Rename columns, reorder, drop unwanted, duplicate. Combine freely — rename + drop happens in one pass.

Does it validate data types?

No — purely structural. For type validation use CSV Schema Validator.

Can I add computed columns?

Limited — you can rename and reorder. For computed columns (concatenate, parse date), use SQL-like tools after converting to JSON.

Yes — RFC 4180 compliant. Commas and quotes inside values are properly escaped in the output.

A worked example, rendered from real sample data. Sign in to run the tool on your own input.

Input

name=full_name
email=contact_email
drop:age
---
name,email,age,city
Alice,alice@test.com,30,NYC
Bob,bob@test.com,25,SF

Output

full_name,contact_email
Alice,alice@test.com
Bob,bob@test.com

Rename, reorder, or drop columns in CSV data. Part of the DevTools Surf developer suite. Browse more tools in the Data / SQL collection.

Column renaming is one of the most common data wrangling operations — a 2020 Kaggle survey found that data scientists spend 45% of their time on data cleaning and preparation.
The pandas rename() function processes millions of rows in milliseconds because it only changes metadata, not the underlying data — a design choice from Wes McKinney's 2008 creation.
GDPR's 'data minimization' principle (Article 5) requires dropping unnecessary personal data columns before processing — making column remapping a legal compliance tool.

What operations?: Rename columns, reorder, drop unwanted, duplicate. Combine freely — rename + drop happens in one pass.
Does it validate data types?: No — purely structural. For type validation use CSV Schema Validator.
Can I add computed columns?: Limited — you can rename and reorder. For computed columns (concatenate, parse date), use SQL-like tools after converting to JSON.
Will it preserve quoting?: Yes — RFC 4180 compliant. Commas and quotes inside values are properly escaped in the output.

A worked example, rendered from real sample data. Sign in to run the tool on your own input.

Input

name=full_name
email=contact_email
drop:age
---
name,email,age,city
Alice,alice@test.com,30,NYC
Bob,bob@test.com,25,SF

Output

full_name,contact_email
Alice,alice@test.com
Bob,bob@test.com

Rename, reorder, or drop columns in CSV data. Part of the DevTools Surf developer suite. Browse more tools in the Data / SQL collection.

Column renaming is one of the most common data wrangling operations — a 2020 Kaggle survey found that data scientists spend 45% of their time on data cleaning and preparation.
The pandas rename() function processes millions of rows in milliseconds because it only changes metadata, not the underlying data — a design choice from Wes McKinney's 2008 creation.
GDPR's 'data minimization' principle (Article 5) requires dropping unnecessary personal data columns before processing — making column remapping a legal compliance tool.

What operations?: Rename columns, reorder, drop unwanted, duplicate. Combine freely — rename + drop happens in one pass.
Does it validate data types?: No — purely structural. For type validation use CSV Schema Validator.
Can I add computed columns?: Limited — you can rename and reorder. For computed columns (concatenate, parse date), use SQL-like tools after converting to JSON.
Will it preserve quoting?: Yes — RFC 4180 compliant. Commas and quotes inside values are properly escaped in the output.