Open AccessVisualization of Optimal Product Pricing using E-Commerce Data
Author(s) -
N Greeshma*,
C. H. Raghavendra,
K. Rajendra Prasad
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a5262.119119
Subject(s) - computer science , python (programming language) , task (project management) , e commerce , visualization , product (mathematics) , world wide web , selection (genetic algorithm) , data mining , machine learning , engineering , geometry , mathematics , systems engineering , operating system
With the number of e-commerce websites being increasing rapidly, online shopping has become the trend nowadays. Though, online shopping is very easy; however, when it comes to product selection it is a tedious task and time consuming to identify which online site gives us the best price and offers. Comparing products and filtering them from each online site is a very time consuming task for a buyer. This paper uses the techniques of Web Scraping using python libraries like Beautiful Soup, requests, matplotlib for identifying the best prices and for deciding the best product deal to the customer from different online websites. Web scraping is an automated technique of extracting data from websites. In this paper, real time data is extracted from various e-commerce sites and compared automatically. Finally, the results are graphically displayed based on which the customer makes the appropriate decision.