Curated Python resources for data engineers: core language, data manipulation, scripting patterns, and the libraries that show up in every pipeline.
The canonical reference. Chapters 4-9 cover everything you need: control flow, data structures, modules, I/O, and errors. Read these before any course.
Free online. The definitive book on pandas from its creator. Part II on data wrangling is required reading for any data engineer.
Clear, practical tutorials with runnable examples. Good for filling gaps in string handling, dicts, and list comprehensions.
Understanding how packages work -- virtual environments, pyproject.toml, uv -- prevents the dependency chaos that wastes days.
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New resources and perspective on building AI-ready data systems, a few times a month. No spam.