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| import json | |
| import pickle | |
| import pandas as pd | |
| import nltk | |
| nltk.download('stopwords') | |
| import regex as re | |
| from nltk.corpus import stopwords | |
| class Preprocess: | |
| genres = None | |
| y = None | |
| def __init__(self) -> None: | |
| self.genres = [] | |
| def clean_text(self, text): | |
| """Cleans text by removing certains unwanted characters""" | |
| # remove backslash-apostrophe | |
| text = re.sub("\'", "", text) | |
| # remove everything except alphabets | |
| text = re.sub("[^a-zA-Z]"," ",text) | |
| # remove whitespaces | |
| text = ' '.join(text.split()) | |
| # convert text to lowercase | |
| text = text.lower() | |
| return text | |
| def remove_stopwords(self,text): | |
| """Function to remove stopwords""" | |
| stop_words = set(stopwords.words('english')) | |
| no_stopword_text = [w for w in text.split() if not w in stop_words] | |
| return ' '.join(no_stopword_text) | |
| def apply(self, plot): | |
| clean_plot = self.clean_text(str(plot)) | |
| clean_plot = self.remove_stopwords(str(clean_plot)) | |
| return clean_plot | |