What this category helps you do
Data cleaning formulas save time before analysis. They help repair exported data, standardize columns, remove invisible characters, and prepare spreadsheets for pivot tables, lookups, and dashboards.
- Find duplicate records
- Convert text numbers into real numbers
- Clean phone numbers for consistent formatting
- Create dropdown validation lists
Data Cleaning formula examples
Choose a formula below. Each page explains the formula in plain English and gives examples one at a time so long formulas are easier to read and copy.
Clean Phone Numbers
removes common phone number punctuation so numbers can be compared consistently.
Open examples →FormulaConditional Formatting Formula
uses TRUE/FALSE logic to format cells automatically.
Open examples →FormulaConvert Numbers Stored as Text
turns imported text numbers into real numeric values.
Open examples →FormulaData Validation List
creates or supports a dropdown list from a clean source range.
Open examples →FormulaDynamic Named Range
creates a range that expands as new records are added.
Open examples →FormulaFind Duplicates
flags values that appear more than once.
Open examples →FormulaHighlight Duplicates
uses a formula rule to identify duplicate rows or values for conditional formatting.
Open examples →FormulaRemove Duplicates
returns a unique list from a range without manually deleting rows.
Open examples →FormulaRemove Line Breaks
removes line breaks and non-printing characters from imported text.
Open examples →Best formulas to start with
How to learn this category
- Open one formula page and test the first beginner example.
- Change one cell reference at a time so you understand what each part controls.
- Check the common mistakes section before copying the formula down.
- Move to related formulas when you need a cleaner or more advanced version.