<｜begin▁of▁sentence｜>### Instruction:
Given a dictionary of dictionaries with nested structure corresponding to nodes, neighbors, and edge attributes, can you convert this data into a NetworkX Graph, iterate through the edges, and print each edge with its assigned weight? The provided data is a simple weighted graph with the following adjacency representation: {0: {1: {'weight': 1}}, 1: {2: {'weight': 2}}, 2: {0: {'weight': 3}}}. Assume each inner dictionary represents connections from a node to its neighbors along with the edge's weight.
### Response:
import networkx as nx

# Define the dictionary of dictionaries
# Each first-level key is a node, its value is another dict
# The second-level key is a neighbor and its value is edge attribute data
dod = {0: {1: {'weight': 1}}, 1: {2: {'weight': 2}}, 2: {0: {'weight': 3}}}

# Create a graph using the dictionary of dictionaries
G = nx.from_dict_of_dicts(dod)

# Iterate through the edges and print them with the respective weight
for u, v, data in G.edges(data=True):
    print(f'Edge {u}-{v} with weight {data['weight']}')
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