<｜begin▁of▁sentence｜>### Instruction:
Given a weighted undirected graph with nodes labeled 'A' through 'E' and edges with weights, how would you use Kruskal's algorithm to find the edges that form the minimum spanning tree, and what would that tree look like?
The graph is defined as:
Nodes: ['A', 'B', 'C', 'D', 'E']
Edges: {'A'-'B': 4, 'B'-'C': 1, 'C'-'A': 3, 'C'-'D': 2, 'D'-'E': 5}
### Response:
import networkx as nx
from networkx.algorithms import tree

# Create a weighted undirected graph
G = nx.Graph()
G.add_edge('A', 'B', weight=4)
G.add_edge('B', 'C', weight=1)
G.add_edge('C', 'A', weight=3)
G.add_edge('C', 'D', weight=2)
G.add_edge('D', 'E', weight=5)

# Find minimum spanning edges by Kruskal’s algorithm
mst_edges = tree.minimum_spanning_edges(G, algorithm='kruskal', data=False)
# Convert the iterator to a list of edges
edgelist = list(mst_edges)
# Sort the edges and print them
print(sorted(edgelist))
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