Visualizing Google Core Update Winners & Losers With Python - Search Engine Journal

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For SEO experts, Google’s core updates are a way of life. They will happen at least once – if not multiple times – a year.

Naturally, there will be winners and losers.

So while Google doesn’t disclose most of the ranking factors behind the algorithm updates, there are things we can do to get a greater understanding of what’s going on, in terms of:

• Which site content is affected.
• Sites operating in your search space.
• Result types.

The limit is your imagination, your questions (based on your SEO knowledge), and of course, your data.

This code will cover aggregations at the search engine results page (SERP) level (inter-site category comparison), and the same principles can be applied to other views of the core update such as result types (think snippets and other views mentioned above).

Using Python To Compare SERPs

The overall principle is to compare the SERPs before and after the core update, which will give us some clues as to what’s going on.

We’ll start by importing our Python libraries:

import re import time import random import pandas as pd import numpy as np import datetime from datetime import timedelta from plotnine import * import matplotlib.pyplot as plt from pandas.api.types import is_string_dtype from pandas.api.types import is_numeric_dtype import uritools...

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