<｜begin▁of▁sentence｜>### Instruction:
Imagine you're evaluating the health and interconnectedness of various cells in a patch of skin tissue. Each cell is connected to others, sharing nutrients and signals, much like nodes in a network. Drawing parallels between the cellular connections and a graph, the relationships we're focusing on are between cell 0 and cells 1, 2, and 3, as well as the connections between cell 1 and cells 2 and 3. In this biological network representation of the skin cells, can you analyze the tissue's resilience by calculating the average local efficiency, akin to assessing how effectively the cells communicate with one another when one pathway is disrupted?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)])

# Calculate the average local efficiency
avg_local_efficiency = nx.local_efficiency(G)

print('Average local efficiency:', avg_local_efficiency)
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