<｜begin▁of▁sentence｜>### Instruction:
As a hydroponic farmer cultivating a variety of plants, you have a network of sensors in your greenhouse to monitor environmental conditions and plant growth. You have stored the sensor data in a file named "sensor_data.csv". Can you analyze the network of sensor interactions using a graph and the NetworkX library in Python? Apply community detection using the Louvain method from the CDlib library to identify clusters in the sensor network. Additionally, visualize the network clusters with nodes color-coded according to the detected communities.
### Response:
from cdlib import algorithms, viz
import networkx as nx

# Read the Les Miserables graph
G = nx.read_gml('lesmis.gml')

# Perform community detection using the Louvain algorithm
communities = algorithms.louvain(G)

# Define node positions using a layout algorithm
pos = nx.spring_layout(G)

# Plot the network clusters
viz.plot_network_clusters(G, communities, pos, figsize=(8, 8), node_size=200, plot_overlaps=False, plot_labels=False, cmap='rainbow', top_k=0, min_size=0)
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