Remove personal details from spreadsheet sample data
If someone needs sample data to help with a spreadsheet, they probably don't need your customers' names and addresses. A few made-up rows may be enough. If you need to use real data, keep the sample small and remove details that aren't needed.
1. Save just the table you need
Keep your workbook private. Spreadsheet privacy cleaner opens CSV, TSV or JSON files, rather than .xlsx workbooks. CSV and TSV are plain-text tables. When saving CSV from Excel, check that the right sheet is active. For JSON, use a list of records and check any details stored inside each record too.
2. Look through every column
Open the file in Spreadsheet privacy cleaner. Check the Looks like and Action choices for each column. The tool guesses from headings and sample values, so it may miss a private note in an ordinary-looking column. Remove whole columns you don't need, such as addresses, account links or case notes.
3. Choose what to replace
Replace consistently is useful when the same person appears on several rows and you need to keep that connection. Otherwise, Remove column or Blank may be enough. Mask leaves part of a value visible, including an email domain. Year only removes some date detail; check that the year in the result is right.
4. Think about what the remaining details reveal
A job title, town and unusual date can point to one person even without a name. Remove or make those details less specific if they aren't needed. If the reader only needs totals, share the totals instead of individual rows.
5. Check more than the preview
The preview shows only eight rows. Choose Download cleaned file and open the result to check the rest, including long cells and headings. Search for private values you know were there. If you choose Hash (keyed), the tool makes fresh codes for each cleaning run; don't expect those codes to stay the same between the preview, download or separate exports.
6. Send the sample, not the original workbook
Use a filename that doesn't reveal a private name or project, and explain any replacements the reader needs to understand. If you must send a workbook too, Document metadata can help remove saved author details. It won't remove private cell contents for you.
Good to know
Replacing names doesn't guarantee that nobody can identify the people in a table. Replacement labels and hash codes also don't stop someone opening the file. Keep the source data and any list connecting replacement names to real people private.