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Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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DAX Variables: Writing Cleaner, Faster Measures
DAX variables explained with real numbers: VAR and RETURN syntax and naming rules, how variables speed up and simplify measures, debugging by returning a variable, the rule that a variable is fixed where it is declared, shown producing a 100% share by mistake, and replacing EARLIER in a ranking column.
Python Best Practices: Writing Pythonic Code
What "Pythonic" means in practice, as before-and-after pairs you can run: looping with enumerate and zip, unpacking, dictionary and Counter idioms, building strings, checking None and emptiness, handling files, plus naming, function design and the formatter, linter and type checker that keep code consistent.
Python Type Hints: Writing Cleaner, Safer Code
What Python type hints do and do not do, shown on a small module with three hidden bugs that mypy finds before the code runs: annotating functions and variables, None and union types, generic collections, dataclasses, narrowing, and how to add hints gradually to an existing codebase.
Reading and Writing CSV Files in Python
CSV looks simple until a field contains a comma, a line break or a hidden byte-order mark. Reading and writing real-world CSV with Python's csv module: why splitting on commas fails, DictReader and DictWriter, utf-8-sig, semicolon files, types, large files, and when pandas is better.