Case Studies

Note

Source: Python-specific — no equivalent in the C# edition.

Case studies show how the concepts in this book apply to real problems. Each study starts from data or a situation you might actually encounter, then builds a complete solution using the tools you have learned — loops, functions, data structures, files, and more.

Working through a case study is different from working through a textbook exercise. The problem is not pre-cleaned or pre-scoped. You will need to read data, explore it, decide what questions to ask, and write code that produces a meaningful result. That process — messy and iterative — is what programming in practice looks like.

• Case Study: Monte Carlo Simulation
  • The Setup
  • Step 1 — Generate the Darts
  • Step 2 — Save the Darts to a File
  • Step 3 — Load the Darts from a File
  • Step 4 — Estimate π
  • Step 5 — Measure Convergence
  • Step 6 — Visualize
  • Where the Method Is Used
  • Challenges
• Case Study: Chicago 311 Graffiti Data
  • Step 1 — Fetch
  • Step 2 — Load and Inspect
  • Step 3 — Aggregate
  • Step 4 — Filter
  • Step 5 — Visualize
  • What the Data Reveals
  • Challenges