CSV Type Inferrer

Paste a CSV and get a JSON schema — the delimiter and header row are auto-detected and every column is typed as int, float, bool, date, datetime or string, with typed records. Runs in your browser; nothing is uploaded.

About this tool

Paste a chunk of CSV and this tool figures out its structure for you. It sniffs the delimiter (comma, semicolon, tab or pipe) by testing which one splits the rows into the most consistent number of columns, decides whether the first row is a header, and then infers a type for every column — int, float, bool, date, datetime, string, or empty. The result is a JSON schema report plus the rows re-emitted as type-coerced JSON records. Everything runs locally in your browser; the CSV is never uploaded.

Worked example

Given this input:

id,name,active,joined,score
1,Alice,true,2021-05-01,9.5
2,Bob,false,2022-11-30,7

the schema report includes:

{
  "dialect": { "delimiter": ",", "delimiter_name": "comma", "quote_char": "\"", "has_header": true },
  "row_count": 2,
  "column_count": 5,
  "columns": [
    { "name": "id",     "type": "int",    "nullable": false, "non_empty": 2, "missing": 0, "unique": 2 },
    { "name": "name",   "type": "string", "nullable": false, "non_empty": 2, "missing": 0, "unique": 2 },
    { "name": "active", "type": "bool",   "nullable": false, "non_empty": 2, "missing": 0, "unique": 2 },
    { "name": "joined", "type": "date",   "format": "YYYY-MM-DD", "nullable": false, "non_empty": 2, "missing": 0, "unique": 2 },
    { "name": "score",  "type": "float",  "nullable": false, "non_empty": 2, "missing": 0, "unique": 2 }
  ]
}

Choose Records only to get just the typed rows, or Schema only to skip the records.

Limits & edge cases

Zero-padded integers such as 007 or ZIP codes like 01234 are kept as strings so leading zeros survive.
A column is only given a numeric/date/bool type when every non-null value in it matches; one stray value keeps the whole column a string.
Null tokens are matched exactly and case-sensitively against the trimmed cell (plus the empty string is always null).
Dates are validated (month/day ranges, leap years). Supported date shapes are YYYY-MM-DD, YYYY/MM/DD, MM/DD/YYYY, DD/MM/YYYY and the dash variants; datetimes are YYYY-MM-DD with a T or space separator and an optional trailing Z.

FAQ

How does it pick the delimiter?

With Delimiter set to Auto-detect, it parses the text once with each candidate (comma, semicolon, tab, pipe) and keeps the one that produces the most consistent column count across rows, requiring at least two columns. Set a specific delimiter to skip sniffing.

How does header detection work?

In Auto-detect mode it compares the first row against the inferred type of each column's data rows: if the data is clearly typed (numbers, dates, booleans) but the first row's cell is text, it votes that the first row is a header. An all-text table can't be told apart, so it assumes a header is present. Force the behaviour with Header row → First row is a header or No header.

Why is my number column showing up as a string?

Every value in the column has to parse for the column to take that type. A single non-numeric cell, a stray label, a thousands separator like 1,000, or a leading-zero code such as 007 will keep the column as string. Add unusual missing-value markers to Null tokens so they don't block inference.

What counts as a missing value?

An empty cell is always treated as missing, plus any token you list in Null tokens (default NA,N/A,NULL,null,None,nan). Missing cells become null in the records and are excluded from type inference; the missing count and nullable flag in the schema reflect them.

Is my data uploaded anywhere?

No. The tool is compiled to WebAssembly and runs entirely in your browser tab — the CSV you paste never leaves your machine.

Developer & Automation Access

Run it from the terminal

Same engine as this page, headless — via the gizza CLI:

gizza tool csv-type-inferrer "id,name,active,joined,score
1,Alice,true,2021-05-01,9.5
2,Bob,false,2022-11-30,7"

New to the CLI? Get gizza →

Open it by URL

Pre-fill and auto-run this tool with query parameters — the names match the API/CLI:

https://gizza.ai/tools/csv-type-inferrer/?data=id%2Cname%2Cactive%2Cjoined%2Cscore%0A1%2CAlice%2Ctrue%2C2021-05-01%2C9.5%0A2%2CBob%2Cfalse%2C2022-11-30%2C7&delimiter=auto&headers=auto&null_tokens=NA%2CN%2FA%2CNULL%2Cnull%2CNone%2Cnan&date_detection=true&output=both

Machine-readable descriptor: tool.json — title + parameters JSON Schema for agents.