<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working on a user interface for a social networking platform, specifically focusing on visualizing connections between users. In this interface, user accounts are represented as nodes, where each node has a numeric identifier, and friendships are represented as undirected edges connecting these nodes.

You are tasked with designing an experience that, when a user selects their account — in this case, represented by the node with the identifier '0' — the interface will highlight or display the entire cluster of connected users within their particular network.

The data you have for this scenario consists of a series of relationships, represented by pairs of connected user identifiers. The relevant user connections are as follows: a link between the users labeled '0' and '1', '1' and '2', '5' and '6', and '3' and '4'.

How would you rephrase the design challenge to your team in order to determine the set of user account identifiers that are present in the interconnected network containing the user account represented by the node with the identifier '0'?
### Response:
import networkx as nx

# Create an undirected graph
G = nx.Graph()

# Add nodes and edges to the graph
G.add_nodes_from([0, 1, 2, 3, 4, 5, 6])
G.add_edges_from([(0, 1), (1, 2), (5, 6), (3, 4)])

# Find the connected component that contains node 0
connected_component = nx.node_connected_component(G, 0)

# Print the connected component
print(connected_component)
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