从pandas数据帧中获取N个最小距离对

import pandas as pd
from scipy.spatial.distance import pdist, squareform

data = {'A': [1, 2, 3, 4, 5],
        'B': [6, 7, 8, 9, 10],
        'C': [11, 12, 13, 14, 15]}
df = pd.DataFrame(data)

distances = pdist(df.values)

distance_matrix = squareform(distances)

indices = distance_matrix.argsort(axis=None)[:N]

min_distance_pairs = [(i // distance_matrix.shape[0], i % distance_matrix.shape[0]) for i in indices]

import pandas as pd
from scipy.spatial.distance import pdist, squareform

data = {'A': [1, 2, 3, 4, 5],
        'B': [6, 7, 8, 9, 10],
        'C': [11, 12, 13, 14, 15]}
df = pd.DataFrame(data)

distances = pdist(df.values)
distance_matrix = squareform(distances)

N = 3
indices = distance_matrix.argsort(axis=None)[:N]
min_distance_pairs = [(i // distance_matrix.shape[0], i % distance_matrix.shape[0]) for i in indices]

print(min_distance_pairs)