<｜begin▁of▁sentence｜>### Instruction:
Given a weighted undirected graph with the edge set [(0, 1, 4), (0, 2, 2), (2, 1, 1), (1, 3, 2), (1, 4, 2), (4, 5, 1)], calculate and sort the Laplacian centrality of each node. The weights on the edges represent the strength or capacity of the connections.
### Response:
import networkx as nx
from networkx.algorithms.centrality import laplacian_centrality

# Create a weighted undirected graph
edges = [(0, 1, 4), (0, 2, 2), (2, 1, 1), (1, 3, 2), (1, 4, 2), (4, 5, 1)]
G = nx.Graph()
G.add_weighted_edges_from(edges)

# Compute the Laplacian centrality of each node
lap_cent = laplacian_centrality(G)

# Sort the nodes by their Laplacian centrality and print them
sorted_lap_cent = sorted((v, f'{c:0.2f}') for v, c in lap_cent.items())
print(sorted_lap_cent)
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