CSV to JSON Converter

How to convert CSV to JSON

1. Paste your CSV data into the input field — the first row must contain the column headers (field names).
2. Choose the delimiter that matches your CSV file: comma (,), semicolon (;), or tab (⇥).
3. Click "Convert" — the JSON array output appears instantly with each row mapped to an object.
4. Switch to "JSON → CSV" using the toggle above if you need the reverse direction.
5. Click "Copy" or "Download .json" to use the output in your application, API, or data pipeline.

How CSV to JSON conversion works

The converter splits the CSV input into lines, uses the first line as the header row (column names), and maps each subsequent line to a JSON object using the headers as keys and the row values as values. The output is a JSON array where each element corresponds to one CSV row. The conversion runs entirely in your browser — no data is sent to any server.

RFC 4180-compliant quoted fields are handled correctly: values wrapped in double quotes are unquoted, escaped double quotes ("" inside a quoted field) are unescaped to a single quote, and newlines inside quoted fields are preserved. All output values are strings — CSV does not store data type information, so numeric coercion is not applied automatically.

// Input CSV (comma delimiter):
name,age,city
Alice,30,Kyiv
Bob,25,Lviv
Carol,35,Odesa

// Output JSON array:
[
  { "name": "Alice", "age": "30", "city": "Kyiv"  },
  { "name": "Bob",   "age": "25", "city": "Lviv"  },
  { "name": "Carol", "age": "35", "city": "Odesa" }
]

// Note: all values are strings. To convert numeric fields:
// data.forEach(row => { row.age = Number(row.age) })

Who uses CSV to JSON conversion

CSV is the universal export format for spreadsheets, databases, and reporting tools. JSON is the universal import format for web applications and APIs. Converting CSV to JSON is the bridge between these two worlds.

• Frontend developers — loading data from a spreadsheet export (Excel, Google Sheets) into a JavaScript application or chart library.
• Backend developers — importing database exports or legacy CSV files into JSON-based APIs or document stores.
• Data engineers — transforming CSV exports from CRMs, ERPs, and analytics tools into JSON for ingestion into NoSQL databases or event streams.
• Content managers — converting spreadsheet content into JSON data files for static site generators (Hugo, Astro, Eleventy).
• QA engineers — converting test data from spreadsheets into JSON fixtures for automated test suites.
• Business analysts — preparing Excel or Google Sheets data for use in JavaScript-based reporting and visualization tools.

CSV input requirements and delimiter guide

The converter follows the RFC 4180 CSV standard. To get reliable output, ensure your CSV meets these requirements before converting:

• First row must be headers — the column names in the first row become the JSON object keys. If your CSV has no header row, add one before converting — otherwise the first data row is treated as headers and lost.
• Consistent delimiter — all rows must use the same delimiter. Select the matching option in the converter before clicking Convert.
• Quoted fields for special characters — values containing the delimiter, double quotes, or newlines must be wrapped in double quotes. The converter handles these correctly when they are properly quoted.
• UTF-8 encoding — the converter processes the text as UTF-8. Files exported from Excel may be in Windows-1252 encoding — resave as UTF-8 first if you see garbled characters.

When to convert to JSON — and when to keep CSV

Convert to JSON when:

• Target is a web application or API — JavaScript natively parses JSON; CSV requires a separate parsing library or manual import step.
• Loading into a NoSQL database — MongoDB, Firestore, DynamoDB, and similar stores use JSON-like documents as their native format.
• Static site generator data files — Hugo, Astro, Eleventy, and 11ty all support JSON data files for template rendering.
• JavaScript chart libraries — Chart.js, D3, Recharts, and similar libraries accept JSON arrays as their data source directly.
• Feeding an API or webhook — REST and GraphQL endpoints expect JSON-encoded request bodies.

Keep CSV when:

• Recipients use Excel or Google Sheets — spreadsheet users are more comfortable filtering and editing CSV than JSON files.
• Bulk database imports — SQL databases use COPY and LOAD INFILE commands that accept CSV natively and efficiently.
• Logs and large flat datasets — CSV is more compact and can stream line-by-line without loading the full file into memory.
• Data interchange with non-developer teams — CSV is universally editable in any spreadsheet tool without special tooling.

Edge cases: quoted fields, numbers, and special characters

CSV appears simple but has several edge cases that trip up basic parsers. This converter handles all of them correctly by following the RFC 4180 specification:

• Commas inside values — "New York, USA" is a single quoted field containing a comma. The converter treats it as one value, not two columns.
• Double quotes inside quoted fields — RFC 4180 escapes an embedded quote by doubling it: "say ""hello""" contains say "hello". The converter unescapes these correctly.
• Newlines inside quoted fields — a multiline value inside double quotes is treated as a single field. The embedded newline is preserved in the JSON string.
• Leading/trailing whitespace — whitespace inside quoted fields is preserved. Unquoted values are trimmed of leading and trailing spaces.

// CSV input with quoted fields:
name,bio,score
Alice,"Software engineer, Kyiv",95
Bob,"Says ""hello"" often",87
Carol,"Line one
Line two",91

// JSON output:
[
  { "name": "Alice", "bio": "Software engineer, Kyiv", "score": "95" },
  { "name": "Bob",   "bio": "Says \"hello\" often",   "score": "87" },
  { "name": "Carol", "bio": "Line one\nLine two",        "score": "91" }
]