I don't know why this AttributeError: 'numpy.ndarray' object has no attribute 'lower' occurs

I'm trying to run a linear regression. But I'm getting this "AttributeError: 'numpy.ndarray' object has no attribute 'lower' " Here's the code I'using:

#Loading the dataset
import pandas as pd
dataset= pd.read_csv('C:/Users/User/MiniProject/MovieReview.csv')
X = dataset.iloc[:,:-1].values
y = dataset.iloc[:,-1].values

def getStemmedReview(review):
    review=review.lower()
    review=review.replace("<br /><br />"," ")
    #Tokenize
    tokens=tokenizer(review)
    new_tokens=[token for token in tokens if token not in  stop]
    stemmed_tokens=[porter.stem(token) for token in new_tokens]
    clean_review=' '.join(stemmed_tokens)
    return clean_review

dataset['text'].apply(getStemmedReview)

from sklearn.model_selection import train_test_split
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.50,random_state=0)

from sklearn.feature_extraction.text import TfidfVectorizer
vectorizer.fit(X_train)
X_train=vectorizer.transform(X_train)
X_test=vectorizer.transform(X_test)


AttributeError                            Traceback (most recent call last)
<ipython-input-72-a51b69c7d0ba> in <module>()
      1 from sklearn.feature_extraction.text import TfidfVectorizer
      2 
----> 3 vectorizer.fit(X_train)
      4 X_train=vectorizer.transform(X_train)
      5 X_test=vectorizer.transform(X_test)

~\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in fit(self, raw_documents, y)
   1359         self : TfidfVectorizer
   1360         """
-> 1361         X = super(TfidfVectorizer, self).fit_transform(raw_documents)
   1362         self._tfidf.fit(X)
   1363         return self

~\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in fit_transform(self, raw_documents, y)
    867 
    868         vocabulary, X = self._count_vocab(raw_documents,
--> 869                                           self.fixed_vocabulary_)
    870 
    871         if self.binary:

~\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in _count_vocab(self, raw_documents, fixed_vocab)
    790         for doc in raw_documents:
    791             feature_counter = {}
--> 792             for feature in analyze(doc):
    793                 try:
    794                     feature_idx = vocabulary[feature]

~\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in <lambda>(doc)
    264 
    265             return lambda doc: self._word_ngrams(
--> 266                 tokenize(preprocess(self.decode(doc))), stop_words)
    267 
    268         else:

~\Anaconda3\lib\site-packages\sklearn\feature_extraction\text.py in <lambda>(x)
    230 
    231         if self.lowercase:
--> 232             return lambda x: strip_accents(x.lower())
    233         else:
    234             return strip_accents

AttributeError: 'numpy.ndarray' object has no attribute 'lower'