online gambling singapore online gambling singapore online slot malaysia online slot malaysia mega888 malaysia slot gacor live casino malaysia online betting malaysia mega888 mega888 mega888 mega888 mega888 mega888 mega888 mega888 mega888 Web Scraping, Regular Expressions, and Data Visualization: Doing it all in Python

摘要: A Small Real-World Project for Learning Three Invaluable Data Science Skills

 

 

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While most data used in classes and textbooks just appears ready-to-use in a clean format, in reality, the world does not play so nice. Getting data usually means getting our hands dirty, in this case pulling (also known as scraping) data from the web. Python has great tools for doing this, namely the requests library for retrieving content from a webpage, and bs4 (BeautifulSoup) for extracting the relevant information.

These two libraries are often used together in the following manner: first, we make a GET request to a website. Then, we create a Beautiful Soup object from the content that is returned and parse it using several methods.

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Our data is in there somewhere, but we need to extract it. To select our table from the soup, we need to find the right CSS selectors. One way to do this is by going to the webpage and inspecting the element. In this case, we can also just look at the soup and see that our table resides under a

HTML tag with the attribute class = "entry-content" . Using this info and the .find method of our soup object, we can pull out the main article content.

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Full Text: towardsdatascience



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