使用nltk处理项目情绪分析股票。我通过GH搜索过,发现没有类似的sentimaent_analyser或popular_scores调用。
我还查看了Python 3.4 - 'bytes' object has no attribute 'encode'并且它并不重复,因为我没有调用bcrypt.gensalt()。encode(' utf-8')。虽然它确实暗示了某种错误类型的问题。
任何人都可以帮忙解决此错误吗?
我收到错误:
init 中的/lib/python3.5/site-packages/nltk/sentiment/vader.py(self,text) 154 def init (self,text): 155如果不是isinstance(text,str): - > 156 text = str(text.encode(' utf-8')) 157 self.text =文字 158 self.words_and_emoticons = self._words_and_emoticons()
AttributeError:' bytes'对象没有属性'编码'
数据帧df_stocks.head(5)是:
prices articles
2007-01-01 12469 What Sticks from '06. Somalia Orders Islamist...
2007-01-02 12472 Heart Health: Vitamin Does Not Prevent Death ...
2007-01-03 12474 Google Answer to Filling Jobs Is an Algorithm...
2007-01-04 12480 Helping Make the Shift From Combat to Commerc...
2007-01-05 12398 Rise in Ethanol Raises Concerns About Corn as...
代码如下,最后一行出现错误:
import numpy as np
import pandas as pd
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import subjectivity
from nltk.sentiment import SentimentAnalyzer
from nltk.sentiment.util import *from nltk.sentiment.vader import SentimentIntensityAnalyzer
import unicodedata
for date, row in df_stocks.T.iteritems():
sentence = unicodedata.normalize('NFKD', df_stocks.loc[date, 'articles']).encode('ascii','ignore')
ss = sid.polarity_scores(sentence)
谢谢
答案 0 :(得分:1)
从 unicodedata.normalize() docs开始,该方法将UNICODE字符串转换为通用格式字符串。
import unicodedata
print(unicodedata.normalize('NFKD', u'abcdあäasc').encode('ascii', 'ignore'))
它会得到:
b'abcdaasc'
所以,问题在于:df_stocks.loc[date, 'articles']
不是UNICODE字符串。