Dendrogram

Hierarchical-clustering dendrogram, drawn with ggplot2 so it shares the package theme. Accepts a data frame (the distance matrix and clustering are computed for you), a stats::dist object, or an stats::hclust object. Optionally cut the tree into k clusters, colouring the leaf labels and drawing the cut height.

Usage

dendrogram_plot(
  x,
  cols = NULL,
  distance = "euclidean",
  method = "complete",
  scale = TRUE,
  k = NULL,
  horizontal = FALSE,
  labels = NULL,
  palette = NULL,
  title = NULL
)

Arguments

x

A data frame, a dist object, or an hclust object.

cols

When x is a data frame, the numeric columns to use.

distance

Distance measure passed to stats::dist().

method

Linkage method passed to stats::hclust().

scale

Whether to scale variables before computing distances (data frame input).

k

Optional number of clusters to highlight (between 1 and the number of leaves). The cut-height line is drawn only when 2 <= k < n.

horizontal

Whether to draw the tree horizontally.

labels

Whether to print the leaf labels. NULL (the default) chooses automatically: labels are shown for small trees (up to 40 leaves) and suppressed for larger ones, where they would otherwise collapse into an unreadable smear. TRUE/FALSE force them on or off. When labels are hidden and k is set, the cluster membership is instead conveyed by a coloured strip of leaf ticks along the bottom of the tree.

palette

Colours for the k clusters; defaults to depictr_palette().

title

Plot title.

Value

A ggplot2::ggplot object.

Examples

# Cluster the survey regions by their wellbeing averages
d <- aggregate(cbind(stress, sleep_hours, life_satisfaction) ~ region,
               data = wellbeing_survey, FUN = mean)
rownames(d) <- d$region
dendrogram_plot(d[-1], k = 2)