<｜begin▁of▁sentence｜>### Instruction:
As a computational biologist, you might be interested in analyzing the network relationships within a cell signaling pathway. If you have a graph representing interactions between proteins, genes, and compounds, and these entities are categorized into different functional groups, you may want to use a function in igraph, such as assortativity_nominal, to calculate the assortativity of the graph based on these group categories. This can help you understand the level of preferential interactions within and between functional groups in the pathway.
### Response:
from igraph import Graph

# Create a graph
g = Graph.Erdos_Renyi(n=100, m=500)

# Assign random categories to each vertex
g.vs['category'] = ['A', 'B', 'C'][vertex.index % 3 for vertex in g.vs]

# Calculate the assortativity based on the categories
assortativity = g.assortativity_nominal('category')

print('Assortativity based on vertex categories:', assortativity)
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