<｜begin▁of▁sentence｜>### Instruction:
As a librarian diligently cataloging the vast intellectual resources at our disposal, imagine we've encountered a theoretical conundrum akin to an intriguing novel nestled in the mathematics section. We have a cycle graph represented within our collection – a structured circular arrangement of information that loops around, connecting five pivotal points akin to chapters in a book.

Now, for this particular graph, we wish to determine the chromatic polynomial – a mathematical expression that beautifully enumerates all the distinct ways in which the graph's nodes can be colored, following certain rules of adjacency akin to the thematic consistency required between successive chapters.

How might one adeptly apply NetworkX, a tool as indispensable to network analysis as the Dewey Decimal System is to library science, to achieve this computation of the chromatic polynomial for our cyclic graph, ensuring the hues chosen for one node do not mirror those of its immediate neighbor, thus maintaining the diversity of our palette?
### Response:
import networkx as nx

G = nx.cycle_graph(5)
chromatic_poly = nx.chromatic_polynomial(G)
print(chromatic_poly)
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