Python In 30 Days - Day 10

Day ten was about reading and writing CSV files, plus some extra work around sorting dictionaries by values. I’ll say again, dictionaries can be so confusing! Glad I got to work through it though.

The Challenge:

You’re building a menu management system using CSV files:

1. Write a function save_menu_to_csv(menu, filename) that:

• Takes a dictionary like your restaurant menu and writes it to a CSV
• The CSV should have two columns: item and price
• Includes the header row

2. Write a function load_menu_from_csv(filename) that:

• Reads the CSV back in
• Returns a proper Python dictionary {"item": price} with prices as integers
• Handles FileNotFoundError gracefully

3. Write a function analyze_menu(menu) that returns a dictionary containing:

• "most_expensive": name of the priciest item
• "cheapest": name of the cheapest item
• "average_price": average price rounded to 2 decimal places
• "items_by_price": the full menu sorted from most to least expensive, as a list of "Item - $X" strings

4. Save your restaurant menu to CSV, load it back into a fresh dictionary, run it through analyze_menu, and print the results cleanly

Things to figure out: how to iterate over a dictionary’s items to write rows, how to sort a dictionary by its values, and how to find the max and min by value in a dictionary.

My Code:

import csv
import json

menu = [
    {"item": "Burger", "price": 15},
    {"item": "Fries", "price": 9},
    {"item": "Brownie", "price": 7},
    {"item": "Soft Drink", "price": 4},
]


def save_menu_csv(menu, filename):
    with open(f"{filename}", "w", newline="") as f:
        writer = csv.DictWriter(f, fieldnames=["item", "price"])
        writer.writeheader()
        writer.writerows(menu)
        print(f"Data saved to {filename}\n")


def load_menu_csv(filename):
    try:
        with open(f"{filename}", "r") as f:
            reader = csv.DictReader(f)

            new_menu = {row["item"]: row["price"] for row in reader}
            menu = {k: int(v) for k, v in new_menu.items()}
        print(f"{filename} loaded and parsed!\n")
        return menu
    except FileNotFoundError:
        print(f"{filename} not found!")


def analyze_menu(menu):
    largest = max(menu, key=menu.get)
    smallest = min(menu, key=menu.get)
    average = round(sum(menu.values()) / len(menu), 2)
    sort = sorted(menu.items(), key=lambda item: item[1], reverse=True)
    formatted = [f"{k} - ${v}" for k, v in sort]

    analyzed = {
        "most_expensive": largest,
        "cheapest": smallest,
        "average_price": average,
        "items_by_price": formatted,
    }

    final = json.dumps(analyzed, indent=4)
    return final


save_menu_csv(menu, "burgerjoint.csv")
printout = analyze_menu(load_menu_csv("burgerjoint.csv"))
print(printout)

\

Running The Code:

Data saved to burgerjoint.csv

burgerjoint.csv loaded and parsed!

{
    "most_expensive": "Burger",
    "cheapest": "Soft Drink",
    "average_price": 8.75,
    "items_by_price": [
        "Burger - $15",
        "Fries - $9",
        "Brownie - $7",
        "Soft Drink - $4"
    ]
}

Days 1–10 covered:

Functions → Lists & Dicts → List Comprehensions → String Methods → Error Handling → Classes → File I/O → JSON → APIs → CSV

Essentially, we’ve covered the full foundation of practical Python. The concepts from here get more interesting — less “how do I store data” and more “how do I write code that’s elegant, efficient, and maintainable” - and following clean code principles.

The next ten days will cover:

• Day 11: Decorators
• Day 12: Generators & iterators
• Day 13: Context managers
• Day 14: args and kwargs
• Day 15: Comprehensions — dict & set (plus nesting)
• Day 16: Regular expressions
• Day 17: Virtual environments & project structure
• Day 18: Testing with pytest
• Day 19: Working with databases (SQLite)
• Day 20: Pulling it all together in a bigger project