🚀 Week 1 — Python for Data Engineering

Welcome! 🎉🎉🎉

This repository contains everything you need for Week 1 of the Data Engineering program: development environment setup, Bash/VS Code/Jupyter intros, Git + GitHub workflows, Python practice (Basics → Intermediate → Advanced), and a Pandas primer.

---

🎯 What You Will Learn This Week

• 🛠 Tooling: Bash, VS Code, Jupyter, Google Colab
• 🌱 Version control: Git + GitHub (clone, branch, commit, PR)
• 🐍 Python: Core syntax & flow, data structures, functions, error handling, iterators/generators, Object-oriented Programming concepts and performance tips
• 📊 Pandas: Series/DataFrame basics, transforms, visualization

---

📂 Folder Map

• 01_installation_setup/ [Time Allocation - 2nd half of Day 1]
  • setup_for_linux/ — Linux install guides (uv, Python, Bash, Docker, Git, VS Code, PostgreSQL/pgAdmin, Jupyter). 🐧
  • setup_for_mac/ — macOS install guides (Homebrew, uv, Python, Bash, Docker, Git, VS Code, PostgreSQL/pgAdmin, Jupyter). 🍎
  • setup_for_windows/ — Windows install guides (uv, Python, Git, Bash, Docker, Git, VS Code, PostgreSQL/pgAdmin, Jupyter). 🪟
• 02_bash_jupyter_vscode_colab_intro/
  • bash.md — Bash intro + practice game (Bandit). 🔹
  • vscode.md — VS Code essentials for this course. ✨
  • jupyter.md — Jupyter Notebook/Lab walkthrough. 📓
  • colab.md — Using Google Colab. ☁️
• 03_git_github/
  • git_github_intro.md — class workflow: fork/clone, feature branches, commits, PRs, resolving simple conflicts. 🧩
• 04_python_practice/
  • python_basics/ — notebooks + exercise folder: 🐍
    • Numeric variable types, Strings, If/Elif/Else, Loops
    • Lists, Sets, Mutability, Dictionaries, Comprehensions
    • Functions (intro/definitions/calling/challenge)
    • Each student notebook has TODOs and assert tests.
  • python_intermediate/ — notebooks + exercise folder: ⚡
    • Error handling, Iterators & Generators, Lambda/Map/Filter/Reduce, Performance.
  • python_advanced/ — notebooks + exercise folder: 🚀
    • OOP introduction, Concurrency & Parallelism.
• 05_pandas_intro/
  • 01_pandas.ipynb → foundations (Series/DataFrame, indexing, I/O). 📊
  • 02_pandas_practice_1.ipynb, 04_pandas_practice_2.ipynb, 05_pandas_practice_3.ipynb → progressively harder practice.
  • 03_pandas_visualization.ipynb → quick plotting. 📈
  • data/ — sample CSVs/parquet used by the notebooks. Don't move/rename. 🗂️

---

✨ Ready to dive in? Your Python + Pandas journey starts here! 🐍💻📊

---