

import nltk

nltk.download('vader_lexicon')
nltk.download('punkt')

from nltk.sentiment.vader import SentimentIntensityAnalyzer


y_pred = []
sid = SentimentIntensityAnalyzer()
for row in df_test.iterrows():
    
    sscore = sid.polarity_scores(row[1]['message'])
    if sscore['neg'] >= sscore['pos']:
        y_pred.append(0)
    else:
        y_pred.append(1)
{"license": "mit"}
license:mit region:us
TAGS
#license-mit #region-us 



import nltk

nltk.download('vader_lexicon')
nltk.download('punkt')

from URL import SentimentIntensityAnalyzer


y_pred = []
sid = SentimentIntensityAnalyzer()
for row in df_test.iterrows():
    
    sscore = sid.polarity_scores(row[1]['message'])
    if sscore['neg'] >= sscore['pos']:
        y_pred.append(0)
    else:
        y_pred.append(1)
TAGS
#license-mit #region-us 

passage: TAGS
#license-mit #region-us 
