Python for Data
The Python that data work actually uses — reading files, cleaning columns, and the small set of libraries you will meet every day.
Most Python courses teach the language and hope you find the data part later. This one goes the other way: every topic exists because you cannot clean a real dataset without it.
If you have done the SQL course, much of the middle of this will feel familiar — grouping and joining are the same ideas wearing different syntax. That is deliberate, and it is the fastest way to learn both.
Every lesson is free and needs no sign-up.
Syllabus
The language, briefly
Variables, lists, dictionaries, loops and functions — the quarter of Python that data work leans on.
Tables in memory
Reading a CSV, looking at what you loaded, and selecting rows and columns without guessing.
Cleaning
Missing values, wrong types, duplicated rows, and dates that arrived as text.
Grouping and reshaping
Group-by, joins between tables, and pivoting — the same ideas as SQL, in a different notation.
Charts that answer a question
Plotting to find something out, not to decorate a report.
Working in a Databricks notebook
Moving the same code onto a cluster, and what changes when the table no longer fits on your laptop.