TOOL GUIDE · CSV CONVERSION
How the converter reads rows
The first record is treated as column headings; each following record becomes an object whose property names come from those headings. Commas inside quoted fields, doubled quote characters, and line breaks within quoted fields are handled according to a common CSV convention. Every data row must contain the same number of fields as the heading row, and repeated heading names are rejected because they would create ambiguous object keys.
CSV has multiple dialects. Files may use a semicolon or tab, omit headers, or follow application-specific quoting rules. This quick tool expects commas and a header row. Inspect a sample and confirm the source convention before converting a large table.
Why values stay strings
A value such as 00137 may be a postal code or product identifier, not a number to calculate with. Converting it automatically would remove meaningful leading zeroes. Dates can also be ambiguous across locales. The converter therefore retains values as text. Apply explicit, documented type rules afterward if your destination requires numbers, dates, booleans, or nulls.
Conversion checks
- Confirm the first row really contains unique column names.
- Check delimiter, quote convention, encoding, and row count.
- Inspect fields containing commas, quotes, blank values, and embedded line breaks.
- Compare the converted object count and field names with the source table.
- Validate the result against the destination schema.
For the reverse direction, use JSON to CSV. Read the CSV conversion and data quality article for more examples and limits.
The conversion executes locally in your browser. It does not submit the table to a FormatInstant processing server.
