Page rank is an algorithm by Google search for ranking websites in their SERP (Search Engine Results Page). It was named after Larry Page. It measures the importance of a website page. This blog will talk about how to implement this algo in python for data science.
It was the first algorithm there by Google, and after this, many other algorithms have been there by Google.
PR algorithm will output a probability distribution there for representing the likelihood of a person randomly clicking on links will arrive at a page. PR can be there for the collection of documents of all sizes. The PR requires several passes known as iterations through collections for adjusting approximate Page Rank values more reflecting the theoretical value more closely.
The code for calculating the Page rank is as follows.
For the implementation of the above code in the network, we have to use the following code.