Without a doubt, integrating a scraper with Excel is a game changer. On the surface, Excel is primarily a data analysis and essential task automation tool. Couple it with a scraper and you get a real-time trends, keywords, and reviews tracker.
Such tracking capabilities give you an edge over your competition, especially if you are running a niche eCommerce business. And the list of positives does not end here. If you are stuck wondering how to get the two to work together, here is a step-by-step guide for you. Let’s learn how to scrape data from website to excel: a step-by-step guide
Scrape Data from Website to Excel: Step-by-Step Guide
1. Grasp the data traits for integration
To integrate your scraper efficiently and effectively with Excel, you must master the characteristics of data suitable for the integration. Why?
Excel structures information in a tabular layout. So, scraping a website with large blocks of unstructured data is a waste of time. Unless you are planning to extract specific elements of the data into Excel. Now, grasp these qualities of the data compatible with Excel’s tabular formatting:
- Numbers and text: Excel handles numeric data, dates, times, and plain text better than multimedia and images. It can also store rich text with simple formatting. In case you want to scrape multimedia and images, your best bet is to store links to the resources in Excel.
- Small to medium-sized: Even though user-friendly and versatile, Excel limits you to about 1 million entries. This number can accommodate small to moderate data sets. Get close to this number or go beyond, and you’ll start noticing a decline in performance, mainly if you are working with large files. If the target data has complex relationships, integrate your scraper with a database rather than Excel. Databases like MySQL can handle large amounts of data with complex relationships.
- Has repeated elements: You can comfortably scrape a website with repeated elements and store the data in Excel. This is because each column in Excel holds a particular attribute, which in this case is the element. Then, the rows hold each record of the component. For instance, a niche site with well-structured elements, including blog title, author, and date, is ideal. For a website like this, you can opt for Excel’s native web query tool as an excellent scraping Excel method.
2. Select the target site and build your web scraper
With the data qualities in mind, define your data needs and go hunting for a website with data that satisfies both. After identifying a suitable website, create a scraper using libraries or frameworks that include a built-in feature for exporting data to Excel. This allows you to automate the whole process of scraping web data into Excel rather than doing it manually or using third-party tools.
Take, for example, scraping with Python. You can use BeautifulSoup for scraping static websites and Pandas for exporting data into an Excel sheet.
BeautifulSoup works by parsing HTML pages to generate a tree of Python objects like navigable strings, comments, and tags. Then, using the built-in methods, you can search, traverse, manipulate, and extract desired data from static web pages.
Pandas, on the other hand, allows you to effortlessly export structured data into Excel using the to_excel() function. This makes it easier for you to automate the process of data scraping and moving data to the storage point, as Pandas also includes data manipulation functionality.
Besides scraping static content, you can also use Selenium to scrape structured dynamic content. Selenium is a Python library capable of automating various browsers’ interactions with dynamic content and retrieving the desired data. It can also work together with Pandas to output data to Excel.
3. Pull data from the target website and export it into Excel
Run the scraper to navigate the target website and retrieve data automatically. The same scraper should export the data into an Excel sheet. As a best practice, use intentional throttling and timers to avoid overwhelming the website’s servers. Doing so helps avoid triggering CAPTCHAs or an IP ban.
In case of an IP ban, you can lease more IPs from a proxy provider of your choice. There are also CAPTCHA resolvers for the purpose of bypassing CAPTCHAs in case your scraper keeps triggering CAPTCHAs.
Monitor and maintain your scraping scripts regularly to adapt to website layout changes. This helps minimize errors and downtime, especially when scraping eCommerce sites, which tend to change structure.
4. Clean and structure the data
After the scraper exports data into Excel, prepare the data for analysis by removing duplicates, handling missing values, and formatting data.
Excel has a built-in feature, “Remove Duplicates,” to identify and eliminate duplicates. It also has tools to replace missing values using formulas, like finding average values to fill the gaps.
For formatting, you have various options like converting text into numbers, standardizing data formats like the date, and more. Overall, Excel provides powerful tools for you to prepare the data for optimal use and, at the same time, extract valuable insights. However, while scraping websites to Excel, consider the following:
What to Consider When Scraping Website to Excel
1. Web scraping permissions
Some websites do not allow scraping. So, consider reviewing your target site’s robots.txt file to find out the limitations. Ignoring the details in the robots.txt file’s guidelines may land you into ethical or legal issues.
2. Compliance with Terms of Service (TOS)
Always go through and respect the target website’s terms of service. In case the TOS limits your scraping operations, you can reach out to the site’s owner to see if they can compromise. Otherwise, do not violate the rules outlined in the TOS to avoid legal or reputational trouble.
3. Respect for privacy and copyrights
Copyrighted content is legally protected, meaning scraping it without permission can land you into legal issues. The same goes for scraping personal or sensitive information without permission. Get consent from the owners of copyrighted or private content before extracting the data. Moreover, be transparent about your intentions.
Closing Words
Did you know that other than using Excel’s web query tool to scrape the web, you can build a scraper and integrate it with Excel? This integration breaks the limitations of Excel’s web query tool, allowing you to develop trackers and other real-time data analysis tools.
Use this blog post to understand how you can scrape a website to Excel. Get also to learn the considerations to keep in mind as you scrape various websites to reduce the chances of getting into legal issues. Remember, integrating a scraper with Excel works best when handling small to medium-sized data.
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