Module 2 warned you that real-world data is always messy — "delhi" next to "Delhi" next to "DELHI ", stray spaces, duplicated rows — and showed you formulas to fight it, one column at a time. This project upgrades the weapon: a script that cleans a whole file in one run, and — the real prize — cleans next week's file the same way with zero extra effort.
Meet the mess
Make a file called customers.csv with these rows (dummy data, as always — invented people, example.com emails):
name,city,email Priya Sharma ,london,priya@example.com amit verma,LONDON,amit@example.com Sara Khan,London ,sara@example.com Priya Sharma ,london,priya@example.com Leo Martin,sydney,leo@example.com
Five rows, three enemies hiding in them:
- Stray spaces — "Priya Sharma " ends with an invisible space; " amit verma" starts with two.
- Inconsistent capitals — london, LONDON and London are the same city to you, and three different cities to a computer.
- Duplicates — Priya appears twice, character for character.
None of these shout. All of them poison your numbers: a report grouping by city would show London three times with a third of the total each, and Priya would be counted twice. This is the whispering wrong number from Module 2, at its favourite hiding spot.