<｜begin▁of▁sentence｜>### Instruction:
Given a directed acyclic graph with the edge set [(1, 2), (1, 3), (2, 3), (3, 4), (4, 5)], how can you compute its transitive reduction using NetworkX, and how can you ensure that the node and edge data are preserved in the reduced graph?
### Response:
import networkx as nx

# Create a directed acyclic graph (DAG)
DG = nx.DiGraph([(1, 2), (1, 3), (2, 3), (3, 4), (4, 5)])

# Perform transitive reduction on the DAG
TR = nx.transitive_reduction(DG)

# Print the edges of the transitive reduction
print(list(TR.edges()))

# Add node data from the original graph to the transitive reduction
TR.add_nodes_from(DG.nodes(data=True))

# Add edge data from the original graph to the transitive reduction
TR.add_edges_from((u, v, DG.edges[u, v]) for u, v in TR.edges())

# Print the edges with data of the transitive reduction
print(list(TR.edges(data=True)))
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