def unpack_dict(matrix, map_index_to_word):    table = sorted(map_index_to_word, key=map_index_to_word.get)          data = matrix.data    indices = matrix.indices    indptr = matrix.indptr            num_doc = matrix.shape[0]        return [{k:v for k,v in zip([table[word_id] for word_id in     indices[indptr[i]:indptr[i+1]] ],    data[indptr[i]:indptr[i+1]].tolist())} \               for i in range(num_doc) ]wiki['tf_idf'] = unpack_dict(tf_idf, map_index_to_word)

map_index_to_word 是一个包含数千个单词的单词:索引字典。tf_idf 是一个 TFIDF 稀疏向量。wiki 数据框的显示截图如下所示。

回答：

[{k: v for k, v in zip([table[word_id] for word_id in indices[indptr[i]:indptr[i + 1]]],data[indptr[i]:indptr[i + 1]].tolist())} for i in range(num_doc)]

与以下代码等效：

final_list = []for i in range(num_doc):    new_list = []    for word_id in indices[indptr[i]:indptr[i + 1]]:        new_list.append(table[word_id])    new_dict = {}    for k, v in zip(new_list, data[indptr[i]:indptr[i + 1]].tolist()):        new_dict[k] = v    final_list.append(new_dict)