<｜begin▁of▁sentence｜>### Instruction:
Imagine you're looking at a bustling barbershop with a trio of seating areas. Each area represents a cluster of customers waiting to get spruced up. The first area has three chatty friends, the second, a quiet pair reading magazines, and the last one is bustling with four folks exchanging stories. 

Now, picture if you will, arranging these customers into a nice, neat lineup. You’re going to set them up so that each group is on its own straight path, like lanes in a hair-cutting relay race. The lineup needs to be straight as a comb, with a vertical orientation that would make a level bubble proud. Each person should be spaced just so, preserving that personal space – we're talking a scale that feels as comfortable as a fresh haircut.

And here’s the kicker: you want to center this human pattern right in the heart of the barbershop, a bullseye that lands at the coordinates of zero gossip, zero wait – the sweet spot of the shop, if you will.

Now let's shift this vision from a barber's eye to a bird's eye view. Translate this lineup into a graph, like one of those fancy diagrams on the hair products we never really read. This graph of yours is a complete multipartite one, fashioned with nodes in place of customers, stretched in layers and as aligned as the blades of your shears. How would you comb this graph to fit the scenario I've just trimmed up for you?
### Response:
import networkx as nx
import matplotlib.pyplot as plt

# Create a complete multipartite graph
G = nx.complete_multipartite_graph(3, 2, 4)

# Use the multipartite layout to position nodes
pos = nx.multipartite_layout(G, subset_key='subset', align='vertical', scale=1, center=(0, 0))

# Draw the graph using the computed positions
nx.draw(G, pos, with_labels=True)
plt.show()
<|EOT|>
