View a CSV with column typing and quick stats - no upload, no install.
The tools that come up when the actual job is interpreting data rather than collecting it: CSV viewer with column typing for the export you just got from the database, JSON formatter for the API response, regex tester against the source string, base64 for the binary blob someone embedded in a JSON field, hash for source verification, and the AI summarizer for digesting long-form sources.
RFC 4180 compliant - quotes, escaped quotes, embedded newlines and BOMs are all handled correctly, including the kind of malformed CSV that real-world tools produce.
Auto-types columns (number, date, string, boolean) so you can sort / filter as you would in a spreadsheet, and shows per-column stats (count, min, max, mean) for the typed ones.
Virtualized rendering keeps 100k-row files snappy. The file is parsed in the browser, not uploaded.
How to use it
Drop or paste the CSV. Pick the delimiter and quote char; if the file is malformed, the viewer tells you which line is broken.
Glance at the column-type row across the top - if a numeric column was detected as string, pick a different column or fix the source.
Sort and filter as needed. Copy the filtered subset back out as CSV or paste it into your downstream tool.
The limit is your browser’s memory, not an upload cap - the file is parsed on your machine and never sent anywhere. A multi-hundred-megabyte export is better filtered or aggregated before it reaches a browser tab.
Is the file uploaded anywhere?
No. That matters when the export contains customer records, invoices or anything under a data-processing agreement - you can inspect the file without moving it off the laptop.
Why does a numeric column import as text?
Usually the export, not the viewer: leading zeros, thousands separators, currency symbols or a stray space make a column string-typed. Fix it at the export when you can, and sort by the string only after you have checked it.