<｜begin▁of▁sentence｜>### Instruction:
If you are managing an electricity distribution company and are interested in analyzing the community structure within your power grid network, you can use the Louvain method in the cdlib library to detect communities within the network. Once the communities are identified, you can calculate the Newman-Girvan modularity to assess the strength of the community structure. To do this, you can read the power grid graph from a GML file named 'power.gml' and then utilize the appropriate functions within the cdlib library to perform community detection and compute the Newman-Girvan modularity score.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Read the power grid graph
G = nx.read_gml('power.gml')

# Apply the Louvain community detection algorithm to the power grid graph
communities = algorithms.louvain(G)

# Compute the Newman-Girvan modularity for the detected communities
modularity = evaluation.newman_girvan_modularity(G, communities)

# Print the modularity result
print('Newman-Girvan Modularity:', modularity.score)
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