I have a data frame which consists:
source dest euclidean
A B 0.5
A C 1.5
A D 0.5
A E 0.8
B C 0.5
B D 6.5
B E 5.4
B A 4.8
C B 4.3
C D 3.6
C E 2.6
C A 3.5
D B 8.0
D C 2.7
D E 7.7
D A 7.3
I want to find Minimum Spanning Tree Which connects these points, where the weights edges are euclidean distance.
I tried using a method shown in Geeks for geeks EMST :
g = Graph(4)
for index,row in df.iterrows():
g.addEdge(row['source'],row['dest'],row['euclidean'])
g.KruskalMST()
But it gave an error.
Is there any other way I Can find this? Any leads will be helpful
Using networkx , you can use
from networkx import *
g = Graph()
for index,row in df.iterrows():
g.add_edge(row['source'],row['dest'],weight=row['euclidean'])
>>> list(minimum_spanning_edges(g))
[('A', 'E', {'weight': 0.8}),
('C', 'E', {'weight': 2.6}),
('C', 'D', {'weight': 2.7}),
('B', 'C', {'weight': 4.3})]
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