CSV to JSON
Convert CSV files to JSON array or object format
Convert
About this tool
Convert CSV files to JSON array or object format
Ready to convert
Select a file and click Convert to get started
Convert tabular CSV rows into a JSON array
CSV to JSON treats the first CSV row as column headers and converts each following row into one JSON object. The current processing engine writes an array of row objects with two-space indentation.
Where row-oriented JSON helps
- •Prepare spreadsheet exports for an API import.
- •Inspect CSV records as named JSON fields.
- •Move a flat table into a JavaScript-friendly exchange format.
How to use this tool
- 1.Upload one .csv file up to 100 MB.
- 2.Choose the delimiter actually used by the file: comma, semicolon, tab, or pipe.
- 3.Convert, then inspect header names, inferred values, missing fields, and row count before using the JSON.
Parsing rules to check
- The server uses pandas read_csv with the chosen single-character delimiter.
- Column names come from the header row; duplicate or blank headers can be renamed or interpreted unexpectedly.
- Pandas infers types, so identifiers with leading zeroes, dates, booleans, and empty values may not retain the representation you expect.
Worked example: two inventory rows
CSV input `sku,stock 0012,7 0013,0` becomes an array with one object per row. Because type inference can treat sku as a number, the leading zeroes may be lost; review identifier columns before importing the JSON.
Flat data stays flat
- CSV has no native nested objects or arrays, so the converter does not invent nested JSON.
- Malformed quoting, inconsistent field counts, or the wrong delimiter can stop parsing or shift columns.
- The verified engine expects text readable by pandas and writes UTF-8 JSON; non-UTF-8 source encodings can fail.
Diagnose a malformed conversion
- One giant column: select the correct delimiter.
- Rows shifted: inspect embedded delimiter characters and make sure fields are correctly quoted.
- Leading zeroes changed: normalize identifier columns after conversion or prepare them as text before upload.
Continue the workflow
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Questions about this specific tool
Does the first row become data?
No. The parser uses the first row as column headers, and subsequent rows become JSON objects.
Can I choose a semicolon or tab delimiter?
Yes. The page offers comma, semicolon, tab, and pipe choices.
Will all values remain strings?
Not necessarily. Pandas infers column types, which can change numeric-looking identifiers, booleans, dates, and missing values.
Can it create nested JSON?
No. The current converter produces a flat array of row objects based on CSV columns.