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CSV / TSV / JSON / YAML converter

Convert between CSV, TSV, JSON and YAML, and see the rows as a table.

Related tools

All Data & computing tools →
CSV to JSON converterParse CSV text (with header row) into a JSON array of objects, handling quoted fields. Drop a file in rather than pasting it — it is read in your browser and never uploaded.JSON to CSV converterTurn a JSON array of objects into comma-separated values with a header row. Takes a whole file, so a long log does not have to go through the clipboard.Random JSON GeneratorGenerate arrays of realistic mock JSON objects (users, products, orders, events…) for testing and prototyping.YAML Formatter / ValidatorTidy YAML — normalize indentation, convert tabs to spaces and flag tab-indent errors.CSV to Markdown tableTurn CSV into a Markdown table, quoting and all: a field may hold the delimiter, a line break or a pipe and the table still lines up. Comma, semicolon (French Excel), tab or pipe, detected or forced.CSV transposeSwap the rows and columns of delimited data. Paste the text or drop the file; nothing leaves the page either way.JSON comment removerStrip // and /* */ comments from JSONC to make it valid JSON. Drop a file in rather than pasting it — it is read in your browser and never uploaded.Flatten / unflatten JSONFlatten a nested JSON object into one level of path keys — and put it back together again. Arrays are indexed as user.roles[0] or user.roles.0, values keep their type, and an empty object stays visible as {}. Takes a whole file, so a long log does not have to go through the clipboard.

CSV / TSV / JSON / YAML converter works straight from this page — free, instant, nothing to install. You will find it under Data & computing, with CSV to JSON converter and JSON to CSV converter for the neighbouring cases.

How to use it

  1. Open the tool — no signup or install needed.
  2. Enter your input or adjust the available options.
  3. Get your result instantly, then copy or download it.

Frequently asked questions

What is CSV / TSV / JSON / YAML converter?

Convert between CSV, TSV, JSON and YAML, and see the rows as a table.

When would I actually use this?

Finding out how big a thing will be before you make it: how many gigabytes an hour of footage takes, how long a file needs on the connection you have, how large a photo prints before it goes soft, what bitrate fits the budget you were given.

What is the most common mistake?

Reading a figure in one unit next to a figure in another. Megabits are not megabytes and the eight-fold gap sinks most transfer estimates; a kilobyte is 1 000 bytes to a drive maker and 1 024 to the operating system; pixels are not dots per inch. None of it is hard arithmetic — the unit on each side is what decides whether the answer means anything.

How is CSV / TSV / JSON / YAML converter different from CSV to JSON converter?

They sit next to each other but answer different questions. CSV to JSON converter: parse CSV text (with header row) into a JSON array of objects, handling quoted fields. Drop a file in rather than pasting it — it is read in your browser and never uploaded. Pick whichever matches what you're starting from — both are free.

Is there a tool for the next step?

JSON to CSV converter is the closest one after this: Turn a JSON array of objects into comma-separated values with a header row. Takes a whole file, so a long log does not have to go through the clipboard.

What else is worth having open alongside it?

Random JSON Generator and YAML Formatter / Validator — they come up in the same task often enough to be worth a second tab.

Where do the figures come from?

Byte prefixes follow the IEC convention where a kibibyte is 1 024 bytes and a kilobyte is 1 000 — drive makers use the second, operating systems often report the first, and a disk that shrinks on arrival is that gap and nothing else. Print sizing assumes 300 dpi unless you change it.

Further reading

All guides →
ExplainerJSON to CSV When the Structure Is Nested: Why There Is No Right AnswerThe same two orders come out as five columns from one converter and ten from another, and neither is wrong. Dotted paths, arrays of scalars, arrays of objects and records with different keys — four decisions, made for you, usually silently.ExplainerWhy Your CSV Breaks Accents and Dates in ExcelThree completely different faults hide behind the same sentence. One is the encoding, one is the separator, one is Excel guessing at types while it opens the file — and the fix for each is different. Here is how to tell them apart in five seconds.ExplainerCSV to JSON: The Five Cases That Break Every ConverterQuoted delimiters, embedded newlines, ambiguous types, duplicate headers and encoding. Each one was run through the converter and the exact output is printed here — including the two cases it does not rescue.GuideTransposing a Table Whose Rows Should Have Been ColumnsWhat happens to the header row, what happens to rows of unequal length, what happens to types — and the one thing transposing is regularly mistaken for and cannot do.GuideTest Data Without Real People: Why Pseudonymised Is Still Personal, and Synthetic Is NotSwapping names for identifiers does not take a database out of the GDPR — Article 4(5) and Recital 26 say so directly. Genuinely synthetic data is outside the Regulation altogether. That single distinction decides how you seed a staging environment.ExplainerYAML Looks Friendly and BitesYAML is JSON plus a type-inference layer, and the inference is the dangerous part. The same file run through a YAML 1.2 parser and a YAML 1.1 parser: no is a string in one and false in the other, 01234 is 1234 in one and 668 in the other, and 12:30:00 is a number in one of them.