<｜begin▁of▁sentence｜>### Instruction:
Imagine we're walking through the rich ecosystem of a graph, where each node represents a species and its connections symbolize the intricate interactions within our networked environment. Now, as naturalists, we meticulously observe the frequency of interactions per species—akin to their degree in the graph with observations recorded as such: [1, 2, 2, 3, 3, 3, 4, 4, 5].

Our quest now delves into understanding not just the isolated interactions, but the broader, cumulative picture of our ecological network. How do we, with the assistance of NetworkX's tools, unveil the normalized cumulative tale of these interactions? This will provide us with a richer, more comprehensive view of our ecological graph's interconnected complexity.
### Response:
import networkx as nx
from networkx.utils import cumulative_distribution

# Given a discrete distribution (for instance, degree distribution of a graph)
distribution = [1, 2, 2, 3, 3, 3, 4, 4, 5]

# Compute the normalized cumulative distribution
cum_dist = cumulative_distribution(distribution)
print('Normalized Cumulative Distribution:', cum_dist)
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