Clean messy name and email fields

Some customer names arrive in ALL CAPS, some have extra spaces, and the emails mix upper and lower case throughout the file.

IntermediateRead 6 minDoing: 35 minutes7 steps

▶ Start

What you'll have at the end

A function that turns a batch of messy name and email values into one consistent format

Before you start

You need

A batch of customer records, each holding a raw name and a raw email as separate text fields, a list of dictionaries or rows already read from a CSV, plus a working Python setup to run a cleaning script against them.

Not covered

Confirming an email address is real and actually receives mail, splitting a name into first and last parts, and handling names in scripts with no letter case, like Chinese or Arabic, all stay out of scope here: this only makes Latin-script names and syntactically well-formed emails consistent.

Leans on

Make every character count the same way

Bring every name to one Unicode form
Collapse the extra whitespace

Fix the letters and the email

Fix the casing without breaking a suffix
Lowercase and trim the email address
Flag emails that fail a basic syntax check

Package it and prove it works

Wrap the fixes into one function
Run the batch and check for duplicates

Where to go next

Profile a brand new CSV file before you trust a single row in it

if you haven't seen this file before, profile it first to find out how messy the name and email columns actually are before you write a cleaning function for them.

Keep a script running when one row in the file is bad

once you're flagging a broken email instead of raising on it, this is where you make the rest of a much bigger batch survive a row that's truly unusable.

Checked 25 Aug 2026

Part of the Python cookbook