Download keyword list from the Google Search Console in CSV format. Set the number of rows per page towards the end of the page and then change the order of Position based on lowest to highest. Now the heighest position will be at the top. Download the CSV file to your local system.
Read the csv file by using read_csv(), by using the column Top Queries we will create one new dataframe (df2).
While creating the dataframe we will use str to create string, then split the string and use stack. Finally we will use value_count() to create a list of key words with the frequency of their occurrence.
We are storing the final key word list with the frequency of occurrence using CSV file using to_csv(). This gives us the list of words which are as per google have relatively better authoritativeness ( Part of E-A-T : expertise authoritativeness and trustworthiness).
import pandas as pd # importing pandas
df = pd.read_csv("H:\\data\\seo\\query-rank.csv") # reading csv file
df2 = df["Top queries"].str.split(expand=True).stack().value_counts()
print(df2.head(15)) # printing top 15 keywords
df2.to_csv("H:\\data\\seo\\to_words.csv") # saving to csv file