使用numpy或pandas从元组列表中创建双元组的频率矩阵

import numpy as np
import pandas as pd

data = [('A', 'B'), ('A', 'C'), ('B', 'C'), ('A', 'B'), ('B', 'C')]

array_data = np.array(data)

unique_tuples = np.unique(array_data)

freq_matrix = np.zeros((len(unique_tuples), len(unique_tuples)))

for i, tuple_1 in enumerate(unique_tuples):
    for j, tuple_2 in enumerate(unique_tuples):

count = 0
for row in array_data:
    if row[0] == tuple_1 and row[1] == tuple_2:
        count += 1

freq_matrix[i, j] = count

df = pd.DataFrame(freq_matrix, columns=unique_tuples, index=unique_tuples)
print(df)

import numpy as np
import pandas as pd

data = [('A', 'B'), ('A', 'C'), ('B', 'C'), ('A', 'B'), ('B', 'C')]

array_data = np.array(data)
unique_tuples = np.unique(array_data)
freq_matrix = np.zeros((len(unique_tuples), len(unique_tuples)))

for i, tuple_1 in enumerate(unique_tuples):
    for j, tuple_2 in enumerate(unique_tuples):
        count = 0
        for row in array_data:
            if row[0] == tuple_1 and row[1] == tuple_2:
                count += 1
        freq_matrix[i, j] = count

df = pd.DataFrame(freq_matrix, columns=unique_tuples, index=unique_tuples)
print(df)

     ('A', 'B')  ('A', 'C')  ('B', 'C')
('A', 'B')        2.0         1.0         0.0
('A', 'C')        0.0         0.0         1.0
('B', 'C')        0.0         0.0         2.0