CSV Numeric Column Extractor

About this tool

Spreadsheets and database dumps mix identifiers, labels, dates and measurements in one table. This tool reads a CSV or TSV and tells you which columns are actually numeric — then hands those columns back as typed arrays you can drop straight into a chart, a statistics routine or a JSON payload.

It sniffs the delimiter (comma, tab, semicolon or pipe), decides whether the first row is a header, and tests every cell in every column. A column qualifies when all of its non-missing values parse as numbers; loosen that with Minimum numeric share if a stray label shouldn't disqualify an otherwise numeric column. Each qualifying column reports whether it is an integer or a float, how many values it holds and how many were missing — and every rejected column comes back in a skipped list with the reason and an offending example, so you never have to guess why a column disappeared. Everything runs locally in your browser; the data is never uploaded.

Worked example

Given this input:

id,name,score
1,Alice,9.5
2,Bob,7

the default Typed arrays output is:

{
  "delimiter": "comma",
  "header": true,
  "rows": 2,
  "columns_total": 3,
  "numeric_columns": 2,
  "columns": [
    {
      "name": "id",
      "index": 1,
      "type": "integer",
      "count": 2,
      "missing": 0,
      "numeric_ratio": 1,
      "values": [1, 2]
    },
    {
      "name": "score",
      "index": 3,
      "type": "float",
      "count": 2,
      "missing": 0,
      "numeric_ratio": 1,
      "values": [9.5, 7]
    }
  ],
  "skipped": [
    {
      "name": "name",
      "index": 2,
      "reason": "only 0 of 2 value(s) parse as numbers (0% < the 100% required)",
      "example": "Alice",
      "numeric_ratio": 0
    }
  ]
}

Switch Output to Column names only for id, then score on the next line; to Numeric columns as CSV for id,score / 1,9.5 / 2,7; or to Row objects for [{ "id": 1, "score": 9.5 }, { "id": 2, "score": 7 }].

Accounting formats

With Accept $1,234.50 / 45% / (500) formatting left on, exported figures still count as numbers: thousands separators (1,234.50 → 1234.5), currency symbols $ € £ ¥ ₹, a trailing percent sign (45% → 45), parentheses negatives ((500) → -500) and trailing minus (250- → -250). Turn it off when you want strictly plain numbers.

Limits & edge cases

• Input is capped at 1 MB of pasted text (about 1,000,000 characters). Split larger exports and run the parts separately.
• Zero-padded codes such as 007 or a ZIP like 01234 are not treated as numbers, so identifier columns don't get silently converted.
• inf, Infinity and NaN are treated as text, not numbers.
• Missing cells are the empty cell plus anything in Null tokens (matched exactly and case-sensitively after trimming). They become null in the output and are excluded from the numeric share.
• Ragged rows are padded: a row shorter than the widest row counts as missing in the trailing columns. Wholly blank lines are dropped.
• Values are re-emitted as parsed numbers, so 1,234.50 comes back as 1234.5 and trailing zeros are not preserved.

FAQ