<｜begin▁of▁sentence｜>### Instruction:
Imagine we're riffing through a complex piece with multiple musical sections, akin to a graph with various disconnected subgraphs. Just like we'd focus on the main groove, the heart of the tune, we want to give our attention to the largest subgraph within this disconnected chart. How do we go about setting the stage to solo over this primary section using the vibes of graspologic? We're talking about getting that main piece isolated so we can lay down a sweet analysis on the biggest connected component. Can you dig?
### Response:
import networkx as nx
from graspologic.utils import largest_connected_component

# Create a disconnected graph
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (2, 0), (3, 4)])

# Only retain the largest connected component
largest_cc_graph = largest_connected_component(G)

# Print the nodes of the largest connected component
print(largest_cc_graph.nodes())

# If we want to get the indices of nodes in the largest component from the original graph
largest_cc_graph, node_indices = largest_connected_component(G, return_inds=True)
print(node_indices)
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