<｜begin▁of▁sentence｜>### Instruction:
{'Description': "Given a bipartite graph with two node sets X = {1, 2, 3} and Y = {'a', 'b', 'c'}, where edges are defined connecting nodes from set X to set Y such as (1, 'a'), (1, 'b'), (2, 'a'), (2, 'b'), (2, 'c'), (3, 'c'), how can we compute the average clustering coefficient for the entire graph, as well as separately for nodes in set X and nodes in set Y?", 'Data': "The graph consists of two sets of nodes, X and Y, with edges that connect only between one node in X and one node in Y, forming a bipartite graph. Node set X contains nodes {1, 2, 3} and node set Y contains nodes {'a', 'b', 'c'}. Edges are specified between nodes in X and nodes in Y.", 'Problem': 'The code calculates the average bipartite clustering coefficient for the whole graph, as well as separately for each bipartite set X and Y.'}
### Response:
import networkx as nx

G = nx.Graph()
G.add_edges_from([(1, 'a'), (1, 'b'), (2, 'a'), (2, 'b'), (2, 'c'), (3, 'c')])
X = {1, 2, 3}
Y = {'a', 'b', 'c'}
clust_coeff_X = bipartite.average_clustering(G, X, mode='dot')
print('Average clustering coefficient for set X:', clust_coeff_X)
clust_coeff_Y = bipartite.average_clustering(G, Y, mode='dot')
print('Average clustering coefficient for set Y:', clust_coeff_Y)
clust_coeff = bipartite.average_clustering(G, mode='dot')
print('Average bipartite clustering coefficient:', clust_coeff)
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