How to preprocess a corpus in Gensim

In this recipe, we will learn detailed steps to preprocess a corpus using the gensim library in python.

Recipe Objective: How to preprocess a corpus in Gensim?

Following the collection of our corpus, we usually wish to do a variety of preprocessing processes. Over here, we will remove some regularly used English terms (like 'a', 'the') and words that only appear once in the corpus. We'll tokenize our data as part of this process. Tokenization is the process of breaking down documents into words (the delimiter, in this case, will be space).

Sentiment Analysis Project on eCommerce Product Reviews with Source Code

Code:

#importing required libraries
import pprint

#creating a sample corpus for demonstration purpose
txt_corpus = [
"Find end-to-end projects at ProjectPro",
"Stop wasting time on different online forums to get your project solutions",
"Each of our projects solve a real business problem from start to finish",
"All projects come with downloadable solution code and explanatory videos",
"All our projects are designed modularly so you can rapidly learn and reuse modules"]

# Creating a set of frequent words
stoplist = set('for a of the and to in on of to are at'.split(' '))

# Lowercasing each document, using white space as delimiter and filtering out the stopwords
processed_text = [[word for word in document.lower().split() if word not in stoplist]for document in txt_corpus]

#displaying final tokens
pprint.pprint(processed_text)

Output:

[['find', 'end-to-end', 'projects', 'projectpro'],
 ['stop',
  'wasting',
  'time',
  'different',
  'online',
  'forums',
  'get',
  'your',
  'project',
  'solutions'],
 ['each',
  'our',
  'projects',
  'solve',
  'real',
  'business',
  'problem',
  'from',
  'start',
  'finish'],
 ['all',
  'projects',
  'come',
  'with',
  'downloadable',
  'solution',
  'code',
  'explanatory',
  'videos'],
 ['all',
  'our',
  'projects',
  'designed',
  'modularly',
  'so',
  'you',
  'can',
  'rapidly',
  'learn',
  'reuse',
  'modules']]

What Users are saying..

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Gautam Vermani

Data Consultant at Confidential
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Having worked in the field of Data Science, I wanted to explore how I can implement projects in other domains, So I thought of connecting with ProjectPro. A project that helped me absorb this topic... Read More

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