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Overcoming Excel Data Overwrite in Python Web Scraping

This guide tackles the common issue of data overwriting when exporting web scraped information to Excel using Python. Learn how to store and manage your scraped data effectively! --- This video is based on the question https://stackoverflow.com/q/71847924/ asked by the user 'Yazılım Destek' ( https://stackoverflow.com/u/18786070/ ) and on the answer https://stackoverflow.com/a/71848252/ provided by the user 'HedgeHog' ( https://stackoverflow.com/u/14460824/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Pyhton Scraped data overwrite itself Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Overcoming Excel Data Overwrite in Python Web Scraping When you're scraping data from the web using Python, one common challenge many face is managing the data once it's been collected. Particularly, if you're pulling multiple items from a web page—like product information—it can be frustrating to see only the latest entry show up in your Excel sheet. This usually happens because each new set of data overwrites the previous one, leading to loss of valuable information. In this post, we will explore the solution to this problem and provide a clear method to ensure that all your scraped data is captured and exported correctly. Understanding the Problem In the example code provided, the scraping involves collecting various attributes for a product, such as the product name, ID, URL, and price. However, the way the data is initially stored leads to an overwrite issue, where only the last item captured is saved to the Excel file. Example Code Breakdown Here's the original code causing the issue: [[See Video to Reveal this Text or Code Snippet]] As you can see, the DataFrame is being created inside the loop, but only the last values read get included in the Excel file. The Solution To solve this problem, we can follow a different approach by storing each product's attributes in a list of dicts before creating the DataFrame. This way, we avoid overwriting previous data and capture all items. Step-by-Step Solution Initialize a List: Start by creating an empty list named data where you'll store all of your scraped data. [[See Video to Reveal this Text or Code Snippet]] Update the Loop: Inside the loop, instead of just assigning the last read values to individual variables, append each product's information as a dictionary to the data list. [[See Video to Reveal this Text or Code Snippet]] Create the DataFrame Once: After you exit the loop, create the DataFrame using the data list. [[See Video to Reveal this Text or Code Snippet]] Complete Revised Code Here’s how the complete, updated code will look: [[See Video to Reveal this Text or Code Snippet]] Conclusion By storing your scraped data in a list of dictionaries, you prevent overwriting and ensure all product information is collected and saved into your Excel sheet. This approach not only enhances the functionality of your script but also allows you to work with data more efficiently. Now, with this guide, you can confidently collect multiple data entries without the fear of losing previous information. Happy coding!