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Kellie Heckman Module 6 Web scraping Web mining and NLP Northwest Missouri State University

This module uses spaCy and BeautifulSoup to tokenize and lemmatize an article that was retrieved from a URL and the HTML saved to a .pkl file

Web Scraping and NLP with Requests, BeautifulSoup, and spaCy

Complete the tasks in the Python Notebook in this repository. Make sure to add and push the pkl or text file of your scraped html (this is specified in the notebook)

Rubric

  • (Question 1) Article html stored in separate file that is committed and pushed: 1 pt
  • (Question 2) Article text is correct: 1 pt
  • (Question 3) Correct (or equivalent in the case of multiple tokens with same frequency) tokens printed: 1 pt
  • (Question 4) Correct (or equivalent in the case of multiple lemmas with same frequency) lemmas printed: 1 pt
  • (Question 5) Correct scores for first sentence printed: 2 pts (1 / function)
  • (Question 6) Histogram shown with appropriate labelling: 1 pt
  • (Question 7) Histogram shown with appropriate labelling: 1 pt
  • (Question 8) Thoughtful answer provided: 1 pt