*Python for SEO vs. Data Science for SEO*
What’s the difference?
When you learn the tool (Python) you learn the how.
When you learn the discipline (Data Science) you learn the what and the why.
If you decide to learn Photoshop (the tool) instead of graphic design (the discipline), one of the things you learn is how to change the color of a piece of text for example.
Click here, click there, choose a color, enter a number, done.
If you get into graphic design, you learn about what colors you should/could use and why.
Is it a printed brochure, are there brand guidelines, what color is the logo, is it medical, or is it for teens? Do you sell bags, or vacations and trips? Is it a landing page for a campaign or a product page…
As you can see, the how is straightforward, has a clear set of steps, and generally easy to learn.
The what and the why are not easy questions, they don’t have straightforward answers/solutions, and are therefore important and difficult considerations.
I can learn how to use Photoshop in a month, but that won’t make me a graphic designer.
Graphic Design -> Photoshop
Data Science -> Python
???? Data Visualization (numeric vs categorical variables, color scales, distributions, counts,...) -> plotly, matplotlib, bokeh, altair…
???? Data manipulation (sorting, pivot tables, subsetting, merging, regex...) -> pandas
???? Machine learning (supervised/unsupervised, classification, regressions,...) -> scikit-learn
???? Crawling (custom extraction, proxy servers, following links behavior, redirects, website/content analysis...) -> advertools
???? Log file analysis (URL analysis, reverse DNS lookup, status codes, user-agent parsing...) -> advertools
???? XML sitemaps (URL analysis, content analysis, publishing trends, ...) -> advertools
etc…
Happy Friday