diff --git a/examples/drawing/plot_clusters.py b/examples/drawing/plot_clusters.py
new file mode 100644
index 00000000000..d768a3bc7c9
--- /dev/null
+++ b/examples/drawing/plot_clusters.py
@@ -0,0 +1,36 @@
+"""
+==============
+Cluster Layout
+==============
+
+This example illustrates how to combine multiple layouts to visualize node
+clusters.
+
+The approach used here can be generalized to visualize hierarchical clustering
+e.g. clusters-of-clusters of nodes by combining layouts with varying scale
+factors.
+"""
+import networkx as nx
+import matplotlib.pyplot as plt
+
+G = nx.davis_southern_women_graph()  # Example graph
+communities = nx.community.greedy_modularity_communities(G)
+
+# Compute positions for the node clusters as if they were themselves nodes in a
+# supergraph using a larger scale factor
+supergraph = nx.cycle_graph(len(communities))
+superpos = nx.spring_layout(G, scale=50, seed=429)
+
+# Use the "supernode" positions as the center of each node cluster
+centers = list(superpos.values())
+pos = {}
+for center, comm in zip(centers, communities):
+    pos.update(nx.spring_layout(nx.subgraph(G, comm), center=center, seed=1430))
+
+# Nodes colored by cluster
+for nodes, clr in zip(communities, ("tab:blue", "tab:orange", "tab:green")):
+    nx.draw_networkx_nodes(G, pos=pos, nodelist=nodes, node_color=clr, node_size=100)
+nx.draw_networkx_edges(G, pos=pos)
+
+plt.tight_layout()
+plt.show()