getfeatureinfo - 需要同时显示 x 和 y 的特征名称而不是索引号

Question

希望“结果”显示特征名称而不是索引。但无法生成，因为 get_feature_names() 不适用于 2d，并且 np.where() 仅返回索引号。

from sklearn.feature_extraction.text import CountVectorizer
import scipy.sparse as sp
import numpy as np
import pandas as pd

docs = ['this this this book',
    'this cat good',
    'cat good shit']
count_model = CountVectorizer(ngram_range=(2,2)) # default unigram model
X = count_model.fit_transform(docs)
X[X > 0] = 1 # run this line if you don't want extra within-text cooccurence (see below)
Xc = (X.T * X) # this is co-occurrence matrix in sparse csr format
Xc.setdiag(0) # sometimes you want to fill same word cooccurence to 0
xx = Xc.todense()
tri_upper_no_diag = np.triu(xx, k=1)
yy = tri_upper_no_diag.tolist()

columns = count_model.get_feature_names()

# Create a numpy array from a list of numbers
arr = np.array(yy) 
result = np.where(arr > 0)  

result