A dendrogram (or tree diagram) is a network structure. It is constituted of a root node that gives birth to several nodes connected by edges or branches. The last nodes of the hierarchy are called leaves. Many options are available to build one with R. This sections aims to lead you toward the best strategy for your data.

Two types of dendrogram

Dendrograms can be built from:

- Hierarchical dataset: think about a CEO managing team leads managing employees and so on.
- Clustering result: clustering divides a set of individuals in group according to their similarity. Its result can be visualized as a tree.

Dendrogram from

`hierarchical`

data.
The `ggraph`

package is the best option to build a
dendrogram from hierarchical data with R. It is based on the grammar
of graphic and thus follows the same logic that `ggplot2`

.

The `collapsibletree`

package is an htmlwidget: it
automatically builds collapsible interactive tree diagram. On the
chart below, __click a node__ to reveal the next branch, and zoom
in/out if necessary.

Dendrogram from

`clustering`

result.
Hierarchical clustering is a common task in data science and can be
performed with the `hclust()`

function in R. The following
examples will guide you through your process, showing how to prepare
the data, how to run the clustering and how to build an appropriate
chart to visualize its result.

More customization with

`dendextend`

.
The `dendextend`

package allows to go one step further in
term of dendrogram customization. Here is a set of examples showing
the main possibilities, like adding color bar on the bottom, drawing 2
trees face to face and more.