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Python for SEO 102 (Advanced)
Introduction
Intro
Intro to Colab
Dictionaries & Lists
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Dictionaries and lists intro
Nested lists
List comprehension
Dictionaries basics
Adding information to dictionaries or overwriting it
End of dictionaries and lists
Error handling
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Simple try except
Handling errors better
Error catching finally
APIs
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Introduction - what are APIs?
APIs hands-on
Setting up GSC API authorisation
Authorising with Search Console API and our first request
Requesting keyword data and working with it
GSC wrapping everything into an easy function
Getting more data out of search console - row limits and filters
Available filters and dimensions and usage limits
Grouping search console data
Google Sheets API - pulling and changing information
Google Sheets API - dataframes and Google Sheets
API wrap up
Requests
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Direct requests intro
Requests library simple requests
Extracting information with beautifulsoup
Pandas to extract tables
Selenium to move around web pages
Manually working with APIs with requests
Advanced work with Pandas
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Pandas advanced intro
Pandas merge 1
Pandas merge outer
Pandas merge left and right
Merge handling duplicates
Pandas pivot
Pandas Melt
Pandas apply introduction
Pandas apply for categorising keywords
Seaborn bar chart
Seaborn scatter charts
Plotly interactive
Pandas advanced wrap up
Local files
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Introduction to working with local files
os making and deleting folders
os creating whole paths
Glob
Reading and writing text files
Pickle
Files wrap up
Analysis methods
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Analysis methods introduction
NLP introduction
NLP Stemming
NLP - Lemmatisation
NLP - what are ngrams
NLP - counting ngrams
NLP - counting ngrams across a list
NLP - returning ngrams for list
NLP - wrap up of ngrams, stemming, and lemmatisation
NLP - entity extraction
Scikit learn
Forecasting
Trying to estimate impact - causal impact
Trying to estimate impact - actual estimations
Trying to estimate impact - making estimates more accurate
Analysis methods conclusion
Running code in the cloud
Running code in the cloud - intro and platforms
Cloud functions - initial settings
Writing code in Google Cloud
Code after you deployed
Cloud scheduling
Cloud functions pricing
Running code in the cloud conclusion
Keyword categorisation
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Different keyword categorisation introduction
Different keyword categorisation - preparing our data
Different keyword categorisation - extracting data from a dataframe into a dictionary
Different keyword categorisation - Comparing similarities of url lists
Different keyword categorisation: finding best overlap
Different keyword categorisation: adding data to google sheets
Conclusion
Conclusion
Trying to estimate impact - actual estimations
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