How to Scrape Data from a Website to Excel?

There are over 1.11 billion websites and more than 50 billion web pages on the internet and these are full of a diverse range of information, from text and images to tables and charts. Tasks like data analysis, reporting, database management and more require this data to be extracted into a structured format. Due to its powerful data manipulation and visualisation capabilities, Excel becomes a popular choice to organise and analyse scraped data.

Web scraping is a technique used to extract data from websites, and converting this data into Excel spreadsheets can greatly enhance its usability. Whether you're compiling market research, tracking financial metrics, or aggregating information for reports, knowing how to scrape data directly into Excel can streamline your workflow.

In this blog, we'll dive into the process of scraping data from a website and importing it into Excel. We'll cover the basics of web scraping and then go through step-by-step instructions on how to extract data into Excel for further analysis. If you're already familiar with web scraping and are eager to learn how to handle data specifically in Excel, feel free to jump straight to this section.

What is web scraping?

Web scraping involves extracting unstructured data from websites and converting it into a structured format that can be used for various purposes, such as analysis, research, or training AI models. This process is essential for efficiently gathering and organizing data from the vast array of information available online.

There are different ways in which people scrape data from websites to excel. While manually copying and pasting data from a website into Excel might seem like a quick solution, it mostly results in poorly formatted data and significant time spent on cleanup. Web scraping tools offer a more efficient alternative by automating the extraction and formatting of data directly into Excel. These tools can transform unstructured website content into a well-organised Excel format. In fact, excel has it's own in built methods to import data from a website.

In this blog, we’ll explore several methods for scraping data from a website to Excel. Whether you're looking for simple tools or more advanced solutions, we'll cover various methods to help you scrape data from a webpage and store it as an excel.

Looking to scrape data from websites? Try Nanonets™ Website Scraping Tool for free and quickly scrape data from any website.

How to scrape data from a website to Excel?

This blog will explore five ways to answer the question, 'How to scrape data from a website to Excel?' What is the best way out of these? Well this actually depends on what kind of use case you have, and the website you want to scrape data from.

Let's deep dive into the ways to scrape data from a website to Excel.

• Manually copy and paste data from a website to Excel
• Using an automated web scraping tool
• Using Excel VBA
• Using Excel Power Queries
• Web scraping with Python

1. Manually copy and paste data from a website to Excel

This is the most commonly used method to scrape data from a website to Excel. While this method is the simplest, it is also the most time-consuming and error-prone. The scraped data is often unstructured and difficult to process. 

This method is best for a one-time use case. However, it is not feasible when web scraping is to be done for multiple websites or at regular intervals.

2. Using an automated web scraping tools

If you want to scrap data from a website to Excel automatically and instantly, try a no-code tool like Nanonets website to excel scraper. This free excel web scraping tool can instantly scrape website data and convert it into an Excel sheets.

Here are three steps to scrape website data to Excel automatically using an automated tool:

Step 1: Head to Nanonets' website scraping tool and insert your URL.
Step 2. Click on 'Scrape and Download'.
Step 3: Once done, the tool downloads the Excel file with the scraped website data automatically.

Scrape data from Websites to Excel with Nanonets™ Website Scraping Tool for free.

3. Using Excel Power Queries

Excel power queries can scrape website data easily. It imports web pages as text files into Excel. Let’s see how to use Excel Power Query to scrape web pages in Excel.

Step 1: Create a new Workbook.
Step 2: On the home screen, select New, and search for ‘Power Query’ in the search bar.
Step 3: Open the Power Query tutorial and press Create.
Step 4: Click on Data > Get & Transform > From Web.
Step 5: Paste the URL that you want to scrape into the text box and click OK.
Step 6: Under Display Options in the Navigator Pane, select the Results table. Power Query will preview it in the Table View pane on the right.
Step 7: Click on Load. Power query will transform and load the data as an Excel table.
Step 8: To refresh the data, right-click on the data in the worksheet and select "Refresh."

What are the drawbacks of using Excel Power query to extract webpage data to Excel?

• Power queries can’t scrape data from dynamic webpages or webpages with complex HTML structures.
• Power queries can extract unformatted data. For example, data may be extracted as text instead of a number or date.
• Power queries rely on the webpage's HTML structure. If it changes, the query may fail or extract incorrect data.

Well you could do it all on your own, or you could just schedule a call with us and we could help you all your webpage to excel workflows. Schedule a Demo now!

4. Using Excel VBA

Excel VBA is powerful and can easily automate complex tasks, such as website scraping to Excel. Let’s see how to use it to scrape a website to Excel.

Step 1: Open Excel and create a new workbook.
Step 2: Open the Visual Basic Editor (VBE) by pressing Alt + F11.
Step 3: In the VBE, go to Insert -> Module to create a new module.
Step 4: Copy and paste the following code into the module:

Sub ScrapeWebsite()
'Declare variables
Dim objHTTP As New WinHttp.WinHttpRequest
Dim htmlDoc As New HTMLDocument
Dim htmlElement As IHTMLElement
Dim i As Integer
Dim url As String
'Set the URL to be scraped
url = "https://www.example.com"
'Make a request to the URL
objHTTP.Open "GET", url, False
objHTTP.send
'Parse the HTML response
htmlDoc.body.innerHTML = objHTTP.responseText
'Loop through the HTML elements and extract data
For Each htmlElement In htmlDoc.getElementsByTagName("td")
'Do something with the data, e.g. print it to the Immediate window
Debug.Print htmlElement.innerText
Next htmlElement
End Sub

Step 5: Modify the URL in the code to the website you want to scrape in the Excel workbook.
Step 6: Run the macro by pressing F5 or clicking the "Run" button in the VBE toolbar.
Step 7: Check the Immediate window (View -> Immediate Window) to see the scraped data.

The website data should have been scraped into the Excel workbook.

Tips

• Ensure Internet Explorer is installed on your computer, as VBA uses IE for web scraping.
• Modify the code to extract specific data elements based on your needs.

What should you consider while using VBA to scrape data from a webpage?

While Excel VBA is a potent tool for web scraping, there are several drawbacks to consider:

• Complexity: VBA can be complex for non-coders. This makes it difficult to troubleshoot issues.
• Limited features: VBA can extract limited data types. It can’t extract data from complex HTML structures.
• Speed: Excel VBA can be slow while scraping large websites.
• IP Blocking Risks: There is always a risk of IP getting blocked when scraping large data websites.

Looking to scrape data from websites? Try Nanonets™ Website Scraping Tool for free and quickly scrape data from any website.

5.  Scrape websites using Python

Web scraping with Python is popular owing to the abundance of third-party libraries that can scrape complex HTML structures, parse text, and interact with HTML form. Some popular Python web scraping libraries are listed below - 

• Urllib3 is a powerful HTTP client library for Python. This makes it easy to perform HTTP requests programmatically. It handles HTTP headers, retries, redirects, and other low-level details, making it an excellent library for web scraping.
• BeautifulSoup allows you to parse HTML and XML documents. Using API, you can easily navigate through the HTML document tree and extract tags, meta titles, attributes, text, and other content. BeautifulSoup is also known for its robust error handling.
• MechanicalSoup automates the interaction between a web browser and a website efficiently. It provides a high-level API for web scraping that simulates human behavior. With MechanicalSoup, you can interact with HTML forms, click buttons, and interact with elements like a real user.
• Requests is a simple yet powerful Python library for making HTTP requests. It is designed to be easy to use and intuitive, with a clean and consistent API. With Requests, you can easily send GET and POST requests, and handle cookies, authentication, and other HTTP features. It is also widely used in web scraping due to its simplicity and ease of use.
• Selenium allows you to automate web browsers such as Chrome, Firefox, and Safari and simulate human interaction with websites. You can click buttons, fill out forms, scroll pages, and perform other actions. It is also used for testing web applications and automating repetitive tasks.

Pandas allow storing and manipulating data in various formats, including CSV, Excel, JSON, and SQL databases. Using Pandas, you can easily clean, transform, and analyze data extracted from websites.

For more advanced methods of data extraction and to enhance your scraping capabilities, consider learning about Retrieval-Augmented Generation (RAG) and its role in improving data workflows. Additionally, if you're interested in the underlying technologies that can support your web scraping efforts, check out our blog on Large Language Models (LLMs).

Automating webpage to excel scraping

Excel tools like VBA and web query can extract webpage data, but they often fail for complex webpage structures or might not be the best choice if you have to extract multiple pages daily. Pasting the URL, checking the extracted data, cleaning it, and storing it requires a lot of manual effort, particularly when this web scraping task must be repeated regularly.

Platforms like Nanonets can help you automate the entire process in a few clicks. You can upload the list of URLs into the platform. Nanonets can save you a significant amount of time by automating the following steps:

• Extracting Data from Webpages: Nanonets can handle Excel web scraping by extracting data from any webpage, including those with complex HTML structures or headless webpages, and convert it directly into an Excel-compatible format.
• Structuring the Data: Nanonets identifies HTML structures and formats the data, retaining table layouts, fonts, and other formatting elements, ensuring that the data is well-organized when imported into Excel, effectively performing web scraping to Excel.
• Data Cleaning: Nanonets can automatically handle tasks like replacing missing data points, formatting dates, and replacing currency symbols, ensuring that the data is clean and consistent when it reaches Excel. This makes the webpage to Excel process smooth and efficient.
• Exporting Data to Excel: You can easily export the extracted and cleaned data into Excel, as well as other platforms like Google Sheets, SharePoint, CRM systems, or any other database of your choice. This makes the website to Excel data transfer seamless.

If you have any requirements, you can contact our team, who will help you set up automated workflows to automate every part of the web scraping process.

Automate manual processes using Nanonets AI-based OCR software. Capture data from documents instantly. Reduce turnaround times and eliminate manual effort.

Use cases for web scraping

Web scraping has many use cases across teams and industries. Some common use cases are -

• Competitor research - Businesses scrape competitor websites to compare product offerings and monitor prices. Web scraping for market research is a good way for organizations to get to know the pulse of the market.
• Lead generation - Generating high-quality leads is extremely important to growing a business. Web scraping for lead generation is a good way to gather potential lead contact information – such as email addresses and phone numbers.
• Search Engine Optimization - Scraping webpages to monitor keyword rankings and analyze competitors' SEO strategies.
• Sentiment analysis - Most online businesses scrape review sites and social media platforms to understand what customers are talking about and how they feel about their products and services.
• Legal and compliance. Companies scrape websites to ensure their content is not being used without permission or to monitor for counterfeit products.
• Real estate markets - Monitoring property listings and prices is crucial for real estate businesses to stay competitive.
• Integrations - Most applications use data that needs to be extracted from a website. Developers scrape websites to integrate this data into such applications, for example, scraping website data to train LLM models for AI development.

Is web scraping legal?

While web scraping itself isn't illegal, especially for publicly available data on a website, it's important to tread carefully to avoid legal and ethical issues. 

The key is respecting the website's rules. Their terms of service (TOS) and robots.txt file might restrict scraping altogether or outline acceptable practices, like how often you can request data to avoid overwhelming their servers. Additionally, certain types of data are off-limits, such as copyrighted content or personal information without someone's consent. Data scraping regulations like GDPR (Europe) and CCPA (California) add another layer of complexity. 

Finally, web scraping for malicious purposes like stealing login credentials or disrupting a website is a clear no-go. By following these guidelines, you can ensure your web scraping activities are both legal and ethical.

Eliminate bottlenecks caused by manually scraping data from websites. Find out how Nanonets can help you scrape data from websites automatically.

Conclusion

Scraping data from websites to excel does not have to be as daunting of a task as we make it seem like. With the right tools and techniques, we can automate this task which helps save time also ensures accuracy. Whether you're a data analyst, researcher, or business professional, learning how to extract data from websites to Excel can significantly enhance your workflow.

By following the steps outlined in this guide, you now know how to extract data from a website to Excel automatically, making data collection more efficient and reliable. This knowledge opens up a world of possibilities, from tracking market trends to compiling research data, all within the familiar environment of an Excel spreadsheet.

Remember, mastering how to extract data from websites to Excel not only boosts productivity but also empowers you to make data-driven decisions with confidence. As you continue to explore and refine your data scraping techniques, you'll find new and innovative ways to leverage this skill in your daily tasks.

Schedule a call with our team to learn more about how Nanonets can help you optimize your data extraction workflows. Let us show you how to extract data from websites to Excel in the most efficient and effective way possible.