CSV Header Sanitizer

About this tool

A header row written by a human is not a set of identifiers. It has spaces, currency symbols and units in brackets, a stray capital, a column somebody left blank, a year at the front, and — the one that actually costs you data — two different columns that both ended up called Notes. Every downstream step then has to cope: a database rejects Total ($), a dataframe gives you df['First Name'] instead of df.first_name, and a join keyed on a name that quietly became the second notes drops rows without telling you.

This tool rewrites that one row and nothing else. Paste the table, pick a casing, and the header comes back as valid identifiers: punctuation and spacing collapsed to single separators, accents transliterated, blank headers named after their position, digit-leading names repaired, and every collision deduplicated so no two columns share a label. Data rows are passed through untouched — no trimming, no re-typing, no row deduplication — quoted fields keep their quoting, and the field separator round-trips unchanged.

It renames columns, not values. If your cells are the mess, clean those separately; if you want to see the renames before you trust them, switch the output to the rename map and read every change as an original,sanitized pair.

Worked example

Input (defaults everywhere: snake, ASCII on, underscore prefix, no length cap, dedupe by counting up):

First Name, Total ($) ,2024 Revenue,,Notes,Notes
Ada,10,120,x,first,second

Output:

first_name,total,_2024_revenue,column_4,notes,notes_2
Ada,10,120,x,first,second

Six problems fixed in one pass: the space in First Name, the currency symbol and padding in Total ($), the leading digit in 2024 Revenue, the blank fourth header, and the duplicate Notes — the second of which became notes_2 rather than overwriting the first. The data row is byte-for-byte what went in.

Switch Output to the rename map and the same input returns the audit trail instead:

original,sanitized
First Name,first_name
 Total ($) ,total
2024 Revenue,_2024_revenue
,column_4
Notes,notes
Notes,notes_2

Controls

• Delimiter — , (default), tab, semicolon, pipe, any single character, or auto to sniff the separator from the header line. Whatever comes in is what goes out.
• Identifier style — snake_case (default), camelCase, PascalCase, kebab-case, SCREAMING_SNAKE, lowercase, or preserve. The first five read FirstName as two words; lowercase and preserve deliberately do not split a CamelCase run, so HTTPStatusCode stays one token.
• Transliterate Unicode to ASCII — on by default: Año → ano, Größe → grosse, 名前 → ming_qian. Turn it off to keep the original letters, which is fine for a quoted SQL identifier or a dataframe column but not for a bare identifier.
• Names starting with a digit — an unquoted SQL identifier cannot begin with one. Prefix an underscore (default), prefix col, or keep it and quote the name yourself.
• Max name length — 0 means no limit. Use 63 for PostgreSQL, whose identifiers are truncated at 63 bytes; 300 is BigQuery's ceiling and this tool's maximum. Truncation cuts any separator left dangling at the end, and a deduplication suffix always stays inside the cap — the base name gives up characters to make room, so a capped customer_lifetime_value pair becomes customer_lif and customer_l_2.
• Name for blank headers — the base used when a header cell is empty or nothing but punctuation. The column's 1-based position is appended, so the default gives column_2, column_4.
• When two names collide — count up (total, total_2, total_3, the default), use the duplicate column's own 1-based position (total, total_3), or allow the collision if your reader genuinely keeps duplicate columns.
• Output — the whole table with the new header (default), just the cleaned header row, or the original,sanitized rename map.

Limits and edge cases

The table is capped at 5,000,000 bytes and names at 300 characters. Only row 1 is rewritten — there is no "no header" mode, because a table without a header has nothing to sanitize. Collisions are matched exactly, so under preserve a Total and a total are two distinct names even though PostgreSQL would fold them together; pick a lowercasing style if that matters. Reserved words are left alone on purpose: the list differs across PostgreSQL, MySQL, BigQuery and Snowflake, so a built-in list would rename legitimate columns for most users. Output rows are terminated with a single newline (\n) and the result always ends with one. Everything runs locally in your browser — the table is never uploaded.

FAQ