CSV Viewer
Drop in a CSV file and read it as a proper table instead of a wall of commas. The viewer parses quoted fields, escaped quotes, and values containing commas or newlines correctly, auto-detects whether the delimiter is a comma, semicolon, tab, or pipe, and lets you sort by any column and filter across all cells. Nothing is uploaded — the file is parsed in your browser, so you can inspect exports and reports privately.
How to use the CSV Viewer
Paste CSV text or load a .csv / .tsv file. The table appears immediately, with a row and column count above it. Leave the delimiter on auto-detect for most files; switch it manually if your data uses an unusual separator or the guess is wrong. Toggle First row is header off if your file has no header line — generic column names are used instead.
Click any column heading to sort by it; click again to reverse. Sorting is numeric when a column holds numbers and alphabetical otherwise, so a score column orders sensibly rather than treating 10 as less than 9. Type in the filter box to keep only rows that contain your text in any cell — useful for finding a record in a large export. Very large files are capped at a few thousand displayed rows for responsiveness, while the full counts still reflect the whole file.
Why CSV needs a real parser
CSV looks trivial — values separated by commas — but the format has corners that trip up naive splitting. A field can be wrapped in double quotes so it may itself contain commas ("Babbage, Charles"), line breaks, or escaped quotes written as two double quotes (""). Splitting on commas alone mangles any file with quoted fields, which is why opening a real-world export in a quick script so often produces misaligned columns. This viewer implements the RFC 4180 rules: it tracks whether it's inside a quoted field and only treats a delimiter or newline as structural when it isn't.
Delimiter detection matters too. Although it's called comma-separated, plenty of CSV in the wild uses semicolons — common in locales where the comma is a decimal separator — or tabs (TSV) or pipes. The viewer samples the first line, ignoring anything inside quotes, and picks whichever candidate appears most, so files from different sources just work. You can always override the guess.
Beyond correct parsing, the value of a viewer is interaction. Sorting reveals the largest or smallest values and groups related rows; filtering finds the needle in a thousand-row haystack. Doing this in the browser means a customer export, a financial report, or a database dump never leaves your machine — a meaningful privacy difference from uploading the same file to an online converter. For genuinely huge files, a streaming tool or a spreadsheet with chunked import is still the right choice; an in-browser viewer is ideal up to the tens-of-megabytes range.
Common use cases
- Inspecting exports. Quickly read a CSV from a database, CRM, or analytics tool without a spreadsheet app.
- Finding a row. Filter a large export down to the records that match a name, ID, or status.
- Checking structure. Confirm column counts and headers parsed correctly before importing elsewhere.
- Private review. Look at sensitive data locally instead of uploading it to a web converter.