<｜begin▁of▁sentence｜>### Instruction:
As a financial advisor, imagine helping a client with an investment portfolio consisting of 100 different assets. Using advanced tools like the DegreeBasedSampler in the networkx Python library, you want to identify a subset of 17 assets based on their interconnections within the network. Additionally, you aim to compute the degree centrality for each of the selected assets to gain insights into their potential influence within the portfolio. This analysis will aid in optimizing the portfolio's performance and aligning it with the client's financial objectives.
### Response:
import networkx as nx
from littleballoffur import DegreeBasedSampler

G = nx.gnp_random_graph(n=100, p=0.08)

sampler = DegreeBasedSampler(17)

sampler_G = sampler.sample(G)

result = nx.degree_centrality(sampler_G)

print(result)
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