<｜begin▁of▁sentence｜>### Instruction:
Given a bipartite graph with two sets of nodes U = {'A', 'B', 'C', 'D'} and V = {1, 2, 3, 4}, and edges between them as {'A': [1, 2], 'B': [1], 'C': [2, 3], 'D': [3, 4]}, compute the bipartite Robins and Alexander clustering coefficient using NetworkX.
### Response:
from networkx.algorithms import bipartite
import networkx as nx

# Create a bipartite graph
B = nx.Graph()
B.add_nodes_from(['A', 'B', 'C', 'D'], bipartite=0) # Add the node attribute 'bipartite'
B.add_nodes_from([1, 2, 3, 4], bipartite=1)
B.add_edges_from([('A', 1), ('A', 2), ('B', 1), ('C', 2), ('C', 3), ('D', 3), ('D', 4)])

# Compute the bipartite Robins and Alexander clustering
clustering = bipartite.robins_alexander_clustering(B)

print(f'The bipartite Robins and Alexander clustering coefficient is: {clustering:.3f}')
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