How to Indentify Anchor Text Overlaps Using Python in Google Colab
Managing anchor texts across a website can be a daunting task. However, with a bit of Python and Google Colab, we can create a simple script to identify overlaps in anchor texts. The code was generated with ChatGPT and then reviewed and used by me.
How to Use the Code
The Python script we’re discussing requires a CSV file with four specific columns: ‘Source’, ‘Destination’, ‘Anchor’, and ‘Link Path’. This file can be easily generated using SEO tools like Screaming Frog or another Python script.
To use the script, follow these steps:
- Open Google Colab and paste the Python script into a new notebook.
- Click the ‘Upload’ button in Google Colab to upload your CSV file.
- Run the script. It will read the CSV file, convert the ‘Anchor’ column to lowercase, and group the data by the ‘Anchor’ column.
- The script identifies instances where the same anchor text links to different ‘Destination’ URLs. These instances are saved in a new CSV file and automatically downloaded to your computer.
Why Is It Useful?
Identifying overlaps in anchor text is an important aspect of SEO. Using the same anchor text for different destination URLs can confuse search engines and dilute SEO impact. This script saves time and effort by automating the detection of these overlaps.
What’s Next?
Once you’ve identified anchor overlaps, you can take steps to rectify them and improve your website’s SEO. Consider revising the anchor text for clarity and to better match the destination content.
Python and Google Colab offer many more possibilities for SEO analysis. By automating tedious tasks, you can focus more on strategy and content creation.
See my previous post on how to transform YouTube timestamps into JSON-LD VideoObject Clips with Python.
