<｜begin▁of▁sentence｜>### Instruction:
In the context of a school counseling scenario, let's imagine that as part of a collaborative project in a computer science class, students are working on an assignment that involves different structures representing student groups. Two groups (Group A and Group B) have charted out relationships within their team members as a network. Group A's network has connections between members 1 & 2, 2 & 3, and 1 & 3. Group B, on the other hand, depicts their relationships between members 10 & 20, 20 & 30, and 10 & 30.

I'd like to propose an intriguing challenge for our bright students. Let's see if they can use their NetworkX toolset to discover all the distinct, but essentially identical, ways the structure of Group A's network can be matched with that of Group B's, noting that these structures, although labeled differently, might actually hold the same pattern of connections. This exploration of network patterns could provide valuable insights for our social dynamics study within the student body.

Just as we identify the similarities and differences among students to better support their development, finding these mappings can foster further understanding of group dynamics. Would you be able to help them dive into this captivating exercise while preserving the educational essence of the task?
### Response:
import networkx as nx

# Create two graphs
G1 = nx.Graph()
G1.add_edges_from([(1, 2), (2, 3), (1, 3)])

G2 = nx.Graph()
G2.add_edges_from([(10, 20), (20, 30), (10, 30)])

# Yield all possible isomorphic mappings between G1 and G2
for mapping in nx.algorithms.isomorphism.vf2pp_all_isomorphisms(G1, G2):
    print(mapping)
<|EOT|>
