Step 7: Package it as a function

Finally, wrap the analysis in a function that returns the headline numbers as a dictionary, so it can be reused on next quarter's file or tested. The report prints the best region and best product.

Examplepython

import csv, io

RAW = """date,region,product,units,price
2026-01-05,North,Notebook,10,4.50
2026-01-09,South,Pen,50,1.20
2026-01-12,North,Backpack,3,39.90
2026-01-15, East ,Notebook,8,4.50
2026-02-01,South,Headphones,2,59.00
2026-02-03,West,Pen,n/a,1.20
2026-02-10,North,Pen,40,1.20
2026-02-14,East,Backpack,5,39.90
2026-02-20,,Mouse,4,19.50
2026-03-02,South,Notebook,12,4.50
2026-03-09,West,Headphones,3,59.00
2026-03-15,North,Mouse,6,19.50
2026-03-21,East,Pen,30,1.20"""

def clean(raw_rows):
    good = []
    for r in raw_rows:
        try:
            units, price = int(r["units"]), float(r["price"])
        except ValueError:
            continue
        if not r["region"].strip():
            continue
        good.append({"date": r["date"], "region": r["region"].strip(), "product": r["product"].strip(),
                     "units": units, "price": price, "revenue": round(units * price, 2)})
    return good

sales = clean(csv.DictReader(io.StringIO(RAW)))

from collections import defaultdict

def summarise(sales):
    """Return a dict with the numbers a manager asks for first."""
    by_region = defaultdict(float)
    by_product = defaultdict(int)
    for s in sales:
        by_region[s["region"]] += s["revenue"]
        by_product[s["product"]] += s["units"]
    best_region = max(by_region, key=by_region.get)
    best_product = max(by_product, key=by_product.get)
    return {
        "orders": len(sales),
        "revenue": round(sum(s["revenue"] for s in sales), 2),
        "best_region": best_region,
        "best_product": best_product,
    }

report = summarise(sales)
for key, value in report.items():
    print(f"{key:>13}: {value}")

Open in editor »

You have done a full analysis: question, load, clean, summarise, rank, report, cross-check with SQL and package. Where next: read the CSV from a real file with open(), draw a chart (in the browser with JavaScript or on your computer with a library such as matplotlib), and schedule the script to run every month.

Your turn: write the code

Write best(totals) that takes a dictionary of totals and returns the key with the largest value. Print best({"a": 3, "b": 9, "c": 5}).

Quick check

Why wrap the analysis in a function?

It can be reused and testedPython requires itIt makes the data smaller

Finish the quick check (and any code exercise) to complete this lesson, or mark it done yourself.

Tip: use the left and right arrow keys to move between lessons.