<｜begin▁of▁sentence｜>### Instruction:
Imagine you're at the salon, and two customers have come in wanting a fresh new look. The first one has a hairstyle that forms a perfect ring, looping all the way around with no beginning or end—let's say it has six sections, just like nodes in a cycle graph. The second client has a more adventurous 'do, something like a ponytail coming from the center of the crown with six sections radiating out from the ponytail base—a bit like a wheel graph with seven total sections, one for the ponytail and six around the head.

Your challenge, as the expert stylist that you are, is to find out the smallest number of snips, color changes, or restyles—our salon's version of edits—you'd need to transform the cycle-shaped hairstyle into the wheel-shaped one. We're looking for the minimum number of changes here, keeping it as simple and stylish as possible. So, how would you go about finding this minimum "hairdo edit distance" using your styling toolkit, or in our language, NetworkX?
### Response:
import networkx as nx

G1 = nx.cycle_graph(6)
G2 = nx.wheel_graph(7)

def compute_ged(G1, G2):
    min_dist = float('inf')
    for dist in nx.optimize_graph_edit_distance(G1, G2):
        if dist < min_dist:
            min_dist = dist
    return min_dist

min_ged = compute_ged(G1, G2)
print(f'Minimum Graph Edit Distance: {min_ged}')
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