如何使用Scikit Learn countvector获取语料库中的单词频率？

Question

我试图使用scikit learn的CountVectorizer计算一个简单的单词频率。

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

texts=["dog cat fish","dog cat cat","fish bird","bird"]
cv = CountVectorizer()
cv_fit=cv.fit_transform(texts)

print cv.vocabulary_
{u'bird': 0, u'cat': 1, u'dog': 2, u'fish': 3}

我以为它会返回{u'bird': 2, u'cat': 3, u'dog': 2, u'fish': 2}。

Answer 1

我们将使用zip方法从单词列表和计数列表中生成dict

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

texts=["dog cat fish","dog cat cat","fish bird","bird"]    

cv = CountVectorizer()   
cv_fit=cv.fit_transform(texts)    
word_list = cv.get_feature_names();    
count_list = cv_fit.toarray().sum(axis=0)    

print word_list
['鸟'，'猫'，'狗'，'鱼']
print count_list
[2 3 2 2]
print dict(zip(word_list,count_list))
{'fish'：2，'dog'：2，'bird'：2，'cat'：3}