Advanced Web Scraping with Power Query: How to Extract Data from Multiple Pages

Web scraping is an essential skill for data analysts who need to collect information from websites for their analysis. While many believe that Power Query can only handle basic table extraction, it actually offers powerful capabilities for scraping multi-page websites and dynamic content.

Understanding Basic Web Scraping in Power Query

The basic approach to web scraping in Power Query involves extracting data from static web pages that contain tables. This is done through the ‘Get Data from Web’ feature, where you can easily select tables from a webpage. However, this method has limitations when dealing with complex websites or multiple pages.

Authentication Options for Web Connections

When connecting to websites, Power Query offers several authentication options:

• Anonymous: For public websites that don’t require sign-in
• Windows: For local servers that require your PC credentials
• Organizational account: For SharePoint or other organization-specific resources
• Web API: For sites requiring API tokens or developer credentials

Advanced Scraping: E-commerce Product Data

The real power of Power Query emerges when scraping complex, multi-page websites like e-commerce platforms. By understanding HTML structure and inspecting web elements, you can target specific data points within containers and divs on the page.

Key steps in the advanced scraping process include:

1. Analyzing the URL structure to understand how pagination works
2. Using browser inspection tools to identify HTML elements containing desired data
3. Creating a function in Power Query that can handle page parameters
4. Implementing the function across multiple pages

Creating a Multi-Page Scraping Solution

The most efficient approach to scraping multiple pages involves:

1. Developing and testing your transformation steps on a single page first
2. Converting your query into a function that accepts page numbers as parameters
3. Creating a list of page numbers to scrape
4. Applying your function to each page number in the list

This method allows you to extract data from multiple pages while maintaining performance. By minimizing transformation steps and optimizing your query, you can scrape hundreds of products across multiple pages efficiently.

Data Validation and Cleaning

After scraping, it’s important to validate your data by comparing samples against the original website. Clean your data by:

• Renaming columns to meaningful names
• Removing unnecessary columns
• Splitting text where needed
• Converting data types appropriately

The result is a comprehensive dataset ready for analysis, containing product details such as names, prices, companies, minimum quantities, and discounts – all extracted automatically across multiple pages.

Performance Considerations

When scraping multiple pages, performance becomes critical. The approach outlined above optimizes performance by:

• Finalizing all transformation steps on a single page before scaling
• Minimizing the number of transformation steps
• Converting data types efficiently
• Using functions to reuse logic across pages

This technique enables you to extract large amounts of data without overwhelming your system’s resources.