How to standardize dates in your data
Provide comma-separated data with a header row and at least one data row. Paste it into Paste CSV below, or load a CSV or TXT file through the file control. The parser splits comma-separated values only.
The tool reformats recognized dates and flags blank, invalid, unparseable, or unresolved ambiguous values. It does not add flagged rows to the standardized results.
Choose the date column and conversion rules
The tool detects the header row and available columns automatically after you paste or upload data, then fills Column containing dates with the detected headers.
- Choose Output format: ISO 8601 (YYYY-MM-DD), US style (MM/DD/YYYY), EU style (DD/MM/YYYY), or Long form (Month D, YYYY).
- Set Ambiguous numeric dates (e.g. 03/04/2024) to Flag for review (don't guess), Assume MM/DD/YYYY (US), or Assume DD/MM/YYYY (international).
- Set Write normalized values to Add normalized column (keep original) or Overwrite selected column.
Recognized date formats and parsing behavior
The detector recognizes YYYY-MM-DD, YYYY/MM/DD, compact YYYYMMDD, numeric D/M/Y or M/D/Y with slash or dash separators, Month D, YYYY, and D Month YYYY.
ISO-like values with a time suffix are reduced to the date portion; the time is not preserved. Two-digit years are accepted: 00 through 68 map to 2000 through 2068, while 69 through 99 map to 1969 through 1999. Invalid calendar dates, such as February 30, are rejected. The standardized table includes a Detected format column.
Run the standardization
- Paste comma-separated data with headers and at least one data row, or load file content.
- Select Column containing dates, then choose Output format, Ambiguous numeric dates (e.g. 03/04/2024), and Write normalized values.
- Processing starts automatically after the input and settings are usable.
Review standardized and flagged results
Only successfully parsed rows appear in Standardized records. Blank, invalid, unparseable, and unresolved ambiguous values are excluded and appear under Flagged - needs review, with the row, original data, and reason.
Each Export CSV button is enabled only when its result set contains records. The standardized export includes detected_format. The flagged export includes row, original_data, value, and reason.
Keep or replace the original date column
Add normalized column (keep original) appends a column named normalized_date. Overwrite selected column replaces the selected date column in standardized output. Flagged rows are not rewritten in either mode.
What the tool does not validate
The parser checks whether a value forms a real calendar date, but the tool does not apply business rules such as future-date, weekend, holiday, or range checks. If Flag for review (don't guess) is selected, an ambiguous value is not assigned a date until you resolve it.
Processing and data-handling scope
The tool's parsing, date detection, formatting, and CSV export code runs in your browser. The inspected tool code does not upload the input to a processing endpoint.
Frequently Asked Questions
Does this validate whether a date is correct?
This tool checks that a value forms a real calendar date (for example, it rejects February 30) as part of parsing it, but it does not perform business validation - such as checking that a date isn't in the future, isn't a weekend, or falls within an expected range. It normalizes representation, not business validity.
What happens with a date like 03/04/2024?
Values like this are genuinely ambiguous - they could mean March 4 or April 3 depending on convention. By default the tool flags them for your review. You can instead choose to assume MM/DD/YYYY (US) or DD/MM/YYYY (international) for all ambiguous values in a run.
What date formats are detected?
ISO 8601 (YYYY-MM-DD), YYYY/MM/DD, compact YYYYMMDD, numeric dates with slash or dash separators (D/M/Y or M/D/Y), "Month D, YYYY", and "D Month YYYY". Values that don't match any of these are flagged rather than guessed.
Can I keep my original date column?
Yes. Choose "Add normalized column" to keep the original column untouched and append a new normalized column, or "Overwrite selected column" to replace it in place.