DATA / FIELD GUIDE

Where did the leading zeros in my CSV go?

Preserve identifiers, handle quoting, and understand conversion losses.

The useful part

CSV stores text. A spreadsheet’s interpretation is a separate step.

Treat identifiers as text

CSV
id,postal_code,note
00123,010010,"Hello, world"
00456,000001,"two
lines"

In PlainKit CSV → JSON, the identifier stays the string "00123". Spreadsheet type inference may display it as 123. Import identifier columns as text and inspect the raw file after saving.

Conversion is not lossless serialization

JSON
[
  {"id":"00123","note":null,"meta":{"tier":1}},
  {"id":"00456","note":""}
]

This tool exports null and missing values as empty cells, and nested objects as JSON text. Converting back produces strings, not the original nulls, missing fields, or objects. Keep the source JSON and a schema when these distinctions matter.

Use formula protection and verify

Spreadsheet applications can interpret formula-like cell text. PlainKit prefixes risky cells and headers with an apostrophe by default. This changes the text and is not a universal guarantee for every importer.

  • Check headers and record counts after conversion.
  • Test cells containing commas, quotes, and line breaks.
  • Agree on encoding, delimiters, types, and null representation.

Sources & editorial note

Sources checked October 17, 2026. Examples and practice notes are authored for PlainKit. Sources do not endorse this project; this is not an audit conclusion.

Try it for yourself.

Start with a synthetic fixture. Tool inputs stay in your browser.

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