Clean spreadsheet exports before importing them: trim stray spaces, remove empty or duplicate rows, normalize column counts, and switch between CSV and TSV without uploading the data.
This tool deliberately avoids guessing whether “0012” is an ID, whether a date is day-first, or whether two differently cased names are the same person. Those are business decisions. It fixes mechanical issues that commonly break imports while leaving cell values recognizable.
A short row often means a missing trailing value; a long row can mean an unquoted comma. Normalization safely pads short rows but never deletes cells. If the reported column count surprises you, inspect the preview first. See the CSV cleanup guide for a reliable import checklist.
Yes. Commas, escaped quotes and line breaks inside quoted fields are parsed according to RFC 4180.
It finds the widest row and pads shorter rows with empty cells. It does not discard extra values from wider rows.
Yes. Exact row deduplication keeps the first occurrence. A normal header differs from data rows and remains first.
Trim, then remove empty rows, then remove duplicate rows, then pad short rows. Because trimming happens first, rows that differ only by stray spaces count as duplicates; the summary states how many rows and cells each step touched.
No. Deduplication compares whole rows exactly and is case-sensitive, so “Ada” and “ada” both survive. A UTF-8 byte-order mark is dropped from the first cell, but the tool does not re-encode text or repair mojibake from an export that was saved in the wrong encoding — re-export those files as UTF-8.