我正在尝试解析网站并生成正面、中性或负面情绪分析

Question

我正在尝试从 CNBC 网站获取非常基本的情绪分析。我把这段代码放在一起，它工作正常。

from bs4 import BeautifulSoup
import urllib.request
from  pandas import DataFrame

resp = urllib.request.urlopen("https://www.cnbc.com/finance/")
soup = BeautifulSoup(resp, from_encoding=resp.info().get_param('charset'))
    
substring = 'https://www.cnbc.com/'

df = ['review']
for link in soup.find_all('a', href=True):
    print(link['href'])
    if (link['href'].find(substring) == 0): 
        # append
        df.append(link['href'])

#print(link['href'])


#list(df)
# convert list to data frame
df = DataFrame(df)
#type(df)
#list(df)

# add column name
df.columns = ['review']

# clean up
df['review'] = df['review'].str.replace('\d+', '')

# Get rid of special characters
df['review'] = df['review'].str.replace(r'[^\w\s]+', '')


from nltk.sentiment.vader import SentimentIntensityAnalyzer
sid = SentimentIntensityAnalyzer()
df['sentiment'] = df['review'].apply(lambda x: sid.polarity_scores(x))
def convert(x):
    if x < 0:
        return "negative"
    elif x > .2:
        return "positive"
    else:
        return "neutral"
df['result'] = df['sentiment'].apply(lambda x:convert(x['compound']))
df['result']

当我运行上面的代码时，我得到了肯定和否定，但这些并没有映射到原始 'review'。我如何在每个 link 的语言旁边显示数据框中的每种情绪？谢谢！

Answer 1

哦，伙计，我完全失去了它！这只是一个简单的合并！！

df_final = pd.merge(df['review'], df['result'], left_index=True, right_index=True)
df_final

结果：

0                                              review  neutral
1                      https://www.cnbc.com/business/  neutral
2   https://www.cnbc.com/2020/09/15/stocks-making-...  neutral
3   https://www.cnbc.com/2020/09/15/stocks-making-...  neutral
4             https://www.cnbc.com/maggie-fitzgerald/  neutral
..                                                ...      ...
90                      https://www.cnbc.com/finance/  neutral
91  https://www.cnbc.com/2020/09/10/citi-ceo-micha...  neutral
92                https://www.cnbc.com/central-banks/  neutral
93  https://www.cnbc.com/2020/09/10/watch-ecb-pres...  neutral
94               https://www.cnbc.com/finance/?page=2  neutral

我正在尝试解析网站并生成正面、中性或负面情绪分析

I am trying to parse a website and generate positive, neutral, or negative sentiment analysis

python

machine-learning

python-3.x

sentiment-analysis