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Automating Data Collection from Web Sources
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Automating Data Collection from Web Sources

Automating Data Collection from Web Sources

IntroductionThe Requests LibraryParse the HTML Content Using BeautifulSoupExtract the Desired AttributeStore Scraped Data Into a Pandas DataFrameInclude Other Informations in the Scraping ProcessRegular Expressions

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Store Scraped Data Into a Pandas DataFrame

Storing scraped data in a pandas DataFrame is a convenient way to manipulate and work with the data. pandas is a powerful library in Python that provides easy-to-use data structures and data analysis tools.

A DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it as a spreadsheet, SQL table, or a dictionary of Series objects. It is generally the most commonly used pandas object.

Task

Swipe to start coding

  1. Import pandas and initialize an empty DF;
  2. Scrape the country name (find all instances on the web page);
  3. Scrape the capital city (find all instances on the web page);
  4. Append the scraped values (country_name, item) in the df.

Solution

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Section 1. Chapter 5
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