This is my code:
file_input1 = open('Amazon_Indi_Seller.py', 'r')
f1 = file_input1.read().lower()
file_input2 = open('Amazon_Prices.py', 'r')
f2 = file_input2.read().lower()
documents = [f1, f2]
import nltk, string, numpy
stemmer = nltk.stem.porter.PorterStemmer()
lemmer = nltk.stem.WordNetLemmatizer()
def LemTokens(tokens):
return [lemmer.lemmatize(token) for token in tokens]
remove_punct_dict = dict((ord(punct), None) for punct in string.punctuation)
def LemNormalize(text):
return
LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))
from sklearn.feature_extraction.text import CountVectorizer
LemVectorizer = CountVectorizer(tokenizer=LemNormalize,
stop_words='english')
LemVectorizer.fit_transform(documents)
Instead of reading 2 files i want to read all the files in a directory. And read them individually so that later I can add those variables in a list named documents.