Use of TfidfVectorizer on dataframe I have the dataframe which has two colums(Reviews and Label):  

  Reviews                                     Label  
0 [cameron, diaz, woman, marri, judg, play]   1  
1 [turgid, dialogu, feebl, character, harvey] 0  
2 [misfortun, watch, rubbish, sky, cinema]    1 


I want to apply the TfidfVectorizer on the DF.
I have written the following code.  

from sklearn.feature_extraction.text import TfidfVectorizer  
df_x=train_df["Reviews"]  
df_y=train_df["Label"]  
cv = TfidfVectorizer()   
df_xcv = cv.fit_transform(df_x)  
a=df_xcv.toarray()  
cv.get_feature_names()  


which is giving an error:


  AttributeError: 'list' object has no attribute 'lower'


Why is this throwing an error?
Your reviews column is a column of lists, and not text. Tfidf Vectorizer works on text. I see that your reviews column is just a list of relevant polarity defining adjectives. A simple workaround is:

df['Reviews']=[" ".join(review) for review in df['Reviews'].values]


And then run the vectorizer again. That will fix the problem.