Question

我正在使用Python34。我想从CSV文件中获取单词的频率，但它显示错误。这是我的代码。任何人都可以帮我解决这个问题。

from textblob import TextBlob as tb
import math

words={}
def tfidf(word, blob, bloblist):
    return tf(word, blob) * idf(word, bloblist)

def tf(word, blob):
    return blob.words.count(word) / len(blob.words)

def n_containing(word, bloblist):
    return sum(1 for blob in bloblist if word in blob)

def idf(word, bloblist):
    return math.log(len(bloblist) / (1 + n_containing(words, bloblist)))

bloblist = open('afterstopwords.csv', 'r').read()

for i, blob in enumerate(bloblist):
     print("Top words in document {}".format(i + 1))
     scores = {word: tfidf(word, blob, bloblist) for word in blob.words}
     sorted_words = sorted(scores.items(), key=lambda x: x[1], reverse=True)
     for word, score in sorted_words[:3]:
         print("\tWord: {}, TF-IDF: {}".format(word, round(score, 5)))

错误是：

 Top words in document 1
 Traceback (most recent call last):
 File "D:\Python34\tfidf.py", line 45, in <module>
    scores = {word: tfidf(word, blob, bloblist) for word in blob.words}
 AttributeError: 'str' object has no attribute 'words'

Answer 1

来自http://stevenloria.com/finding-important-words-in-a-document-using-tf-idf/ bloblist的一些代码是：

bloblist = [document1, document2, document3]

不要改变它。另外，在它之前是文件的代码，如：

document1 = tb("""blablabla""")

这就是我做的...我在python中使用一个函数来打开文件，其中openfile保存文件的详细信息。

txt =openfile()  
document1=tb(txt)  
bloblist = [document1]

原始代码的其余部分保持不变。这工作但我只能得到它来完成小文件。大文件需要太长时间。而且它看起来并不准确。对于字数统计，我使用https://rmtheis.wordpress.com/2012/09/26/count-word-frequency-with-python/
它已经很快地工作了9999行，每行50-75个字符。看似准确，结果似乎等同于wordcloud结果。

AttributeError：'str'对象没有属性'words'

1 个答案: