train_data1 = ['football is the sport', 'gravity is the movie',
    'education is important']
vectorizer = TfidfVectorizer(stop_words='english')
print('Applying first train data')
X_train = vectorizer.fit_transform(train_data1)
print(vectorizer.get_feature_names())
print("""
Applying second train data""")
train_data2 = ['cricket', 'Transformers is a film', 'AIMS is a college']
X_train = vectorizer.transform(train_data2)
print(vectorizer.get_feature_names())
print("""
Applying fit transform onto second train data""")
X_train = vectorizer.fit_transform(train_data1 + train_data2)
print(vectorizer.get_feature_names())
Updating the feature names into scikit TFIdfVectorizer