When a CSV looks right but imports wrong
A CSV file is text arranged into records and fields. A spreadsheet adds its own interpretation when it opens that text. A file can therefore have correct structure and still produce an unexpected date, shortened product code or changed price in the next application. Start by separating those two problems.
1. Check the separator before changing your data
If an entire row appears in one column, the receiving application may expect a different separator. A semicolon-separated export needs the semicolon option here; a tab-separated export needs Tabs. The output of this tool always uses commas. It does not automatically guess your input separator.
For example, this is a two-column record when semicolons are selected:
product;description
00123;"Blue pencils, pack of 12"The comma inside the description belongs to the value. Quotation marks keep that description together when the output is converted to comma-separated CSV.
2. Treat quotation marks as structure
A quoted field can contain its separator or a line break. A quotation mark inside a quoted field is represented by two quotation marks. Removing every quote with Find and Replace can break a valid file. This checker reports malformed quotation marks instead of guessing where a field ends.
item,description
00123,"Notebook labelled ""Travel"""That description contains the text Notebook labelled "Travel". The repeated quotation marks are the CSV representation of a single literal quote; they are not duplicate content to remove.
3. Count records, not lines on the screen
A postal address or note can include a line break inside a quoted value. That is still one field in one record. The checker reports record and column positions. Those positions may differ from the line numbers in a text editor. It also checks that records have a consistent field count; an extra separator can create an unintended empty field.
4. Preserve product codes and other text identifiers
The checker preserves values such as 00123, 12.50 and spaces inside fields. Your spreadsheet may subsequently convert them. Use the receiving application's text import flow and select a Text column type for identifiers when that option is available. A CSV has no column-type metadata, so quoting a value cannot guarantee every spreadsheet will treat it as text.
5. Review formula-like values
Some spreadsheet applications interpret a value starting with symbols such as = as a formula. The checker warns about suspicious values but leaves them unchanged; it does not execute them. A structure check is not a security clearance. Import untrusted columns as text, and use the original source to investigate unexpected formulas.
6. Keep the original and compare a small sample
Download creates a separate file called checked-data.csv. Keep your original, import a small sample into the destination and compare identifiers, prices, row counts and a multiline note before replacing a working dataset. If the file fails the encoding check, export UTF-8 from its original application. Renaming a file's extension does not change its encoding.