Python Data Analysis in Practice

What you will achieve

Automate Excel/CSV with Pandas, scrape web data, produce shareable charts, package as reproducible Jupyter notebooks

Syllabus

• 1
  Python Env & Jupyter

  venv, pip, Jupyter Lab, VS Code

• 2
  NumPy Vectorization

  ndarray, broadcasting, perf comparison

• 3
  Pandas Basics

  Series, DataFrame, indexing

• 4
  Pandas Advanced

  groupby, pivot, merge, apply

• 5
  Data Cleaning

  Missing data, type conversion, dedup, outliers

• 6
  Visualization

  Matplotlib, Seaborn, Plotly

• 7
  Web Scraping

  requests, BeautifulSoup, Playwright

• 8
  API Integration

  REST API, auth, rate limit, retry

• 9
  Pipeline Automation

  Scheduling, logging, error alerts

• 10
  Capstone

  Sales dashboard / stock backtest / social sentiment

Highlights

• Cut Excel hours by more than half
• Capstone is workplace-ready
• 30+ Pandas operations cheat sheet included

Instructor

Hi, I'm Morld's founder — a full-time engineer and amateur fitness enthusiast. I've been writing code for 10+ years; my primary stack is JavaScript / TypeScript / React + Cloud Run / GCP deployments, with C# / .NET, Docker, and DevOps as secondary specialties. My 1-on-1 teaching style is: first understand the outcome you want, then design the chapter order and pace to reach it. Each lesson ends with homework; the next starts with a 5-minute review.