Anonymize CSV Data

Anonymize sensitive data in CSV files directly in your browser. Select columns to mask and instantly replace names, emails, or other private info with generic labels.

Paste your CSV above or import a file below.
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Supported file types: .csv, .txt, .tsv
Total characters: 0
Options

How to Use:

  • Paste your CSV content into the Input CSV box or upload a file using the Choose File button.
  • Supported file types include .csv, .txt, and .tsv.
  • The tool reads your header row and lists each column in the Select Columns to Anonymize section.
  • Tick the checkbox next to any column you want to anonymize (e.g., Name, Email, Phone).
  • As soon as you make a selection, the tool replaces each unique value in that column with a generic anonymized value like Anon1, Anon2, and so on.
  • The result updates live in the Anonymized Output box with a quick flash so you can spot the change.
  • You can mix and match any columns just check or uncheck them and the output will instantly reprocess.
  • The Total characters counter updates in real time so you can see the size of the result.
  • Use Copy Output to copy the anonymized data to your clipboard.
  • Use Export to File to download the result as a .csv file.

What Anonymize CSV Data can do:

Anonymize CSV Data is the fastest way to hide personal or sensitive information in your datasets. Whether you’re cleaning up client records, preparing a sample for testing, or complying with privacy policies, this tool lets you keep the structure of your CSV intact while masking specific fields. All processing happens locally in your browser nothing is uploaded or stored.

Example:

Input:

Name,Email,Phone
Alice,[email protected],555-1234
Bob,[email protected],555-5678

Output (Name and Email anonymized):

Name,Email,Phone
Anon1,Anon1,555-1234
Anon2,Anon2,555-5678

Common Use Cases:

Use this to prepare CSV data for public sharing, anonymize test cases for developers, or comply with GDPR or privacy requirements when working with spreadsheets. It’s fast, simple, and doesn’t require Excel or any scripts.

Useful Tools & Suggestions:

Before anonymizing, run Find Data in CSV to locate sensitive fields like names or emails. Then after the swap, use Validate CSV to make sure nothing broke during the obfuscation.

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