Analyzing Data by Web Scraping Using Python

Analyzing Data by Web Scraping Using Python
Author(s):
Srikanth Dharavath, Bhavani Adula, Shiva Gampa, Jyotsna J
Keywords:
Data analysis, Web Scraping, Beautiful soup.
Abstract
Web scraping refers to the process of extracting structured data from HTML content. To achieve this, a web scraper is utilized to extract specific information from a desired website. This information can be obtained by using the inspect option to select the relevant class of data, which is then scraped. There are two main libraries used for web scraping: the "Request" library, which updates the HTML data, and the "Beautiful Soup" library, which scrapes data from the desired website. The data obtained can be stored in a CSV file or represented on a website or charts using the Python library, Matplotlib. In addition to acquiring data, web scraping can also be used to archive and track changes to online data that may be poorly structured or not presented in tabular form.
Article Details
Unique Paper ID: 159338 Publication Volume & Issue: Volume 9, Issue 11 Page(s): 813 - 816
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org