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Tutorials
Tutorials
Practical, hands-on tutorials and how-to guides on Python, Pandas, NumPy, SQL, and setting up your data-science environment.
scikit-learn Overview: One fit/predict API for Every Model
A wider tour of scikit-learn than one worked example can give you: the shared fit/predict/transform pattern behind every estimator, a classifier and a preprocessing transformer side by side, and how Pipeline chains them into one reusable object.
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SQL
SQL Triggers: A Practical Guide to Event, Timing, Action
A trigger is code the database runs for you, automatically, whenever a row changes. This guide builds the event-timing-action mental model, then works through BEFORE and AFTER triggers, an audit log, and the traps that catch people the first time, all in SQLite.
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Python
Text Classification with spaCy: A Practical Beginner's Guide
Build a working spam/ham text classifier with spaCy's TextCategorizer, from a blank pipeline through a real training loop to a proper precision/recall evaluation on held-out messages.
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Python
Web Scraping with Scrapy: Building a Spider from Scratch
A hands-on walkthrough of Scrapy's core pieces — spiders, selectors, Items, and pipelines — building a small price-watch project against a real practice site, one runnable step at a time.
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Python
Your First Machine Learning Model: A Hands-On scikit-learn Tutorial
A complete first pass at supervised learning: explore a real health dataset with pandas, chart a relationship with matplotlib, split it honestly, and train and grade a scikit-learn regression model.
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Python
Pandas GroupBy: A Practical Guide to Split, Apply, Combine
Every 'per-group' question in Pandas goes through groupby. This guide builds the split-apply-combine mental model, then works through agg, named aggregations, multi-column grouping, transform, and filter on a small dataset you can regenerate yourself.
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Python
Python's match Statement: Cleaner Code with Structural Pattern Matching
The match statement is one of Python's most underused features. See how it replaces messy if/elif chains and, more importantly, how structural pattern matching lets you match the shape of your data and pull out the parts you need.
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Python
Managing Python Projects with Poetry: A Practical Guide
Outgrown venv and requirements.txt? Poetry handles dependencies, virtual environments, lockfiles, and packaging from a single pyproject.toml. A practical, end-to-end guide with real commands.
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SQL
Loading CSV Data into PostgreSQL: COPY vs INSERT, Benchmarked
Connecting to Postgres from Python is the easy part. This guide builds a table with psycopg2, loads a CSV row by row and then in bulk with COPY, and measures the real speed difference between them on 8,000 rows.
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Python
Fast, All-in-One Python Project Management with uv
uv is a single, blazing-fast tool that handles virtual environments, dependencies, lockfiles, Python versions, and packaging. A practical guide to the toolchain replacing pip, venv, and pyenv.
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