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@article{159338,
        author = {Srikanth Dharavath and Bhavani Adula and Shiva Gampa and Jyotsna J},
        title = {Analyzing Data by Web Scraping Using Python},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {11},
        pages = {813-816},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159338},
        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.},
        keywords = {Data analysis, Web Scraping, Beautiful soup.},
        month = {},
        }