Rows and duplicates
Remove duplicate records using the keys you name, delete blank rows, filter incomplete records, and preserve a raw copy for reconciliation.
Excel data cleanup
Turn the export into a table you can use.
Tell Griddy how to split, deduplicate, standardize, convert, and format a messy Excel range. The result stays in the workbook, where you can compare the changed rows and continue the analysis.
Cleanup can be destructive. Work on a copy when the raw export is your source of record, and review row counts plus a sample of changed values.
Concrete cleanup prompt
“Split this CSV data into columns, remove duplicate rows, delete rows with blank phone numbers, extract the company name from each email into column E, standardize names to Proper Case, autofit the columns, and apply light header formatting.”
This request separates parsing, deletion, extraction, standardization, and formatting rules. It also identifies where a newly derived field should go.
Expected output
- Delimited text split into separate name, email, phone, and purchase columns.
- Duplicate rows and rows matching the explicit blank-phone rule removed.
- A derived company field added from email domains.
- Consistent name casing, readable column widths, and restrained header formatting.
Record the starting and ending row counts. A cleanup is not verified until removed rows and converted values have been spot-checked.
Workflow
From request to workbook.
- 01
Preserve the raw data
Duplicate the source sheet or workbook before a cleanup that removes rows, replaces values, splits columns, or changes data types.
- 02
List each cleanup rule
Specify the target range and the exact rule for duplicates, blanks, whitespace, casing, delimiters, dates, numbers, errors, or derived fields.
- 03
Apply the transformation
Griddy can coordinate supported Excel cleanup operations and formatting in sequence instead of requiring a separate menu action for each step.
- 04
Reconcile the result
Compare row counts, scan changed columns, test filters and formulas, and keep the raw tab available until downstream reports have been validated.
Cleanup operations
Make messy structure explicit.
Data cleanup is its own intent because the output is a transformed dataset, not a formula explanation or general analysis.
Text and columns
Trim whitespace, clean non-printable characters, split text into columns, extract substrings, concatenate fields, and standardize capitalization.
Types and formats
Convert text numbers and dates, fix leading apostrophes, replace values, fill blanks, and apply the number formats the cleaned data needs.
Review before you rely
A clean-looking table can hide lost data.
Validate cleanup with counts and examples, not appearance alone. The most important check is whether the transformation preserved the records and meaning you intended.
- Define the duplicate key; matching email may be valid while matching company name is not.
- Confirm that identifiers with leading zeros did not become numbers.
- Inspect date conversions for locale ambiguity such as 04/05/2026.
- Keep a raw source tab until formulas, pivots, charts, and imports built on the cleaned data reconcile.
Keep going
Related spreadsheet resources
PlatformAI for ExcelSee the full set of workbook workflows Griddy can perform in Excel.Task pageAI PivotTable generatorSummarize the cleaned table by explicit row and value fields.GuideHow to clean data in ExcelA manual checklist for duplicates, spaces, dates, numbers, and quality checks.TemplateCRM lead trackerMove normalized contact and company data into a structured operating sheet.
FAQ
Before you start.
What Excel data can Griddy clean?
Griddy supports cleanup actions such as removing duplicates, trimming whitespace, splitting text into columns, converting text to numbers or dates, replacing values, removing blank rows or columns, and standardizing formats.
Can Griddy clean a CSV pasted into one Excel column?
Yes. Give the delimiter, target range, expected fields, and follow-up rules. The product demo on this page shows a one-column CSV being split and then cleaned in Excel.
Will cleanup overwrite my data?
Cleanup operations can change or delete cells and rows. Preserve a raw copy, name protected ranges in the prompt, and use undo if the transformation is broader than intended.
How do I verify an AI cleanup?
Compare starting and ending row counts, review removed duplicates, inspect converted dates and identifiers, and reconcile any downstream totals before deleting the raw copy.
Keep the raw data. Fix the working copy.
Open the export in Excel, define the cleanup rules, and reconcile the result.