<｜begin▁of▁sentence｜>### Instruction:
As a radiologic technologist, you may need to analyze and interpret medical imaging data to identify cohesive subgroups within a patient population with a specific condition. For example, using the CohesiveBlocks method from igraph, you can analyze a network representing patients with a certain disease and then display the sizes of the cohesive subgroups that exist within the patient population. This analysis can help in understanding the interconnectedness of different patient groups and contribute to treatment planning and evaluation.
### Response:
from igraph import Graph, CohesiveBlocks

# Example graph with cohesive blocks
g = Graph.Famous('Zachary')
# Calculate cohesive blocks
blocks = CohesiveBlocks(g)
blocks = blocks.blocks

# Get the subgraphs of each block
subgraphs = blocks.subgraphs()

# Now, let's print the size of each subgraph
for i, sg in enumerate(subgraphs):
    print(f'Subgraph {i} size: {len(sg.vs)}')
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