Semalt – How To Scrape Data From Websites Into Excel
It's been proven time and time again that data should be at the core of any decision making. As such, businesses have to stay ahead of this huddle by devising efficient methods of collecting such data. To begin with, there are various methods of harvesting data from websites. And they are all important although to varying degrees because each process has its highs and lows.
For one to pick one method over the others, you would have to analyze your project size first of all and decide if the process you want will adequately meet your requirements. Let's go ahead and look at some of these methods of mining data from websites.
1. Get a premium scraping software
While these will set you back a couple of backs, they perform excellently, especially in huge projects. This is because the majority of these programs have undergone years of development and the companies owning them have invested heavily in code development as well as debugging. With such software, you will be free to set up all the parameters that you want as well as gain access to advanced crawling tools.
These programs also allow you to use various means of content exporting, from JSON to excel sheets. You will, therefore, have no trouble transferring your scraped data to analysis tools.
2. Web query within excel
Excel offers a nifty tool called web query that allows you to get external data from the web. To launch it, navigate to Data> Get External Data> From Web, this will launch the "new web query" window. Input your desired website in the address bar, and the page will automatically load.
And it gets even better: the tool will automatically recognize data and tables and show yellow icons against such content. You can then proceed to mark the appropriate one and press import to begin data extraction. The tool will then organize the data into columns and rows. While this method is perfect for crawling through a single page, it is however limited in terms of automation as you will have to repeat the process for each page. Also, the scraper cannot retrieve information such as phone numbers or emails as they are not always provided on the page.
3. Use Python/ Ruby libraries
If you know your way around these programming languages, you can try out one of the many data scraping libraries out there. This will allow you to use queries and decide how your data will be saved, in this case, you can use the CSV libraries to export the content to CSV files allowing an easy switch between different projects while maintaining compatibility.
4. Use one of the many web scraping browser extensions available
Unlike conventional software, these tools only require you to have an up-to-date browser for them to work with. They are also easy to use and highly recommended for small scraping projects because the majority of them are free and will perform just fine. They also offer different data exportation modes from CSV files to JSON feeds.
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