<｜begin▁of▁sentence｜>### Instruction:
Imagine you're compiling a behind-the-scenes documentary about how different parts of a network come together to create a complex web, similar to the crew and cast members of a film. You've gathered footage of an intricate interaction represented by a series of connections, which in the world of network theory we'd call a tree with an edge set: [(0, 3), (1, 3), (2, 3), (3, 4), (4, 5)].

In your storyline, you want to highlight the underlying structure of this network in a simplified manner—akin to a list that can reveal the essence of the connectivity without the visual complexity. In technical terms, this list is known as the Prüfer sequence.

Could you envision utilizing NetworkX, a powerful tool in the video editor's software arsenal, to translate this tree's connected pattern into such a list? How would you go about acquiring the Prüfer sequence corresponding to this tree using NetworkX, adding yet another layer of depth to your network narrative?
### Response:
import networkx as nx

# Create a graph representing a tree
edges = [(0, 3), (1, 3), (2, 3), (3, 4), (4, 5)]
tree = nx.Graph(edges)

# Get the Prüfer sequence of the tree
sequence = nx.to_prufer_sequence(tree)
print('Prüfer sequence:', sequence)
<|EOT|>
