Convert a CSV while preserving leading-zero identifiers

Treat the first row as your field names

The CSV to JSON Converter reads the first CSV row as headers and returns an array of objects. Choose short, unique column names before converting. Repeated headers are rejected because two columns should not silently compete for the same object property.

Paste the CSV into Input and process it. Empty rows are skipped, including rows that contain only whitespace after parsing. A parsing error stops the conversion, so inspect mismatched quotes or inconsistent field counts before trying again. The tool supports up to 5,000 data rows and 250,000 input characters.

Preserve an identifier and a quoted comma

Use this sample:

code,name,quantity
0012,"Bolt, brass",3

The expected JSON is:

[
  {
    "code": "0012",
    "name": "Bolt, brass",
    "quantity": "3"
  }
]

The quotes around the CSV name keep its comma inside one field. The code retains its leading zeros. Quantity is also a string, even though it looks numeric. This is intentional: the converter disables automatic numeric and Boolean conversion rather than guessing which columns contain identifiers.

If your application needs quantity as a number, apply that conversion later to the specific validated field. The same approach protects long account references whose digits could exceed a number parser’s exact integer range. Turning all digit-only strings into numbers would undo that protection.

Check the receiving system’s expectations

Download converted.json and confirm the row count, header spelling, and representative values. A syntactically valid output does not ensure that the next application accepts empty strings, field names, or date formats. Decide explicitly whether a blank source cell means unknown, not applicable, or an empty text value.

The implementation uses Papa Parse’s header-based parsing with dynamic typing disabled. Its official documentation describes these parsing options and error reports. CSV dialects vary, so a complicated export should be tested with a small representative sample before converting a whole workflow.

Keep data handling deliberate

Conversion runs in the browser without uploading the entered table to an ERITHRA processing service. The downloaded JSON remains a copy of your source data, so store it appropriately and remove personal records from examples you share. Use JSON Formatter to inspect nested output from later processing, or JSON to CSV when you need a flat tabular export again.