<｜begin▁of▁sentence｜>### Instruction:
Imagine that you're working with a client who has a keen interest in mathematical structures, and during one of your therapy sessions, you decide to engage them in an activity that involves exploring the robustness of different shapes. You've chosen the icosahedral shape, which is one of the Platonic solids, known for its 20 faces and symmetry.

To make this activity relevant to their interest, you plan to involve them in a problem-solving session where you both will explore the resilience of this icosahedral structure in terms of its network connectivity. To do this, you want to use the icosahedral graph as a representation and determine the minimum number of edges that need to be removed to disconnect the graph. This concept is known as the graph's 'edge connectivity'.

For our session, we would visualize the structure digitally with the help of NetworkX, a powerful library in Python that specializes in the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

In our scenario, you'd explain to the client that this measure of edge connectivity would illustrate how well the structure would stand up to various challenges, if the connections represent paths or relationships that need to be maintained for the structure to function in its environment.

To keep with the therapy's goal of improving their daily life skills, you'd frame this exploration as a real-life analogy for resilience and problem-solving. By the end of our session, you aim to have the client understand how to compute this edge connectivity using NetworkX, which would give a practical application to their interest in mathematical structures.
### Response:
import networkx as nx

# Create a graph
G = nx.icosahedral_graph()

# Compute edge connectivity
connectivity = nx.edge_connectivity(G)

print('Edge connectivity:', connectivity)
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