將生成器表達式（<genexpr>）轉換爲列表？

Question

我正在做一些主題建模，並期待存儲我的分析結果。

import pandas as pd, numpy as np, scipy 
import sklearn.feature_extraction.text as text 
from sklearn import decomposition 

descs = ["You should not go there", "We may go home later", "Why should we do your chores", "What should we do"] 

vectorizer = text.CountVectorizer() 

dtm = vectorizer.fit_transform(descs).toarray() 

vocab = np.array(vectorizer.get_feature_names()) 

nmf = decomposition.NMF(3, random_state = 1) 

topic = nmf.fit_transform(dtm) 

topic_words = [] 

for t in nmf.components_: 
    word_idx = np.argsort(t)[::-1][:20] 
    topic_words.append(vocab[i] for i in word_idx) 

for t in range(len(topic_words)): 
    print("Topic {}: {}\n".format(t, " ".join([word for word in topic_words[t]]))) 

打印：

Topic 0: do we should your why chores what you there not may later home go 

Topic 1: should you there not go what do we your why may later home chores 

Topic 2: we may later home go what do should your you why there not chores 

我想寫這些主題的文件，所以我想將它們存儲在一個列表可能會奏效，像這樣：

l = [] 
for t in range(len(topic_words)): 
    l.append([word for word in topic_words[t]]) 
    print("Topic {}: {}\n".format(t, " ".join([word for word in topic_words[t]]))) 

但l只是最後一個空的數組。我如何將這些單詞存儲在列表中？

Answer 1

您正在將生成器表達式附加到列表topic_words，因此第一次打印時，生成器表達式已經用盡。你可以做，而不是：

topic_words = [] 

for t in nmf.components_: 
    word_idx = np.argsort(t)[::-1][:20] 
    topic_words.append([vocab[i] for i in word_idx]) 
#     ^      ^

有了這個，你顯然不會需要一個新的列表，你可以打印出：

for t, words in enumerate(topic_words, 1): 
    print("Topic {}: {}\n".format(t, " ".join(words)))