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Data helper

CSV ⇔ JSON Converter

Convert between CSV and JSON formats seamlessly.
Support for custom delimiters (comma, tab, semicolon) and bidirectional conversion.
Perfect for data migration, spreadsheet integration, and quick data analysis.

Guide: How to use & features

  • Select the conversion direction: CSV to JSON or JSON to CSV.
  • Under "Options," specify the delimiter (comma, tab, or semicolon) for your data.
  • Paste your data into the input field to see the conversion results instantly.
  • Click "Copy Output" to grab the converted data for your project.

Samples: Sample input & output

CSV to JSON conversion

Input

id,name,role
1,Alice,Admin
2,Bob,User

Output

[
  {
    "id": "1",
    "name": "Alice",
    "role": "Admin"
  },
  {
    "id": "2",
    "name": "Bob",
    "role": "User"
  }
]

JSON to CSV conversion

Input

[
  {"id": 1, "product": "Widget", "price": 10.5},
  {"id": 2, "product": "Gadget", "price": 20.0}
]

Output

id,product,price
1,Widget,10.5
2,Gadget,20

FAQ: FAQ

  • How is nested JSON (nested objects or arrays) converted?

    CSV is a flat table of rows and columns, so nested structures cannot be represented as-is. Data shaped as an array of objects where each item shares the same keys converts most cleanly. For deeply nested data, flatten the fields you need to the top level first for stable results.

  • Can I choose the delimiter and whether there is a header row?

    Yes — it supports comma, tab, and semicolon delimiters and lets you toggle a header row. Tab (TSV) or semicolon delimiters can work better with Excel in locales that use a comma as the decimal separator.

  • Non-ASCII text looks garbled when I open the file in Excel — what should I do?

    That happens because Excel does not auto-detect UTF-8; the converted data itself is correct. Import via Data → From Text/CSV in Excel and choose UTF-8 as the encoding to open it without garbled characters.

Use cases: Common use cases

  • Convert Spreadsheet Data to JSON

    Convert table data copied from Excel or Google Sheets into JSON format for use as initial program data or mock APIs.

  • Export API Responses to CSV

    Convert JSON data received from an API to CSV for easier aggregation and analysis in spreadsheet software.

  • Data Format Conversion & Cleansing

    Switch between CSV and JSON while easily changing delimiters (comma/tab) to normalize your data formats.

Notes: Notes & limitations

  • Nested Structures

    When converting JSON to CSV, nested objects or arrays are not flattened. Plain, flat JSON structures are recommended.

  • Large Datasets

    Converting extremely large datasets may cause the browser to freeze or crash due to memory limitations.

CSV and JSON Converter

CSV and JSON are common data exchange formats, but they serve different workflows. This converter helps turn CSV rows into JSON objects and flatten simple JSON data into CSV for spreadsheets, tests, API fixtures, and quick data handoffs.

Common use cases

  • Create API fixtures: Convert spreadsheet exports into JSON samples for tests or mock servers.
  • Prepare spreadsheet data: Turn simple JSON records into CSV for analysis or sharing.
  • Inspect data shape: Check fields, values, and inferred types before importing data elsewhere.

Conversion note

CSV is flat, while JSON can be nested. Arrays and nested objects need a flattening or serialization convention before they can fit cleanly into columns.

Articles for this tool

Introduction
2026-05-02

CSV and JSON Conversion: Choosing the Right Format for APIs and Data Migration

Learn how to convert between CSV and JSON safely, including headers, delimiters, value types, nested data, and practical workflow tips.

Recent Articles

Use Case
2026-08-07

curl Options Cheat Sheet: What -X, -H and -d Actually Do

A reference for the curl options you meet in real API work: why -d already implies POST, how -d differs from --data-raw, the @ prefix that silently reads a file, single vs double quotes, and why -k and -L deserve more caution than they usually get.

Introduction
2026-08-06

Converting Between JSON Schema and Zod: How required Maps to .optional()

Inside a two-way converter that turns JSON Schema into a Zod schema and Zod code back into JSON Schema. Covers the inverted defaults between required and .optional(), the constraint mapping table, and how the Zod side is parsed without executing any code.

Use Case
2026-08-06

SQL Clause Order Reference: Why WHERE Can't See Your SELECT Alias

The order you write SQL clauses is not the order the database runs them. A reference for the logical execution order (FROM → WHERE → GROUP BY → HAVING → SELECT → ORDER BY → LIMIT), why aliases fail in WHERE, when to use WHERE vs HAVING, and the MySQL/PostgreSQL differences that bite.

Use Case
2026-08-06

Unified Diff Format Reference: Reading @@ Hunks in git diff Output

How to read the unified diff format git produces: what the four numbers in @@ -12,7 +12,9 @@ mean, why a one-character edit shows as a whole-line replacement, the whitespace and line-ending traps, \ No newline at end of file, combined @@@ diffs on merges, and rename detection via similarity index.

Use Case
2026-08-06

UTC to JST Reference: The 9-Hour Offset, Cheat Sheet & Timezone Pitfalls

Convert between UTC and JST (Japan Standard Time) with a cheat sheet. Covers what Z and +09:00 mean in ISO 8601, when JavaScript date parsing silently shifts by 9 hours, MySQL/PostgreSQL timezone behavior, and why GitHub Actions cron always runs in UTC.

Use Case
2026-08-04

CREATE TABLE Reference: MySQL vs PostgreSQL vs SQLite Types & Constraints

A cross-database CREATE TABLE (DDL) reference with cheat sheets for data types, auto-increment keys (AUTO_INCREMENT / IDENTITY / rowid), foreign key ON DELETE behavior, and the CHECK constraint that MySQL silently ignores.

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