Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge.
The term used for extracting data from the web or internet is referred to as web scraping. You will Learn what web scraping is and how it can be achieved with the help of Python's beautiful soup library.
Web scraping is an important technique that is widely used as the first step in many workflows in data mining, information retrieval, and text-based machine learning.
In this course, Extracting Data from HTML with BeautifulSoup* you will gain the ability to build robust, maintainable web scraping solutions using the Beautiful Soup library in Python.
Beautiful Soup is a pure Python library for extracting structured data from a website. It allows you to parse data from HTML and XML files. It acts as a helper module and interacts with HTML in a similar and better way as to how you would interact with a web page using other available developer tool.
In the time when the internet is rich with so much data, and apparently, data has become the new oil, web scraping has become even more important and practical to use in various applications. Web scraping deals with extracting or scraping the information from the website. Web scraping is also sometimes referred to as web harvesting or web data extraction. Copying text from a website and pasting it to your local system is also web scraping. However, it is a manual task. Generally, web scraping deals with extracting data automatically with the help of web crawlers. Web crawlers are scripts that connect to the world wide web using the HTTP protocol and allows you to fetch data in an automated manner.
Whether you are a data scientist, engineer, or anybody who analyzes vast amounts of datasets, the ability to scrape data from the web is a useful skill to have. Let's say you find data from the web, and there is no direct way to download it, web scraping using Python is a skill you can use to extract the data into a useful form that can then be imported and used in various ways.