CSV Viewer
Paste or open a CSV file to view it as a sortable table, then export to JSON, SQL, XML, or Markdown. Handles quoted fields and custom delimiters. Free, private, in-browser.
CSV Viewer, Sorter & Converter
Your table will appear here. Paste CSV above or open a .csv file.
How to Use the CSV Viewer
Load your CSV
Paste your comma-separated data into the box, or click Open .csv file to load one straight from your computer. If your file uses semicolons, tabs, or pipes instead of commas — common in European exports and spreadsheets — pick the matching delimiter from the dropdown.
View it as a table
Press View table and your data renders as a clean, scrollable grid. Leave "First row is a header" ticked if your top row contains column names; untick it and the tool labels the columns for you. Quoted fields, embedded commas, and line breaks inside cells are all handled correctly.
Sort any column
Click a column header to sort the table by that column; click again to reverse the order. Numeric columns sort by value (so 9 comes before 80), while text columns sort alphabetically — no need to tell the tool which is which.
Convert and export
Choose JSON, SQL, XML, or Markdown to convert your table into that format. Copy the result to your clipboard or download it as a file. The SQL option emits ready-to-run INSERT statements using the table name you provide.
Working With CSV: View, Sort, Convert
The Format That Refuses to Die
CSV — comma-separated values — is the oldest and most stubbornly universal data format on the web. Every spreadsheet exports it, every database imports it, every analytics platform accepts it, and almost every "download my data" button on the internet hands you one. Its appeal is its simplicity: a plain-text file where each line is a row and commas separate the columns. But that same simplicity hides a surprising amount of complexity, and it is exactly where most quick online viewers fall over. What happens when a value itself contains a comma — a name like "Smith, John" or an address? The CSV standard wraps such fields in double quotes. What if the value contains a quote character, or a line break in the middle of a cell? Those get escaped too. A naive "split on commas" approach mangles all of these, silently corrupting your data. This viewer implements the quoting rules properly, so a field like "Smith, John" stays one cell, a doubled quote "" becomes a single literal quote, and a newline inside quotes does not break the row. It also lets you switch the delimiter to a semicolon, tab, or pipe, because many real-world exports — particularly from European locales where the comma is a decimal separator — do not actually use commas at all.
Viewing is only half the job; the other half is getting the data into whatever shape your next tool needs. A developer seeding a database wants INSERT statements. A front-end engineer wants a JSON array of objects to drop into a fixture file. Someone documenting a dataset wants a clean Markdown table to paste into a README or a wiki. An integration that speaks SOAP or a legacy system wants XML. This tool produces all four from the same parsed table, escaping each format's special characters correctly — single quotes doubled for SQL, angle brackets entity-encoded for XML, pipes backslash-escaped for Markdown — so the output is safe to use as-is rather than a starting point you have to clean up by hand.
"CSV looks trivial until a value contains a comma. The difference between a toy viewer and a useful one is entirely in how it handles the awkward cases — quotes, escapes, and embedded newlines."
Private by Design
There is one more reason to use an in-browser CSV tool rather than the first online converter a search throws up: privacy. CSV files are very often the most sensitive data an organisation handles — customer lists, transaction exports, employee records, mailing lists, sales pipelines. Uploading one of those to an unknown website to "convert it to JSON" can quietly hand a copy of your data to a third party, which for anyone bound by GDPR, PDPA, or a basic duty of care is a real problem. This tool runs entirely in your browser: the file you open is read locally, parsed in JavaScript on your own machine, and never transmitted anywhere. You can confirm this by loading the page, disconnecting from the internet, and watching it work exactly as before. For everyday data wrangling — eyeballing an export, sorting it to spot outliers, or reshaping it for the next step in a pipeline — a fast, correct, private CSV viewer is one of the quietly essential tools in a developer's or analyst's kit.
10 Facts About CSV
CSV predates the PC — comma-separated lists were used in IBM Fortran as far back as 1972.
The format was finally written down as RFC 4180 only in 2005 — decades after it was in use.
A field with a comma in it must be wrapped in double quotes to stay a single value.
A literal double-quote inside a quoted field is written as two quotes ("").
Cells can contain line breaks — as long as the whole field is quoted.
Many European exports use a semicolon, because the comma is their decimal separator.
TSV (tab-separated) is just CSV with a tab as the delimiter — this tool reads both.
CSV has no types — every value is text until something decides to read it as a number.
This tool sorts numbers by value and text alphabetically, automatically per column.
Your file never leaves your browser — parsing happens entirely on your own machine.
Frequently Asked Questions
- Paste your CSV (or open a file), press "View table", then click the JSON export button. The tool turns each row into a JSON object using the header row as the keys, and outputs a formatted array you can copy or download. Quoted fields and special characters are handled correctly, so the JSON is valid and ready to use in code or a fixture file.
- Yes. The parser follows the standard CSV quoting rules: a field wrapped in double quotes can contain commas, line breaks, and even quote characters (written as two quotes in a row). So a value like
"Smith, John"stays a single cell rather than splitting into two. This is the main thing that separates a correct CSV viewer from a "split on commas" script that quietly corrupts your data. - Yes — choose Semicolon from the Delimiter dropdown before viewing. Many spreadsheet exports from European locales use semicolons because the comma is their decimal separator. The tool also supports tab-separated (TSV) and pipe-separated files, so most common export formats are covered.
- Click any column header to sort by it, and click again to reverse. When both values being compared look like numbers, the tool sorts them numerically — so 9 comes before 80, not after it. When they are text, it sorts alphabetically (case-insensitively, with natural number ordering). You do not have to tell it which columns are numeric; it decides per comparison.
- It generates one
INSERT INTOstatement per row, using your header names as the column list and the table name you type into the box. Text values are quoted and any single quotes inside them are escaped (doubled) so the SQL is safe to run; empty cells becomeNULL. It is designed for seeding a development database quickly from a spreadsheet. - No. The entire tool runs in your browser — the file you open is read locally and parsed on your own machine. Nothing is sent to any server, stored, or logged. This matters because CSV files often hold sensitive data such as customer or employee records, and uploading those to an unknown converter can be a real privacy and compliance risk. You can even use this tool offline.
- Untick "First row is a header" before viewing. The tool then treats every line as data and labels the columns "Column 1", "Column 2", and so on. Exports use those generated names as JSON keys, SQL columns, and so forth, which you can rename afterwards if you need to.
- It comfortably handles files with thousands of rows. Because everything runs in your browser's memory, the practical limit is your device's RAM rather than any server cap — very large files (hundreds of thousands of rows) may render slowly, but typical exports open instantly. The table scrolls within a fixed area so big datasets stay manageable on screen.
- Yes. Click the Markdown export to produce a GitHub-flavoured table — a header row, a separator row, and one row per record — with any pipe characters in your data safely escaped. Copy it straight into a README, wiki page, or pull-request description.
- Completely free, with no account, no sign-up, and no usage limit. It runs entirely in your browser and collects no personal data. Open as many files and run as many conversions as you like.
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