CSV Inspector
File
Auto-detects the delimiter from the first line (comma, tab, semicolon, pipe) and parses with proper RFC 4180 quoting. Each column gets a quick type inference (number, boolean, date, string) plus a count of empty cells, the number of distinct values, and a sample. Full-row duplicates are surfaced as a separate metric.
Rows
5
Cols
6
Duplicates
0
| Column | Type | Empty | Unique | Sample |
|---|---|---|---|---|
| id | number | 0 | 5 | 1 |
| name | string | 0 | 4 | Alice |
| string | 1 | 4 | alice@example.com | |
| age | number | 1 | 4 | 30 |
| signup | date | 0 | 4 | 2024-01-15 |
| verified | boolean | 0 | 2 | true |
Everything runs in your browser — your data never leaves the device.
How to use
- Drop a CSV / TSV file or paste data directly into the box.
- Toggle the header-row checkbox to match your data.
- Read the row / column / duplicate cards, then the per-column type table.
Frequently asked questions
- What counts as a duplicate?
- An exact match across all fields. A row where one cell differs by a single character is not a duplicate. Use a dedicated dedupe step in your pipeline if you need fuzzy matching.
- How accurate is the type inference?
- Best-effort. A column passes as `number` only if every non-empty cell parses as a number, and similarly for boolean and ISO-ish dates. Mixed columns fall back to `string` rather than guessing.
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