<｜begin▁of▁sentence｜>### Instruction:
Imagine you're tasked with selecting a range of products for your retail store, and you've categorized them based on their packaging size for logistical purposes—'Small' for products with a size rating of 2, and 'Medium' for those with a size rating of 3. Now, envision your products as a network where each product is a node. Products are paired like this: Small products are paired together (products 0 and 1), and Medium products are paired together (products 2 and 3).

With this network of products, you're looking to measure the tendency of products to pair with others that have the same packaging size—an attribute we can think of as 'size assortativity.' Using NetworkX, a software that analyzes the relationships within a network, how would you compute the 'size assortativity' coefficient for this network of products? This coefficient measures the preference for connections between products of similar sizes and can be valuable for inventory organization and planning.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add nodes with a numeric attribute 'size'
G.add_nodes_from([0, 1], size=2)
G.add_nodes_from([2, 3], size=3)

# Add edges
G.add_edges_from([(0, 1), (2, 3)])

# Compute assortativity for numerical node attribute 'size'
r = nx.numeric_assortativity_coefficient(G, 'size')
print('Numeric assortativity coefficient for attribute size:', r)
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