<｜begin▁of▁sentence｜>### Instruction:
Given a bipartite graph B with edge set [(1, 'A'), (1, 'B'), (2, 'B'), (2, 'C'), (3, 'C'), (3, 'A')], where node set {1, 2, 3} is the 'top' nodes and {'A', 'B', 'C'} is the 'bottom' nodes, how do you use NetworkX's overlap_weighted_projected_graph function to compute the weighted projection onto the bottom nodes, using the Jaccard index as the weight?
### Response:
import networkx as nx
from networkx.algorithms import bipartite

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

# Specify the nodes to project onto (bottom nodes)
nodes = ['A', 'B', 'C']

# Get the weighted projection of the bipartite graph
G = bipartite.overlap_weighted_projected_graph(B, nodes, jaccard=True)

# Print the edges with weights
e = list(G.edges(data=True))
print(e)
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