Format
CSV to JSON
Paste a delimited table and get an array of objects. Delimiters can be detected. Type inference is optional and conservative.
Input is processed in your browser. DataToolMage does not upload it, store it, or send it to analytics.
Paste structured data. Work stays in this browser.
How it works
A local RFC-style parser splits rows, then maps columns to object keys. Detection looks at the first line only.
Input and output
Input is delimited text. Output is a JSON array of objects. Binary spreadsheets are out of scope.
Common uses
Header row
name,qty\ntea,2 becomes [{"name":"tea","qty":"2"}] unless inference is on.
Quoted comma
"Smith, Ada",42 stays one field, not two.
How to use this tool
- Paste CSV or TSV into the input.
- Confirm the delimiter, header row, and whether types should be inferred.
- Copy or download the JSON array.
Limitations
- Not an Excel/Office file converter.
- Header-less tables get column_1, column_2, … keys.
- Very large tables are rejected by row, cell, and byte limits.
Questions
- Is this RFC 4180 CSV?
- It follows RFC 4180 quoting: fields may be quoted, quotes are escaped as "", and quoted fields may contain newlines. Dialects still vary. Pick the delimiter if detection is wrong.
- Are numbers converted automatically?
- Only if you enable type inference. Leading-zero IDs and integers outside the safe integer range stay strings so they are not corrupted.
- Is my CSV uploaded?
- No. Parsing runs in your browser. DataToolMage does not send the table to a server.
Related tools
JSON to CSV
Paste objects and get a table. Column order follows first-seen keys. Nested values are serialized as JSON text, not silently dropped.
CSV Cleaner
Clean a messy export: trim whitespace, drop empty rows, and drop columns that are empty in every row.
Deduplicate CSV
Paste a table and drop later rows that match an earlier row. Compare the whole row or named key columns.