หลายคอลัมน์ข้อความ

# Import the vectorizer and default English stop words list
____

# Define the stop words
my_stop_words = ____._____(['airline', 'airlines', '@', 'am', 'pm'])
 
# Build and fit the vectorizers
vect1 = CountVectorizer(____=my_stop_words)
vect2 = CountVectorizer(____=____) 
vect1.fit(tweets.text)
vect2.fit(tweets.negative_reason)

# Print the last 15 features from the first, and all from second vectorizer
print(vect1.get_feature_names()[-15:])
print(vect2.get_feature_names())