<｜begin▁of▁sentence｜>### Instruction:
As a digital artist crafting a visually intricate piece for my latest digital installation, I’ve chosen to use the Frucht Graph as an inspirational blueprint due to its uniqueness of having no nontrivial symmetries. It’s also the smallest cubic graph to possess this characteristic, which fits the theme of my piece—celebrating singularities within structured complexities. To more accurately depict this graph in my work, I require a method to generate the Frucht Graph in a digital environment. Specifically, I'm interested in previewing its vertices, edges, and examining its inherent properties through a computational lens. How might I proceed with this in a tool like NetworkX, so that I could potentially translate the structure and information to my digital canvas?
### Response:
import networkx as nx

# Generate the Frucht graph
G = nx.frucht_graph()

# Print the edges of the Frucht graph
print('Edges of the Frucht Graph:', G.edges())

# Print the number of nodes and edges in the Frucht graph
print('The Frucht Graph has', G.number_of_nodes(), 'nodes and', G.number_of_edges(), 'edges.')
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