Scraping data from multiple webpages using python 📑 || python for beginners
Hello Guys,
Welcome to Day 80 of our web scraping journey! In this final chapter of our project, we embark on an exhilarating adventure as we expand our web scraping skills to extract specific data from multiple web pages of the same website. Join us as we fetch valuable information from a series of web pages, store it in lists, and then combine it into a comprehensive DataFrame for analysis and storage.
In this tutorial, we cover the following key topics:
Fetching Data from Multiple Webpages: Learn how to iterate through a range of web pages using a loop and extract data from each page using BeautifulSoup and requests. Explore techniques for handling pagination, dynamic content, and other challenges encountered when scraping data from multiple pages.
Storing Data in Lists: Utilize Python lists to store the extracted data from each web page, allowing for easy organization and manipulation. Append relevant data elements such as company names, ratings, reviews, service offerings, and more to their respective lists for further processing.
Creating a DataFrame: Combine the data lists into a structured DataFrame using pandas, providing a unified representation of the extracted information. Utilize pandas' DataFrame constructor to create a tabular dataset with labeled columns and rows, facilitating data analysis and visualization.
Exporting Data to CSV: Store the final DataFrame containing the aggregated data in a CSV (Comma-Separated Values) file for future use and analysis. Utilize pandas' to_csv() function to export the DataFrame to a CSV file with customizable options for index inclusion and file formatting.
By the end of this tutorial, you'll have the skills and knowledge to fetch data from multiple web pages, organize it into a DataFrame, and export it to a CSV file for further analysis and storage.
Don't forget to like, share, and subscribe for more informative tutorials on web scraping, data extraction, and Python programming. Stay tuned for our next series, where we'll explore advanced techniques and applications in the exciting field of web scraping!
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