<｜begin▁of▁sentence｜>### Instruction:
Imagine you're overseeing a nutritional network where various food components, such as vitamins and minerals, are interconnected, much like the relationships within a balanced diet. Each connection — or 'edge' — represents a synergy between two nutrients, enhancing absorption or functionality in the body.

Consider this nutritional web: Vitamin C enhances iron absorption, calcium works closely with vitamin D, and omega-3 fatty acids complement the efficacy of vitamin E. If we represent these interactions in your dietary network as edges, with the numbers (1, 2), (1, 3), (2, 3), (2, 4), and (3, 4) corresponding to different vital nutrients, could you determine the average strength of nutrient-to-nutrient connectivity within this web?

This understanding would help us ensure that, on average, each nutrient is optimally connected to others, allowing for a harmonious and healthy diet plan.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (2, 4), (3, 4)])

# Calculate average node connectivity
avg_connectivity = nx.average_node_connectivity(G)

print('Average node connectivity:', avg_connectivity)
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