Project 2: Multi‑Week Weather Analyzer

Overview

This project extends the work you did in Project 1 by analyzing multiple weeks of temperature data. Instead of a single 7‑day dataset, you will process four weeks of weather information, compute broader trends, and generate a comparative report.

This follow‑up project helps you practice loops, nested structures, functions, and organizing a larger program.

Learning Objectives

This project assesses your ability to:

• Use variables and data collections effectively (Outcome 1)
• Apply conditionals in multi‑step decision making (Outcome 2)
• Use nested loops to analyze multi‑dimensional data (Outcome 3)
• Write and call functions to organize code (Outcome 4)
• Break down a complex problem into manageable parts (Outcome 6)

Dataset

You are given temperatures for 4 weeks (28 days total). Each week includes a list of 7 daily high temperatures:

weeks = [
    [72, 68, 75, 80, 77, 71, 69],
    [70, 67, 74, 78, 76, 73, 71],
    [69, 65, 72, 77, 79, 74, 70],
    [73, 70, 76, 82, 78, 75, 72]
]

days = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]

Copy this into your program.

Requirements

Functional Requirements

Your program must:

1. Compute the average temperature per week
2. Compute the overall average across all 28 days
3. Find the hottest day overall (temperature + week + day name)
4. Find the coolest day overall
5. For each week, count how many days are Hot (>75), Mild (70‑75), and Cool (<70)
6. Generate a formatted report showing:
   • Weekly averages
   • Overall average
   • Hottest & coolest days
   • Weekly category counts

Technical Requirements

Your code must:

• Use nested loops to process weeks and days
• Include at least two functions (e.g., compute_week_average, classify_temperature)
• Use meaningful variable names
• Include comments explaining your approach
• Run without errors

Getting Started

Suggested Approach

1. Process one week first: compute its average
2. Add classification for each day
3. Track extremes while looping through all weeks
4. Create functions for reusable steps
5. Build the final report

Example

Sample Output (abbreviated):

=== Multi‑Week Weather Report ===

Week 1 Average: 73.1°F
Week 2 Average: 72.7°F
Week 3 Average: 72.3°F
Week 4 Average: 75.1°F

Overall Average: 73.3°F
Hottest Day: 82°F (Week 4, Thursday)
Coolest Day: 65°F (Week 3, Tuesday)

Weekly Categories:
- Week 1: Hot 2 | Mild 3 | Cool 2
- Week 2: Hot 1 | Mild 4 | Cool 2
- Week 3: Hot 2 | Mild 3 | Cool 2
- Week 4: Hot 2 | Mild 4 | Cool 1

Rubric

See project-2.rubric.md for detailed grading criteria.

Grading Summary

Submission

1. Name your file multiweek_weather.py
2. Push to your GitHub repository by Week 7
3. Verify your code runs without errors

Academic Integrity

• You may discuss ideas but must write your own code
• No copying code from the internet or classmates
• AI tools may help you understand but not write the program

Getting Help

• Start early
• Come to office hours
• Use the discussion forum for conceptual questions