Update tweet_analyzer.py

tweet_analyzer.py

@@ -109,15 +109,14 @@ class TweetDatasetProcessor:
 
         def analyze_topics(self, n_topics=5):
             """Extract and identify different topics the author has tweeted about""" 
-            all_tweets = [tweet['content'] 
-            for tweet in self.tweets] vectorizer = TfidfVectorizer(stop_words='english')
+            all_tweets = [tweet['content'] for tweet in self.tweets]
+            vectorizer = TfidfVectorizer(stop_words='english')
             tfidf_matrix = vectorizer.fit_transform(all_tweets)
             nmf_model = NMF(n_components=n_topics, random_state=1)
             nmf_model.fit(tfidf_matrix)
             topics = [] 
             for topic_idx, topic in enumerate(nmf_model.components_): 
-               topic_words = [vectorizer.get_feature_names_out()[i]
-            for i in topic.argsort()[:-n_topics - 1:-1]] 
+               topic_words = [vectorizer.get_feature_names_out()[i] for i in topic.argsort()[:-n_topics - 1:-1]] 
                topics.append(" ".join(topic_words)) 
             return topics