<｜begin▁of▁sentence｜>### Instruction:
Imagine you're leading a PR campaign that aims to fortify relationships between various stakeholders and the public. To visualize this complex network of interactions, you have documented all the connections in an edgelist file named 'path_to_edgelist_file.edgelist'. This file contains critical data about the strength of each connection, as it's a weighted bipartite graph. Could you guide us on how we can employ NetworkX to bring this graph to life, ensuring that we can observe not just the interlinks but also appreciate the magnitude of each bond as represented by the weights in our edgelist? This visualization will be invaluable in strategizing our communication efforts effectively.
### Response:
import networkx as nx

# Read the edgelist from a file
G = nx.read_edgelist('path_to_edgelist_file.edgelist', nodetype=int, data=(('weight', float),))

# Print the edges with weight data
for edge in G.edges(data=True):
    print(edge)
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