<｜begin▁of▁sentence｜>### Instruction:
As a networkx expert, I can help you apply the CommunityStructureExpansionSampler to sample a subgraph from an erdos_renyi_graph and then calculate the average clustering coefficient for the sampled graph. This can be useful in analyzing the structure and connectivity of complex networks.

Let's consider a practical scenario where a construction manager is overseeing the development of a smart city infrastructure. The smart city includes a complex network of sensors, communication nodes, and data centers. To ensure efficient coordination and resource allocation, the construction manager needs to analyze the connectivity patterns within the network.

By leveraging networkx and the CommunityStructureExpansionSampler, the construction manager can sample a subgraph from the overall network and calculate the average clustering coefficient to better understand the local connectivity patterns. This analysis can help in optimizing the placement of resources and enhancing the overall efficiency of the smart city infrastructure.
### Response:
import networkx as nx
from littleballoffur import CommunityStructureExpansionSampler

G = nx.gnp_random_graph(n=700, p=0.2)

sampler = CommunityStructureExpansionSampler()
sampled_G = sampler.sample(G, start_node=0)

result = nx.average_clustering(sampled_G)
print(result)
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