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Parse CSV records across quoted physical lines and map every string field under explicit header, blank-record and row-width rules.

Survey data analyst

Keep multiline responses, padding and leading-zero identifiers.

Convert quoted comments, inspect record count and page through the bounded preview.

No spurious rows or trimming; full export contains all accepted records.

Import API developer

Detect ambiguous headers and uneven records.

Test duplicate headers, switch to row arrays, compare reject/pad rules.

No field overwrite or dropped extra columns; selected changes are disclosed.

Mobile data-cleaning Project reviewer

Save this conversion separately from reverse export.

Convert valid CSV, explicitly save to Format and Clean Data, inspect three unique fields.

Source/output/policy persist only by request, and reverse conversion cannot overwrite them.

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Reference & details

How it works

Stateful record parsing

A quote-aware parser reads delimiters, doubled quotes and CR/LF inside quoted fields across physical lines. Unexpected characters after a closing quote and unterminated fields stop conversion.

Explicit record mapping

Object mapping requires unique non-empty names or generated Column names. Extra cells are always refused; missing cells may be padded only by choice. Row arrays preserve every record, including headers and uneven widths.

Review and bounded export

Every cell remains a string. The preview is limited to 200 records in 25-row pages, while output includes every converted row. Explicit Project saving uses CSV-to-JSON-specific source, output and policy fields.

Updated: August 2026

Example Scenarios

An analyst retains embedded newlines and quoted commas in comments, checks the preview count and preserves leading-zero participant identifiers.

A developer detects duplicate headers, chooses row arrays to retain all fields, or fixes the source before using object mapping.

A mobile reviewer converts a validated CSV sample and explicitly saves its three fields to Format and Clean Data without overwriting a later JSON-to-CSV export.

FAQ

No type inference or trimming is performed. Every CSV cell is a JSON string, including numeric-looking text, padding and embedded line endings. One leading BOM is treated as a file marker and disclosed.

Object mapping rejects empty or repeated names. Choose no header to generate Column1-style names, or row arrays to preserve all original records without assuming a header schema.

Blank records are preserved and validated by default. An explicit skip option removes only physically empty unquoted records. Object rows with extra fields are refused; missing fields require explicit padding. Row arrays allow unequal lengths.

No. Preview shows the first 200 data rows in pages of 25; copy and download contain the full result. Limits are 5,000 data rows, 200 columns, 100,000 cells, one million input and two million output characters.

No. Conversion uses a local worker with a ten-second timeout. Explicit Project save stores source, JSON and policy notes locally when source and output are each at most 100,000 characters. Copy is result-only; UTF-8 file import rejects invalid bytes.

About CSV to JSON

Treat CSV as records, not physical lines. Preserve strings first, and choose explicit policies for headers and uneven rows before sending the JSON to another system.