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preprocessing.py
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preprocessing.py
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import unicodedata
import re
import inflect
def removeNonASCII(data):
new_words=[]
for word in data:
new_word = unicodedata.normalize('NFKD', word).encode('ascii', 'ignore').decode('utf-8', 'ignore')
new_words.append(new_word)
return new_words
def lowerCase(data):
for i in range(len(data)):
temp = data[i].lower()
data[i] = temp
return data
def removePunctuation(data):
new_data = []
for word in data:
temp = re.sub(r'[^\w\s]', '', word)
if temp != "":
new_data.append(temp)
return new_data
def removeStopWords(data):
new_data = []
for word in data:
if word not in nltk.corpus.stopwords.words('english'):
new_data.append(word)
return new_data
def numberToWords(data):
for i in range(len(data)):
if data[i].isdigit() and int(data[i])<3000:
temp = inflect.engine().number_to_words(data[i])
data[i] = temp
return data
def stemming(data):
for i in range(len(data)):
temp = nltk.stem.LancasterStemmer().stem(data[i])
data[i] = temp
return data
def preprocess(data):
words = nltk.word_tokenize(data)
words = removeNonASCII(words)
words = lowerCase(words)
words = removePunctuation(words)
words = removeStopWords(words)
words = numberToWords(words)
#words = stemming(words)
return words
###https://www.kdnuggets.com/2018/03/text-data-preprocessing-walkthrough-python.html