Independent tool / Browser-only analytics
Data quality lab
Profile a CSV. Preview the cleanup. Export the result.
Find missing values and duplicate rows before they distort your analysis. Start with the synthetic sample or use a local CSV. Your file stays in this browser tab.
A file, or a few rows.
UTF-8, comma-separated, first row as headers. Up to 2 MiB, 5,000 data rows, and 50 columns. Quoted commas, quotes, and multiline fields are supported.
Paste or inspect the CSV
Before → proposed cleanup
Missing cells include blank and whitespace-only values. Duplicate rows count additional exact copies across every column; whitespace matters until you choose to trim it.
Changes run in order: trim, drop blank rows, then remove duplicates. The original stays in memory unchanged. Uncheck an option to compare again.
Original rows
Proposed rows
Inspect every column
Profile of the proposed dataset before export protection. Numeric-looking values are inferred, never converted. Min, max, and mean use finite numeric values only; mixed columns show how many values were excluded. A numeric-looking identifier may still be an identifier.
Export what you inspected.
CSV quoting alone does not prevent spreadsheet formulas. Export adds a leading apostrophe
to cells and headers beginning with =, +, -, or @, including after whitespace, and to leading tab or line-break values.
This protection can change spreadsheet interpretation, including making negative numbers text. The preview shows cleanup; the export adds these protective prefixes. Treat externally supplied files carefully in the spreadsheet you use.
Independently developed for this portfolio with AI assistance. The sample uses synthetic manufacturing-style records, including deliberate duplicates, blanks, mixed values, and a formula-like note. It contains no employer or customer data. Processing is deterministic: no model calls, uploads, cookies, or browser storage.