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If you work with data exports, log files, or anything that comes out of a database, you probably deal with CSV more than you would like. These tools let you inspect, clean, transform, and analyze tabular data without firing up Excel or writing a script. View a CSV in a spreadsheet-like interface, run pivot table aggregations, compare two data files side by side, or generate SQL INSERT statements from your rows. There are also validators, deduplicators, and column-level transformers for the messier datasets.
CSV files often carry customer lists, revenue figures, research datasets, and internal metrics - data that has no business being on a third-party server. Processing locally means your data stays in your browser's memory and is discarded when you close the tab. There is also no row-count limit imposed by a server tier; load a million-row export and work with it directly.
Keep and reorder chosen columns, with the list built from the widest row so a field beyond the header is not dropped
Rename columns under a stated convention, with two that would end up with the same name numbered rather than left to collide
Chain 34 cell transformations, each stating its own rule, with anything it could not do reported rather than passed through unchanged
Classify every column against a decider rather than a regex: calendar-checked dates, RFC 4291 addresses, and leading zeros kept out of integer columns
Validate columns against rules that name their definition: the email rule browsers enforce, a URL scheme allowlist, calendar-checked dates, and every failure explained
Remove duplicate rows with equality as a stated choice: case, spaces, accents and numbers each their own switch, and the rule in force shown
Diff two CSV files with the matching rule stated: a key that may repeat, or a real Myers diff, with every row accounted for
Format and validate against RFC 4180 by section, with output verified by reading it back
Combine CSV files with columns matched by name, so a reordered export still lands correctly, and every difference reported
Count what is missing in five categories that add up to the grid, with the tokens that mean missing your choice
Group and aggregate with the choices stated: what count counts, how group keys are matched, and which values were not numbers
Filter rows with each condition stating its rule: a cell that is not a number does not match a comparison, and an empty cell is not a zero
Find and replace with both halves stated: what the pattern matches, and whether $1 and $& in the replacement are patterns or text
Sort by any number of columns, with the comparison stated: numbers by value, dates by day, text by a collation you choose
Split a CSV by rows, file count, column value or a real byte-size maximum, with every input row accounted for exactly once
Per-column statistics with the definitions named: which of the nine quantile rules, sample and population deviation side by side, and why each cell was counted
Convert CSV to XLSX or ODS with cell types that keep leading zeros, long IDs and dates intact
Convert both ways, converting a type only when it reads back the same, and naming every value that cannot
Generate SQL that runs: identifiers quoted rather than stripped, values escaped per dialect, and every change to your data reported
View, sort and edit a CSV, with an undo stack that goes back exactly one step and a parse report that tells a broken quote from a ragged row
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