<｜begin▁of▁sentence｜>### Instruction:
As a sleep specialist, you are looking to understand how to convert information from one format to another in a practical clinical scenario. If you had a network of patients with sleep disorders represented as a simple triangle using the NetworkX library in Python, you might want to convert this information into the iGraph format to gain additional insights.

Using the `Graph.from_networkx` method in the iGraph library, you can seamlessly convert the network representation and then visualize the vertices and edges to gain a better understanding of the connections and relationships among the patients. This can provide valuable insight into how specific sleep disorders may be interconnected and how to effectively treat them to improve overall well-being.
### Response:
import networkx as nx
import igraph as ig

# Create a NetworkX graph
nx_graph = nx.Graph()
nx_graph.add_edge('A', 'B')
nx_graph.add_edge('B', 'C')
nx_graph.add_edge('C', 'A')

# Convert NetworkX graph to an igraph graph
ig_graph = ig.Graph.from_networkx(nx_graph)

# Print the igraph vertices and edges
print('Vertices:', ig_graph.vs['name'])
print('Edges:', ig_graph.get_edgelist())
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