Add Errors to CSV

Add Errors to CSV is perfect for simulating messy data. Quickly introduce typos, missing values, or duplicates to stress-test scripts, forms, or import pipelines with realistic CSV errors.

Paste your input above or import a file below.
No file chosen
Supported file types: .txt, .csv, .tsv, .log, .json, .xml, .md, .ini, .yaml, .yml, .html, .htm, .css
Total characters: 0
Options
Shuffle characters in cells
Duplicate random rows
Remove values randomly

How to Use:

  • Paste your clean CSV data into the “Input Text” box on the left
  • Or click “Choose File” to upload a .csv or other supported plain text file
  • File types supported: .txt, .csv, .tsv, .log, .json, .xml, .md, .ini, .yaml, .yml, .html, .htm, .css
  • Toggle Shuffle characters in cells to randomly scramble letters within individual values
  • Toggle Duplicate random rows to occasionally insert full row duplicates
  • Toggle Remove values randomly to blank out random cell entries
  • Use the Errors per 100 rows number field to set how often errors are introduced
  • The output updates live on the right and flashes to show changes
  • Under the output, you’ll see a live counter for total characters
  • Click “Add Errors” to manually re-inject randomized errors
  • Use “Copy Output” to copy the new CSV to your clipboard
  • Use “Export to File” to download your glitchy CSV for testing
  • Click “Clear All” to reset input, output, file choice, toggles, and error rate

What Add Errors to CSV can do:

Add Errors to CSV is built to help developers and QA teams simulate bad data. Whether you’re validating input sanitization or seeing how your app behaves with corrupted files, this tool can generate realistic edge cases with just a click. You control how frequent and what kind of errors show up from scrambled characters to dropped values or rogue duplicates. And because it all runs in the browser, it’s safe and fast.

Example:

Before:

name,age,email
Alice,30,[email protected]
Bob,25,[email protected]
Carol,28,[email protected]

After (with errors):

name,age,email
Ailce,30,[email protected]
Bob,25,
Bob,25,
Carol,82,[email protected]

Common Use Cases:

Whether you’re testing how a parser handles bad CSVs, building training material, or stress-testing form logic, Add Errors to CSV makes it easy to mess up your data intentionally. It’s great for testing import systems, catching edge-case bugs, or demonstrating what not to do in production.

Useful Tools & Suggestions:

Before adding errors, Extract a CSV Column lets you pull out a clean copy for safekeeping. And once you’ve introduced the glitches, Analyze CSV can help you spot how and where things broke.

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