<｜begin▁of▁sentence｜>### Instruction:
Consider a bipartite graph with two sets of nodes {1, 2, 3} and {'a', 'b', 'c', 'd'}. Edges are added such that each node from the first set is connected to two nodes from the second set, forming a pattern like a path graph. How can you calculate the bipartite clustering coefficient for the nodes in the first set?
### Response:
import networkx as nx
from networkx.algorithms import bipartite

# Create a bipartite graph
B = nx.Graph()
B.add_edges_from([(1, 'a'), (1, 'b'), (2, 'b'), (2, 'c'), (3, 'c'), (3, 'd')])

# Assuming 1, 2, 3 are one set and 'a', 'b', 'c', 'd' are another set of bipartite graph
left_nodes = {1, 2, 3}

# Compute the bipartite clustering coefficient for nodes
clustering_coefficients = bipartite.clustering(B, nodes=left_nodes)
print(clustering_coefficients)
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