<｜begin▁of▁sentence｜>### Instruction:
As a woodworker, you may find yourself involved in a project where you need to optimize the use of different types of wood to create a stylish and functional piece of furniture. Using igraph library can you create a new design for a piece of furniture where each component's material (as determined by an edge betweenness community detection method) is combined into an optimal set of materials, ensuring efficient use and balance of wood types?
### Response:
from igraph import Graph

# Create a graph with 10 vertices and some edges
edges = [(0, 1), (0, 2), (1, 2), (3, 4), (4, 5), (3, 5)]
g = Graph(edges=edges)

# Assume you have a vertex clustering, for example by some community detection method
vertex_clustering = g.community_edge_betweenness()
clusters = vertex_clustering.as_clustering()

# Use the `cluster_graph` method to create a new graph where each cluster is a vertex
g_clustered = clusters.cluster_graph()

# Print the summary of the clustered graph
print(g_clustered.summary())
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