CSV to JSON Converter
Transform delimited tabular data into structured JSON objects or arrays.
Convert CSV, TSV, semicolon-delimited, or pipe-delimited text into structured JSON. Supports automatic delimiter detection, optional headers, primitive type parsing, and multiple JSON output shapes.
Use CSV to JSON Converter
CSV or TSV text
JSON result
Built for the task, not the page view
- Automatic delimiter detection or explicit comma, tab, semicolon, and pipe selection
- Header-row handling with duplicate-header deduplication
- Optional number, boolean, and null parsing with leading-zero preservation
- Array-of-objects, matrix, keyed-by-first-column, and column-array outputs
- Local file loading plus copy and JSON download
CSVTSVDelimited TextArray of Objects2D JSON ArrayKeyed JSONColumn ArraysUse it correctly
RFC 4180 Quoting & Escaping
Fields that contain commas, line breaks, or double quotes must be enclosed in double quotes. To include a literal double quote inside a quoted field, escape it by doubling it (""), not with a backslash. Unquoted commas always divide columns.
Delimiters & Auto-Detection
Auto-detection scans candidate separators (comma, tab, semicolon, pipe) across the first 15 rows for consistency. If working with tab-separated TSV files or European Excel exports (which use semicolons because commas serve as decimal points), you can lock the delimiter manually.
Row-Width Mismatches
When a row has fewer or more columns than the header row, EveryTools issues an inline warning specifying the row number and column discrepancy. Missing values are filled with empty strings, and extra values beyond the header count are omitted in object mode to prevent corrupt keys.
Header Extraction & Key Deduplication
When header handling is enabled, the first row supplies JSON property keys. If your CSV has duplicate or blank headers, the engine deduplicates them by appending _2, _3, or column_N suffixes, preventing silent key collision and data loss in the output object.
Strict Type Conversion
Numeric values, booleans (true/false), and nulls are converted to native JSON types by default. Crucially, numeric strings with leading zeros (like "01234" for postal codes or IDs) are preserved as strings to prevent truncation and precision loss.
Local In-Browser Processing
All CSV parsing and JSON serialization executes directly within your browser tab. Your tabular data is never uploaded to an EveryTools transformation API or any remote server.
RFC 4180 Parsing & Syntax Guide
The table below summarizes standard CSV rules implemented by the in-browser parser, showing how raw tabular inputs translate into structured JSON:
| Scenario | Delimited CSV Input | Parsed JSON Behavior | Parsing Rule |
|---|---|---|---|
| Embedded commas | 1,"Doe, Jane",Admin | {"name":"Doe, Jane"} | Fields containing delimiters must be enclosed in double quotes. |
| Escaped quotes | 1,"She said ""Hello!""" | {"text":"She said \"Hello!\""} | Quotes inside quoted cells are escaped by doubling them (""). |
| Multiline values | 1,"Line 1\nLine 2" | {"notes":"Line 1\nLine 2"} | Newlines inside quotes are preserved as cell content rather than splitting rows. |
| Duplicate headers | name,name,id | {"name":"A","name_2":"B","id":1} | Colliding header names are suffixed (_2, _3) to prevent data loss. |
| Leading zero strings | id,zip\n1,01234 | {"id":1,"zip":"01234"} | Values with leading zeros are kept as strings to preserve postal codes and IDs. |
| Type conversion | 42,19.95,true,null | 42, 19.95, true, null | Integers, floats, booleans, and nulls cast to native JSON data types. |
| Headerless mode | Alice,Engineer,true | {"column_1":"Alice","column_2":"Engineer"} | When headers are disabled, 1-based indexed keys (column_N) are generated. |
Supported Output Structures
Array of Objects (Default)
Each CSV row becomes a JSON object whose keys correspond to column headers. Ideal for REST APIs, MongoDB, and frontend state management.
[
{ "id": 1, "name": "Ada" }
]2D Arrays (Matrix)
Rows and columns are translated into nested arrays without repeating object keys. Minimizes payload size for large data tables.
[
[1, "Ada"]
]Keyed by First Column
Maps the value of the first column as dictionary keys. Creates a hash map suitable for instant record lookup by unique ID or SKU.
{
"1": { "name": "Ada" }
}Column Arrays
Groups records by column into an object of parallel arrays. Suited for charting libraries, columnar analytics, and data science workflows.
{
"id": [1],
"name": ["Ada"]
}