# load all necessary libraries
import pandas as pd
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from sklearn.feature_extraction.text import CountVectorizer

pd.set_option('max_colwidth', 100)

documents = ["Gangs of Wasseypur is a great movie.", "The success of a movie depends on the performance of the actors.", "There are no new movies releasing this week."]
print(documents)

def preprocess(document):
    'changes document to lower case and removes stopwords'

    # change sentence to lower case
    document = document.lower()

    # tokenize into words
    words = word_tokenize(document)

    # remove stop words
    words = [word for word in words if word not in stopwords.words("english")]

    # join words to make sentence
    document = " ".join(words)
    
    return document

documents = [preprocess(document) for document in documents]
print(documents)