将生成器表达式（<genexpr>）转换为列表？

我正在做一些主题建模，并期待存储我的分析结果。将生成器表达式（<genexpr>）转换为列表？

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

我想写这些主题的文件，所以我想将它们存储在一个列表可能会奏效，像这样：

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只是最后一个空的数组。我如何将这些单词存储在列表中？

来源

2016-07-22 blacksite

'[在topic_words一个字一个字[T]] = = list（topic_words [t]）' –

题外话题：不要使用'l'作为变量名，它看起来太像数字'1'。 –

您正在将生成器表达式附加到列表topic_words，因此第一次打印时，生成器表达式已经用尽。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]) 
#     ^      ^

有了这个，你显然不会需要一个新的列表，你可以打印出：

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

来源

2016-07-22 21:11:38

将生成器表达式（<genexpr>）转换为列表？

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