Why Python, and which quarter of it
The parts of the language data work actually uses, and permission to ignore the rest for now.
Python is a general-purpose language. Most of it exists for building web servers, games, desktop applications and operating-system tooling — none of which you are here for.
Data work uses a surprisingly small slice, and you can be productive in it long before you have seen the rest.
What you actually need
- Values and variables. Numbers, text,
True/False, and giving them names. - Lists and dictionaries. An ordered pile of things, and a set of labelled things. Nearly every data structure you meet is one of these wearing a costume.
- Loops. Doing something once per item.
- Functions. Naming a piece of work so you can do it again without copying it.
- Imports. Borrowing someone else's code, which is most of what data work is.
That is this module. Five ideas.
What you can put off
Classes, decorators, generators, async, type hints, packaging, virtual environment theory. All of them are real and some become useful later. None of them are between you and reading a CSV.
If a tutorial opens with class Animal: and inheritance, it is teaching you
software engineering. That is a fine thing to learn, but it is not the shortest
path to answering a question with a table.
The one habit worth forming now
Run the code. Not read it — run it, change a number, run it again, and predict what will happen before you press enter.
Everyone who is good at this got there by being wrong in small, cheap ways thousands of times. The gap between people who learn quickly and people who stall is almost never intelligence; it is how often they actually execute something.