<｜begin▁of▁sentence｜>### Instruction:
In a study looking at connectivity between sections of a large, complex network, each section is represented as a graph. To analyze the overall connectivity, the researcher wants to find the largest connected component that represents how these sections are interconnected. The goal is to take the union of multiple graphs representing the network's sections and extract the largest connected component from the combined graph.
### Response:
import networkx as nx
from graspologic.utils import multigraph_lcc_union

# Step 1: Construct multiple NetworkX graphs
G1 = nx.fast_gnp_random_graph(10, 0.5, seed=42)
G2 = nx.fast_gnp_random_graph(10, 0.3, seed=42)
G3 = nx.fast_gnp_random_graph(10, 0.1, seed=42)

# Create a list of these graphs
graph_list = [G1, G2, G3]

# Step 2: Use multigraph_lcc_union to find the union and the LCC of the graphs
# Since the graphs are NetworkX graphs, the return_inds parameter is ignored
unified_lcc_graph = multigraph_lcc_union(graphs=graph_list)

# Print information about the unified LCC graph
print('Number of nodes in the unified LCC graph:', unified_lcc_graph.number_of_nodes())
print('Number of edges in the unified LCC graph:', unified_lcc_graph.number_of_edges())
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