<｜begin▁of▁sentence｜>### Instruction:
Imagine we're tasked with analyzing the informal communication network within a small investment firm of 10 analysts. We want to evaluate the potential for information flow and collaborative opportunities, recognizing that interpersonal relationships are inherently random. To model this scenario, we postulate that there's a 50% probability of any given pair of analysts sharing insights and financial strategies with each other. How might we construct and depict a graphical representation of this stochastic professional network to better assess the structure and implications for information dissemination within the firm?
### Response:
import networkx as nx
import matplotlib.pyplot as plt

# Use the erdos_renyi_graph API to generate a random graph
# n is the number of nodes, p is the probability of edge creation
G = nx.erdos_renyi_graph(n=10, p=0.5, seed=42)

# Draw the graph
nx.draw(G, with_labels=True)
plt.show()
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