<｜begin▁of▁sentence｜>### Instruction:
In the context of overseeing the security measures within our correction facility, I've been exploring various visualization techniques to effectively map out the interconnectivity within different sectors of our infrastructure. Specifically, I'm considering a design akin to a Lollipop Graph for this exercise, where the "candy" part represents a closely-knit network, much like a cluster of cells or blocks, and the "stick" extends as a linear pathway akin to a sequence of checkpoints or gated areas.

For our scenario, let's assume the core cluster (the "candy") consists of 5 interconnected nodes representing key areas within the maximum-security zone that are all tightly monitored and connected. Extending from this, we have a controlled pathway with 4 additional checkpoints (the "stick") leading towards a lower-security region or administrative section.

How might we utilize networkx alongside matplotlib to create a visual representation of this "Lollipop" model? This visual tool could then potentially assist us in understanding the flow and management of this particular security structure within our establishment.
### Response:
import networkx as nx
# Create a Lollipop Graph with m=5 and n=4
m, n = 5, 4
G = nx.lollipop_graph(m, n)

# Draw the graph, enable labels and show it
import matplotlib.pyplot as plt
nx.draw(G, with_labels=True)
plt.show()
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