Web Scraping for Python using Beautiful Soup
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Learn web scraping with BeautifulSoup, a Python library for extracting data from web pages. Discover how to parse HTML and XML documents efficiently, navigate their structure, and extract information using filters. Download and scrape web page contents, including images and HTML tables, and convert data into a Pandas DataFrame for analysis. Start your data science journey now!
At a Glance
Data is the fuel of Data Science. We can get data from databases and other data repositories. A lot of data is published as web pages. Web scraping is the process of harvesting data from web pages. BeautifulSoup is a Python library that allows for web scraping, parsing, and extracting data from HTML and XML documents. In this guided project, you will use BeautifulSoup to scrape the contents of a web page.
Web scraping with BeautifulSoup is a popular method for extracting data from websites and transforming the scraped data into a structured format for analysis and manipulation. BeautifulSoup provides a simple and efficient way to parse HTML and XML documents, an essential tool for web scraping projects.
First, you’ll create a BeautifulSoup object and learn how to navigate its HTML structure using tags, children, parents, and siblings. Then, you’ll extract information, or elements, from HTML files by using filters, find_all, and find. Then, after you locate the specified elements, you will extract their text or attributes. Then, you’ll download and scrape the contents of a web page, including images and data from HTML tables, and convert the data into a Pandas DataFrame for further analysis.
