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In the rapidly evolving landscape of online shopping, the amalgamation of web scraping and data analysis has emerged as a powerful toolset, enabling businesses and data scientists to extract valuable insights and make informed decisions.This paper explores the utilization of Selenium, a robust automation tool, in conjunction with data science methodologies for extracting, processing, and analyzing data from e-commerce websites.The methodology involves the utilization of Selenium, a browser automation tool, to navigate through web pages, simulate user interactions, and extract data elements such as product details, prices, reviews, and other relevant information.
Lakshmi et al. (Sat,) studied this question.
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