bw.nrd0(iris$Sepal.Width)))
+#'
+#' ## customized ridge plot without overlap of densities
+#' tinyplot(Species ~ Sepal.Width, data = iris,
+#'   type = type_ridge(scale = 1),
+#'   bg = "light blue", col = "black")
+#'
+#' ## by grouping is also supported. two special cases of interest:
+#'
+#' # 1) by == y (color by y groups)
+#' tinyplot(Species ~ Sepal.Width | Species, data = iris, type = "ridge")
+#'
+#' # 2) by == x (gradient coloring along x)
+#' tinyplot(Species ~ Sepal.Width | Sepal.Width, data = iris, type = "ridge")
+#'
+#' # aside: pass explicit `type_ridge(col = <col>)` arg to set a common border
+#' # color
+#' tinyplot(Species ~ Sepal.Width | Sepal.Width, data = iris,
+#'   type = type_ridge(col = "white"))
+#'
+#' ## gradient coloring along the x-axis can also be invoked manually without
+#' ## a legend (the following lines are all equivalent)
+#' tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(gradient = TRUE))
+#' # tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(gradient = "viridis"))
+#' # tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(gradient = hcl.colors(512)))
+#'
+#' ## highlighting only the center 50% of the density (between 25% and 75% quantile)
+#' tinyplot(Species ~ Sepal.Width, data = iris, col = "white", type = type_ridge(
+#'   gradient = hcl.colors(3, "Dark Mint")[c(2, 1, 2)], probs = c(0.25, 0.75)))
+#'
+#' ## highlighting the probability distribution by the color gradient
+#' tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(
+#'   gradient = hcl.colors(250, "Dark Mint")[c(250:1, 1:250)], probs = 0:500/500))
+#'
+#' ## with faceting and color gradient
+#' airq = transform(airquality, Late = ifelse(Day > 15, "Late", "Early"))
+#' tinyplot(Month ~ Ozone, facet = ~ Late, data = airq,
+#'   type = type_ridge(gradient = TRUE),
+#'   grid = TRUE, axes = "t", col = "white")
+#'
+#' @export
+type_ridge = function(scale = 1.5, gradient = FALSE, breaks = NULL, probs = NULL, bw = "nrd0", kernel = "gaussian", ..., raster = FALSE, col = NULL, alpha = NULL) {
+  density_args = list(bw = bw, kernel = kernel, ...)
+  data_ridge = function() {
+    fun = function(datapoints, yaxt = NULL, ...) {
+      get_density = function(k) {
+        out = do.call("density", c(list(x = k$x), density_args))
+        out = data.frame(x = out$x, ymax = out$y, ymin = 0, y = k$y[1])
+        out$ymax = out$ymax / max(out$ymax) * scale
+        out$facet = k$facet[1]
+        out$by = k$by[1]
+        return(out)
+      }
+      #  catch for special cases
+      anyby = length(unique(datapoints$by)) != 1
+      x_by = identical(datapoints$x, datapoints$by)
+      y_by = identical(datapoints$y, datapoints$by)
+      if (x_by) {
+        gradient = TRUE
+        datapoints$by = ""
+      } else if (y_by) {
+        datapoints$by = ""
+      } else if (anyby && is.null(alpha)) {
+        alpha = 0.6
+      }
+      # flag for (non-gradient) interior fill adjustment
+      fill_by = anyby || y_by
+      if (isTRUE(x_by)) fill_by = FALSE
+      # if (isTRUE(anyby) && is.null(alpha)) alpha = 0.6
+      ##
+      d = split(datapoints, list(datapoints$y, datapoints$by, datapoints$facet))
+      d = lapply(d, function(k) tryCatch(get_density(k), error = function(e) NULL))
+      d = do.call(rbind, Filter(function(x) !is.null(x), d))
+      d = split(d, d$facet)
+      offset_z = function(k) {
+        ksplit = split(k, k$y)
+        for (idx in seq_along(ksplit)) {
+          ksplit[[idx]]$ymax = ksplit[[idx]]$ymax + idx - 1
+          ksplit[[idx]]$ymin = ksplit[[idx]]$ymin + idx - 1
+        }
+        k = do.call(rbind, ksplit)
+        return(k)
+      }
+      d = do.call(rbind, lapply(d, offset_z))
+      
+      if (y_by) {
+        d$y = factor(d$y)
+        d$by = factor(d$y, levels = rev(levels(d$y)))
+      } else if (x_by) {
+        d$by = d$x
+      }
+      
+      # Manual breaks flag. Only used if gradient is on
+      manbreaks = !is.null(breaks) || !is.null(probs)
+
+      ## use color gradient?
+      xlim = range(d$x, na.rm = TRUE)
+      if (!is.null(probs)) {
+        if (!is.null(breaks)) {
+          warning("only one of 'breaks' and 'quantile' must be specified")
+          probs = NULL
+        } else {
+          if (probs[1L] > 0) probs = c(0, probs)
+          if (probs[length(probs)] < 1) probs = c(probs, 1)
+        }
+      }
+      if (!isFALSE(gradient)) {
+        dotspal = list(...)[["palette"]]
+        palette = if (!is.null(dotspal)) dotspal else gradient
+        gradient = TRUE
+        if (isTRUE(palette)) palette = "viridis"
+
+        if (length(palette) > 1L || !is.character(palette)) {
+          ## color vector already given
+          if (is.null(breaks) && is.null(probs)) {
+            breaks = seq(from = xlim[1L], to = xlim[2L], length.out = length(palette) + 1L)
+          } else {
+            npal = pmax(length(breaks), length(probs)) - 1L
+            if (length(palette) != npal) {
+              warning("length of 'palette' does not match 'breaks'/'probs'")
+              palette = rep_len(palette, npal)
+            }
+            if (isTRUE(raster)) raster = npal > 20L
+          }
+        } else {
+          ## only palette name given
+          npal = if (is.null(breaks) && is.null(probs)) 512L else pmax(length(breaks), length(probs)) - 1L
+          palette = hcl.colors(npal, palette = palette)
+          if (is.null(breaks) && is.null(probs)) breaks = seq(from = xlim[1L], to = xlim[2L], length.out = npal + 1L)
+          if (isTRUE(raster)) raster = npal > 20L
+        }
+      } else {
+        palette = NULL
+        if (!is.null(breaks) || !is.null(probs)) gradient = TRUE
+      }
+      if (!is.null(breaks)) {
+        breaks[1L] = pmin(breaks[1L], xlim[1L])
+        breaks[length(breaks)] = pmax(breaks[length(breaks)], xlim[2L])
+      }
+
+      out = list(
+        datapoints = d,
+        yaxt = "n",
+        ylim = c(min(d$ymin), max(d$ymax)),
+        type_info = list(
+          gradient = gradient,
+          palette = palette,
+          breaks = breaks,
+          probs = probs,
+          manbreaks = manbreaks,
+          yaxt = yaxt,
+          raster = raster,
+          x_by = x_by,
+          y_by = y_by,
+          fill_by = fill_by,
+          col = col,
+          alpha = alpha
+        )
+      )
+      return(out)
+    }
+    return(fun)
+  }
+
+  draw_ridge = function() {
+    fun = function(ix, iy, iz, ibg, icol, iymin, iymax, type_info, ...) {
+      d = data.frame(x = ix, y = iy, ymin = iymin, ymax = iymax)
+      dsplit = split(d, d$y)
+      if (is.null(ibg)) {
+        ibg = if (isTRUE(type_info[["fill_by"]])) seq_palette(icol, n = 2)[2] else "gray"
+      }
+      if (!is.null(type_info[["alpha"]]) && is.null(type_info[["palette"]])) {
+        ibg = adjustcolor(ibg, alpha.f = type_info[["alpha"]])
+      }
+      if (!is.null(type_info[["col"]])) icol = type_info[["col"]]
+      draw_segments = if (type_info[["raster"]]) segmented_raster else segmented_polygon
+      for (i in rev(seq_along(dsplit))) {
+        if (type_info[["gradient"]]) {
+          with(
+            dsplit[[i]],
+            draw_segments(
+              x, ymax, ymin = ymin[1L],
+              breaks = type_info[["breaks"]],
+              probs = type_info[["probs"]],
+              manbreaks = type_info[["manbreaks"]],
+              col = if (is.null(type_info[["palette"]])) ibg else type_info[["palette"]],
+              # border = if (is.null(type_info[["palette"]])) icol else "transparent",
+              alpha = alpha
+            )
+          )
+        }
+        with(dsplit[[i]], polygon(x, ymax, col = if (type_info[["gradient"]]) "transparent" else ibg, border = NA))
+        with(dsplit[[i]], lines(x, ymax, col = icol))
+      }
+      lab = if (is.factor(d$y)) levels(d$y) else unique(d$y)
+      if (isTRUE(type_info[["y_by"]])) {
+        # avoid duplicating the y-axis labs for the special y==by case
+        # val = match(lab, levels(d$y)) - 1
+        val = match(d$y[1], levels(d$y))
+        lab = lab[val]
+        val = val - 1
+      } else {
+        val = cumsum(rep(1, length(lab))) - 1
+      }
+      tinyAxis(x = d$y, side = 2, at = val, labels = lab, type = type_info[["yaxt"]])
+    }
+    return(fun)
+  }
+
+  out = list(
+    draw = draw_ridge(),
+    data = data_ridge(),
+    name = "ridge"
+  )
+  class(out) = "tinyplot_type"
+  return(out)
+}
+
+## auxiliary function for drawing shaded segmented polygon
+segmented_polygon = function(x, y, ymin = 0, breaks = range(x), probs = NULL, manbreaks = FALSE, col = "lightgray", border = "transparent", alpha = NULL) {
+
+  if (!is.null(probs)) {
+    ## map quantiles to breaks
+    if (!(missing(breaks) || is.null(breaks))) stop("only one of 'breaks' and 'probs' must be specified")
+    breaks = quantile.density(list(x = x, y = y - ymin), probs = probs)
+  }
+
+  ## sanity check
+  if (breaks[1L] > x[1L] || breaks[length(breaks)] < x[length(x)]) stop("'breaks' do no span range of 'x'")
+
+  # ## recycle color (if necessary) rather use colorRampPalette below
+  # col = rep_len(col, length(breaks) - 1L)
+  
+  # Create individual polygons
+  if (isFALSE(manbreaks)) {
+    # Special case for length(breaks)==length(x). We can take a fully vectorised
+    # shortcut
+    xx = c(rbind(x[-length(x)], x[-1], x[-1], x[-length(x)], NA))
+    yy = c(rbind(y[-length(y)], y[-1], ymin, ymin, NA))
+  } else {
+    # For other cases, we'll do a bit more work to make sure that the polygons
+    # overlap
+    bvals = do.call(c, sapply(seq_along(breaks[-1]), function(b) tail(x[x<breaks[b]], 1)))
+    bidx = match(bvals, x)
+    bidx = c(1, bidx, length(x))
+    xx = do.call(c, sapply(
+      seq_along(bidx[-1]),
+      function(b) {
+        xx = x[bidx[b]:bidx[b+1]]
+        c(xx, rev(xx), NA)
+      }
+    ))
+    yy = do.call(c, sapply(
+      seq_along(bidx[-1]),
+      function(b) {
+        yy = y[bidx[b]:bidx[b+1]]
+        c(yy, rep(ymin, length(yy)), NA)
+      }
+    ))
+    # Catch for missing lower breaks if individual density doesn't span the full
+    # range of x (and discrete color fills are supplied)
+    # Aside: We only need to fix the lower missing breaks, since missing top
+    # breaks will be ignored in the final polygon call anyway
+    lwrmissings = breaks < x[bidx][1]
+    if (any(lwrmissings[-1])) {
+      lwrmissings = breaks[lwrmissings] 
+      xxtra = c(rbind(lwrmissings[-length(lwrmissings)], lwrmissings[-1], lwrmissings[-1], lwrmissings[-length(lwrmissings)], NA))
+      yytra = c(rbind(rep(ymin, length(lwrmissings)-1), ymin, ymin, ymin, NA))
+      xx = c(xxtra, xx)
+      yy = c(yytra, yy)
+    }
+  }
+  
+  # Drop trailing NAs
+  xx = xx[1:(length(xx)-1)]
+  yy = yy[1:(length(yy)-1)]
+  
+  if (!is.null(alpha)) col = adjustcolor(col, alpha.f = alpha)
+  
+  # Color ramp for cases where the breaks don't match 
+  if (isFALSE(length(col)==1)) {
+    col = rev(col) ## uncomment to make extreme cols dark
+    if (isTRUE(manbreaks)) {
+      if (!is.null(breaks) && length(breaks)-1 != length(col)) {
+        xrange = range(xx, na.rm = TRUE)
+        idx = which(breaks >= xrange[1] & breaks < xrange[2])
+        idx = c(idx, length(idx)+1)
+        col = col[idx]
+        col = colorRampPalette(col, alpha = TRUE)(length(x)) # support alpha?
+      }
+    } else if (isFALSE(manbreaks) || length(col) > length(x) || length(x) %% length(col) != 0) {
+      xrange = range(xx, na.rm = TRUE)
+      idx = which(breaks >= xrange[1] & breaks < xrange[2])
+      idx = c(idx, length(idx)+1)
+      col = col[idx]
+      col = colorRampPalette(col, alpha = TRUE)(length(x)) # support alpha?
+    }
+  }
+  
+  ## draw all polygons
+  polygon(xx, yy, col = col, border = border)
+}
+
+#' @importFrom graphics rasterImage
+#' @importFrom grDevices as.raster
+segmented_raster = function(x, y, ymin = 0, breaks = range(x), probs = NULL, manbreaks = FALSE, col = "lightgray", border = "transparent", alpha = NULL) {
+  ## set up raster matrix on x-grid and 500 y-pixels 
+  n = length(x) - 1L
+  m = 500L ## FIXME: hard-coded?
+  r = matrix(1:n, ncol = n, nrow = m, byrow = TRUE)
+
+  ## map quantiles to breaks
+  if (!is.null(probs)) {
+    if (!(missing(breaks) || is.null(breaks))) stop("only one of 'breaks' and 'probs' must be specified")
+    breaks = quantile.density(list(x = x, y = y - ymin), probs = probs)
+  }
+
+  if (!is.null(alpha)) col = adjustcolor(col, alpha.f = alpha)
+  ## map colors to intervals and fill colors by column
+  col = col[cut(x, breaks = breaks, include.lowest = TRUE)]
+  r[] = col[r]
+
+  ## clip raster pixels above density line
+  ymax = max(y)
+  ix = cbind(as.vector(row(r)), as.vector(col(r)))
+  ix = ix[seq(from = ymax, to = ymin, length.out = m)[row(r)] > y[col(r)], , drop = FALSE]
+  r[ix] = NA
+
+  ## plot density and add raster gradient
+  rasterImage(as.raster(r), min(x), ymin, max(x), ymax, interpolate = length(breaks) >= 20L) ## FIXME: improve quality for "few" breaks?
+}
+
+## auxiliary function for determining quantiles based on density function
+#' @importFrom stats median
+quantile.density = function(x, probs = seq(0, 1, 0.25), ...) {
+  ## sanity check for probabilities
+  if (any(probs < 0 | probs > 1)) stop("'probs' outside [0,1]")
+
+  ## probability density function, extrapolated to zero, use midpoints
+  n = length(x$x)
+  pdf = x$y
+  pdf = c(0, pdf, 0)
+
+  ## x variable, also extrapolated, use midpoints
+  x = x$x
+  delta = median(diff(x))
+  x = c(x[1L] - delta, x, x[n] + delta)
+
+  ## numerical integration of density
+  cdf = c(0, cumsum(diff(x) * (pdf[-1L] + pdf[-(n + 2L)])/2))
+  cdf = cdf/cdf[n + 2L]
+
+  ## approximate quantiles
+  approx(cdf, x, xout = probs, rule = 2)$y  
+}
diff --git a/altdoc/quarto_website.yml b/altdoc/quarto_website.yml
index 37eb4d8c..bc04cb4e 100644
--- a/altdoc/quarto_website.yml
+++ b/altdoc/quarto_website.yml
@@ -67,6 +67,8 @@ website:
               file: man/type_jitter.qmd
             - text: type_qq
               file: man/type_qq.qmd
+            - text: type_ridge
+              file: man/type_ridge.qmd
             - text: type_spineplot
               file: man/type_spineplot.qmd
           - section: Models
diff --git a/inst/tinytest/_tinysnapshot/ridge_01.svg b/inst/tinytest/_tinysnapshot/ridge_01.svg
new file mode 100644
index 00000000..0ac90279
--- /dev/null
+++ b/inst/tinytest/_tinysnapshot/ridge_01.svg
@@ -0,0 +1,65 @@
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398.78,402.35 399.47,402.62 400.17,402.88 400.86,403.15 401.55,403.41 402.25,403.67 402.94,403.93 403.63,404.20 404.32,404.46 405.02,404.72 405.71,404.98 406.40,405.24 407.10,405.50 407.79,405.76 408.48,406.03 409.18,406.29 409.87,406.56 410.56,406.82 411.26,407.09 411.95,407.35 412.64,407.62 413.34,407.89 414.03,408.15 414.72,408.42 415.42,408.68 416.11,408.95 416.80,409.21 417.50,409.47 418.19,409.74 418.88,410.00 419.58,410.25 420.27,410.51 420.96,410.76 421.66,411.01 422.35,411.25 423.04,411.49 423.74,411.73 424.43,411.96 425.12,412.19 425.82,412.41 426.51,412.63 427.20,412.84 427.90,413.04 428.59,413.24 429.28,413.44 429.98,413.62 430.67,413.81 431.36,413.98 432.06,414.15 432.75,414.31 433.44,414.47 434.14,414.62 434.83,414.76 435.52,414.89 436.22,415.02 436.91,415.15 437.60,415.26 438.30,415.37 438.99,415.48 439.68,415.58 440.37,415.67 441.07,415.76 441.76,415.84 442.45,415.92 443.15,415.99 443.84,416.06 444.53,416.12 445.23,416.18 445.92,416.23 446.61,416.28 447.31,416.33 448.00,416.37 448.69,416.41 449.39,416.45 450.08,416.48 450.77,416.51 451.47,416.54 452.16,416.57 452.85,416.59 453.55,416.61 454.24,416.63 454.93,416.65 455.63,416.67 456.32,416.68 457.01,416.69 457.71,416.70 458.40,416.72 ' style='stroke-width: 0.75;' />
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+<g clip-path='url(#cpMC4wMHw1MDQuMDB8MC4wMHw1MDQuMDA=)'>
+<line x1='59.04' y1='416.80' x2='59.04' y2='220.23' style='stroke-width: 0.75;' />
+<line x1='59.04' y1='416.80' x2='51.84' y2='416.80' style='stroke-width: 0.75;' />
+<line x1='59.04' y1='318.51' x2='51.84' y2='318.51' style='stroke-width: 0.75;' />
+<line x1='59.04' y1='220.23' x2='51.84' y2='220.23' style='stroke-width: 0.75;' />
+<text transform='translate(41.76,416.80) rotate(-90)' text-anchor='middle' style='font-size: 12.00px; font-family: "Liberation Sans";' textLength='35.37px' lengthAdjust='spacingAndGlyphs'>setosa</text>
+<text transform='translate(41.76,318.51) rotate(-90)' text-anchor='middle' style='font-size: 12.00px; font-family: "Liberation Sans";' textLength='51.36px' lengthAdjust='spacingAndGlyphs'>versicolor</text>
+<text transform='translate(41.76,220.23) rotate(-90)' text-anchor='middle' style='font-size: 12.00px; font-family: "Liberation Sans";' textLength='44.02px' lengthAdjust='spacingAndGlyphs'>virginica</text>
+</g>
+</svg>
diff --git a/inst/tinytest/test-ridge.R b/inst/tinytest/test-ridge.R
new file mode 100644
index 00000000..4e77f97c
--- /dev/null
+++ b/inst/tinytest/test-ridge.R
@@ -0,0 +1,66 @@
+source("helpers.R")
+using("tinysnapshot")
+
+f = function() {
+  tinyplot(Species ~ Sepal.Width, data = iris, type = "ridge", col = "white")
+}
+expect_snapshot_plot(f, label = "ridge_01")
+
+f = function() {
+  tinyplot(Species ~ Sepal.Width, data = iris,
+    type = type_ridge(scale = 1),
+    bg = "light blue", col = "black")
+}
+expect_snapshot_plot(f, label = "ridge_02")
+
+f = function() {
+  tinyplot(am ~ mpg | factor(cyl), data = mtcars, type = "ridge")
+}
+expect_snapshot_plot(f, label = "ridge_by")
+
+# special by cases
+
+## by == y
+f = function() {
+  tinyplot(Species ~ Sepal.Width | Species, data = iris, type = "ridge")
+}
+expect_snapshot_plot(f, label = "ridge_by_y")
+
+## by == x
+f = function() {
+  tinyplot(Species ~ Sepal.Width | Sepal.Width, data = iris,
+           type = type_ridge(col = "white"), palette = "plasma")
+}
+expect_snapshot_plot(f, label = "ridge_by_x")
+
+# "manual" gradients
+
+f = function() {
+  tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(gradient = TRUE))
+}
+expect_snapshot_plot(f, label = "ridge_gradient")
+
+f = function() {
+  tinyplot(
+    Species ~ Sepal.Width, data = iris,
+    type = type_ridge(gradient = TRUE, breaks = seq(2, 4.5, by = 0.5))
+  )
+}
+expect_snapshot_plot(f, label = "ridge_gradient_discrete")
+
+f = function() {
+  tinyplot(
+    Species ~ Sepal.Width, data = iris,
+    type = type_ridge(
+      gradient = hcl.colors(250, "Dark Mint")[c(250:1, 1:250)],
+      probs = 0:500/500
+    )
+  )
+}
+expect_snapshot_plot(f, label = "ridge_gradient_probs")
+
+tinyplot(
+  am ~ mpg, facet = ~vs, data = mtcars, type = type_ridge(gradient = "agsunset"),
+  col = "white"
+)
+expect_snapshot_plot(f, label = "ridge_gradient_facet")
diff --git a/man/tinyplot_add.Rd b/man/tinyplot_add.Rd
index cadced23..916e7159 100644
--- a/man/tinyplot_add.Rd
+++ b/man/tinyplot_add.Rd
@@ -42,18 +42,18 @@ arguments (\code{x}, \code{y}, etc.) are attached to your global R environment.)
 library(tinyplot)
 
 tinyplot(Sepal.Width ~ Sepal.Length | Species,
-         facet = ~Species,
-         data = iris)
+  facet = ~Species,
+  data = iris)
 
-tinyplot_add(type = "lm")   ## or : plt_add(type = "lm")
+tinyplot_add(type = "lm") ## or : plt_add(type = "lm")
 
 ## Note: the previous function is equivalent to (but much more convenient
 ## than) re-writing the full call with the new type and `add=TRUE`:
 
 # tinyplot(Sepal.Width ~ Sepal.Length | Species,
 #          facet = ~Species,
-#          data = iris, 
-#          type = "lm", 
+#          data = iris,
+#          type = "lm",
 #          add = TRUE)
 
 }
diff --git a/man/type_ridge.Rd b/man/type_ridge.Rd
new file mode 100644
index 00000000..67163fc7
--- /dev/null
+++ b/man/type_ridge.Rd
@@ -0,0 +1,116 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/type_ridge.R
+\name{type_ridge}
+\alias{type_ridge}
+\title{Ridge plot type}
+\usage{
+type_ridge(
+  scale = 1.5,
+  gradient = FALSE,
+  breaks = NULL,
+  probs = NULL,
+  bw = "nrd0",
+  kernel = "gaussian",
+  ...,
+  raster = FALSE,
+  col = NULL,
+  alpha = NULL
+)
+}
+\arguments{
+\item{scale}{Numeric. Controls the scaling factor of each plot.
+Values greater than 1 means that plots overlap.}
+
+\item{gradient}{Logical or character. Should a color gradient be used
+to shade the area under the density? If a character specification is
+used, then it can either be of length 1 and specify the palette to be
+used with \code{gradient = TRUE} corresponding to \code{gradient = "viridis"}.
+If a character vector of length greater than 1 is used, then it
+should specifify the colors in the palette, e.g.,
+\code{gradient = hcl.colors(512)}.}
+
+\item{breaks}{Numeric. If a color gradient is used for shading, the
+breaks between the colors can be modified. The default is to use
+equidistant breaks spanning the range of the \code{x} variable.}
+
+\item{probs}{Numeric. Instead of specifying the same \code{breaks} on the
+x-axis for all groups, it is possible to specify group-specific quantiles
+at the specified \code{probs}. The quantiles are computed based on the density
+(rather than the raw original variable). Only one of \code{breaks} or
+\code{probs} must be specified.}
+
+\item{bw, kernel, ...}{Arguments passed to \code{\link[stats]{density}}.}
+
+\item{raster}{Logical. Should the ridges and color gradient, if relevant,
+be drawn via a coercion to \code{\link[graphics]{rasterImage}}? Note that
+this will result in potential smoothness artifacts at high resolutions.
+Defaults to \code{FALSE}, in which case the ridges and color gradient will be
+passed in vectorised fashion to \code{\link[graphics]{polygon}}.}
+
+\item{col}{Character string denoting the outline (border) color for all
+of the ridge densities. Note that a singular value is expected; if multiple
+colors are provided then only the first will be used. This argument is mostly
+useful for the aesthetic effect of drawing a common outline color in
+combination with gradient fills. See Examples.}
+
+\item{alpha}{Numeric in the range \verb{[0,1]} for adjusting the alpha
+transparency of the density fills. In most cases, will default to a value of
+1, i.e. fully opaque. But for some \code{by} grouped plots (excepting the special
+cases where \code{by==y} or \code{by==x}), will default to 0.6.}
+}
+\description{
+Type function for producing ridge plots (also known as joy plots),
+which display density distributions for multiple groups with vertical offsets.
+This function uses \code{tinyplot} scaffolding, which enables added functionality
+such as grouping and faceting.
+
+The line color is controlled by the \code{col} argument in the \code{tinyplot()} call.
+The fill color is controlled by the \code{bg} argument in the \code{tinyplot()} call.
+}
+\examples{
+## default ridge plot
+tinyplot(Species ~ Sepal.Width, data = iris, type = "ridge")
+
+## use the same bandwidth for all densities
+tinyplot(Species ~ Sepal.Width, data = iris,
+  type = type_ridge(bw = bw.nrd0(iris$Sepal.Width)))
+
+## customized ridge plot without overlap of densities
+tinyplot(Species ~ Sepal.Width, data = iris,
+  type = type_ridge(scale = 1),
+  bg = "light blue", col = "black")
+
+## by grouping is also supported. two special cases of interest:
+
+# 1) by == y (color by y groups)
+tinyplot(Species ~ Sepal.Width | Species, data = iris, type = "ridge")
+
+# 2) by == x (gradient coloring along x)
+tinyplot(Species ~ Sepal.Width | Sepal.Width, data = iris, type = "ridge")
+
+# aside: pass explicit `type_ridge(col = <col>)` arg to set a common border
+# color
+tinyplot(Species ~ Sepal.Width | Sepal.Width, data = iris,
+  type = type_ridge(col = "white"))
+
+## gradient coloring along the x-axis can also be invoked manually without
+## a legend (the following lines are all equivalent)
+tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(gradient = TRUE))
+# tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(gradient = "viridis"))
+# tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(gradient = hcl.colors(512)))
+
+## highlighting only the center 50\% of the density (between 25\% and 75\% quantile)
+tinyplot(Species ~ Sepal.Width, data = iris, col = "white", type = type_ridge(
+  gradient = hcl.colors(3, "Dark Mint")[c(2, 1, 2)], probs = c(0.25, 0.75)))
+
+## highlighting the probability distribution by the color gradient
+tinyplot(Species ~ Sepal.Width, data = iris, type = type_ridge(
+  gradient = hcl.colors(250, "Dark Mint")[c(250:1, 1:250)], probs = 0:500/500))
+
+## with faceting and color gradient
+airq = transform(airquality, Late = ifelse(Day > 15, "Late", "Early"))
+tinyplot(Month ~ Ozone, facet = ~ Late, data = airq,
+  type = type_ridge(gradient = TRUE),
+  grid = TRUE, axes = "t", col = "white")
+
+}
