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ENGDS-final-project

Image of TF-IDF findings

The Bestseller Blueprint

Amren Hossain

Abstract: This project uses a Python program to process bestselling books’ from the Publisher’s Weekly website. It looks at the summaries of the books to assess the similarities and differences amongst these books throughout 5 years. The goal of this project is to see what contributes to books becoming bestsellers. One main conclusion of this project found that genre of novels could be an indicator of bestselling status, along with the parts of speech that are used within the summary.

Website: The project is hosted on https://github.com/AmrenH/ENGDS-final-project

Specs: I used Python 3.12, the Natural Language Toolkit, Pandas, Matplotlib, and a virtual environment associated with smaller programs within the Beautiful Soup package. The project was coded on Visual Studio Code and uploaded to GitHub for easier viewing.

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Collecting bestselling books from each year and finding similarities

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