<｜begin▁of▁sentence｜>### Instruction:
Imagine you're orchestrating a tightly-knit event where three essential stakeholders, designated by the tags 0, 1, and 2, are to be connected by a network of partnerships. The strength of these collaborations is quantified by mutual investments, valued at 1.0, 2.0, and 3.0 respectively, forging the links between each pair (0 & 1, 1 & 2, and 2 & 0). To ensure seamless coordination and to facilitate a strategic overview for the event’s success, would you be able to structure this complex web of collaborations into a streamlined resource—a dictionary within a dictionary—where each connection's financial weight is meticulously recorded via NetworkX? This detailed blueprint would be instrumental in visualizing and navigating the intricate interconnections at play within the event's framework.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add weighted edges
G.add_edges_from([(0, 1, {'weight': 1.0}), (1, 2, {'weight': 2.0}), (2, 0, {'weight': 3.0})])

# Convert to a dictionary of dictionaries representation
# Preserving edge weights
node_dict_of_dicts = nx.to_dict_of_dicts(G)

print(node_dict_of_dicts)
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