<｜begin▁of▁sentence｜>### Instruction:
As a performance artist, you're collaborating with a group of fellow artists to create an interactive art installation exploring the concept of interconnectedness. You've collected data from various collaborations within the condensed matter physics community in 2005, represented as a graph stored in a GML file named "cond-mat-2005.gml". To infuse this data into your project, you plan to use the Louvain algorithm available in the Community Detection Library (cdlib) to identify distinct communities within the network of collaborations. Once you've detected these communities, you aim to save the community structure to a CSV file for further analysis. Additionally, you want to ensure that you can easily access and manipulate this data, so you intend to read the CSV file back into a NodeClustering object, maintaining its original structure and integrity.
### Response:
import networkx as nx
from cdlib import algorithms, readwrite

# Load an example graph
G = nx.read_gml('cond-mat-2005.gml')

# Detect communities using the Louvain algorithm
communities = algorithms.louvain(G)

# Write the detected communities to a CSV file
readwrite.write_community_csv(communities, 'communities.csv', delimiter=',')

# Read the community structure from the CSV file
communities_from_csv = readwrite.read_community_csv('communities.csv', delimiter=',', nodetype=str)
<|EOT|>
