<｜begin▁of▁sentence｜>### Instruction:
As a business consultant, a client has a network of 200 suppliers and wants to evaluate the efficiency of their connections. I have suggested using the networkx library to model the relationships. By simulating a CommonNeighborAwareRandomWalkSampler, we can extract a subgraph of 20 suppliers and calculate the average clustering coefficient to measure the grouping tendency and potential for collaboration within the sampled network.
### Response:
import networkx as nx
from littleballoffur import CommonNeighborAwareRandomWalkSampler

G = nx.gnp_random_graph(n=200, p=0.25)

sampler = CommonNeighborAwareRandomWalkSampler(20)

sampler_G = sampler.sample(G, start_node=0)

result = nx.average_clustering(sampler_G)

print(result)
<|EOT|>
