<｜begin▁of▁sentence｜>### Instruction:
Given a bipartite graph with nodes [1, 2, 3, 4] in one set and ['a', 'b', 'c'] in the other, and the edges [(1, 'a'), (1, 'b'), (2, 'b'), (2, 'c'), (3, 'c'), (4, 'a')], can you compute the bipartite clustering coefficient for the nodes using NetworkX?
### Response:
import networkx as nx
from networkx.algorithms import bipartite

# Create a bipartite graph
B = nx.Graph()
B.add_nodes_from([1, 2, 3, 4], bipartite=0)
B.add_nodes_from(['a', 'b', 'c'], bipartite=1)
B.add_edges_from([(1, 'a'), (1, 'b'), (2, 'b'), (2, 'c'), (3, 'c'), (4, 'a')])

# Calculate bipartite clustering using the 'dot' mode
clustering = bipartite.clustering(B, mode='dot')
print(clustering)
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