Skip to content
Server-sideDeleted in 30 minutes

Convert CSV to XLSX

Every cell in a CSV is text. Every cell in a workbook has a type. The conversion therefore has to guess, and guessing is where reference numbers lose their leading zeros and where 03/04 becomes a date in whichever order the locale prefers. Knowing that in advance is most of what you need to convert a CSV safely.

Use this without the search next time. Prathom Workbench puts Prathom's tools in your toolbar.

Add to Chrome — free
CSVXLSX

Drop your CSV file here, or click to browse

Up to 50 MB. Deleted automatically after 30 minutes.

What it does

  • Rows and quoted fields parsed correctly, including embedded commas
  • Cell types inferred from content, which is worth reviewing
  • Output is a single-sheet .xlsx that opens in Excel and LibreOffice

How to use CSV to XLSX

  1. 1

    Upload the CSV

    Comma-separated, with or without a header row. Quoted fields containing commas or line breaks are handled.

  2. 2

    Types are inferred

    Something that looks like a number becomes a number and something that looks like a date becomes a date. This is convenient and occasionally wrong.

  3. 3

    Audit the columns that are identifiers

    Postcodes, product codes, phone numbers and anything with a leading zero are the cells to look at first.

How it works

The CSV is parsed with proper quoting rules: a field wrapped in quotation marks may contain commas and line breaks, and a doubled quotation mark inside one is a literal quote. Each parsed row becomes a row in a new single-sheet workbook.

As each cell is written, its type is inferred from the text. Digits become a number, a recognized date pattern becomes a date, TRUE and FALSE become booleans, and everything else stays text.

Why type inference is both the feature and the hazard

It is the feature because a column of numbers stored as text is nearly useless in a spreadsheet: it will not sum, it sorts alphabetically so 100 comes before 20, and charts refuse it. Inference is what makes the file usable.

It is the hazard because CSV carries no type information, so the inference is a guess made from appearance. A guess is right on genuine numbers and wrong on identifiers that merely look numeric.

The columns to check every time

Anything with a leading zero, anything that is a code rather than a quantity, long numbers that might be rendered in scientific notation, and dates in a slash format. These four cover almost every real import problem.

A safer source

If you control how the CSV is produced, two habits remove most of the risk: write dates as ISO 8601, and quote identifier columns. Quoting does not by itself force a text type everywhere, but combined with ISO dates it removes the ambiguity that causes the worst silent changes.

What a spreadsheet adds that a CSV cannot hold

A CSV is a list of values separated by commas and nothing else. It has no types, no formatting, no formulas, no second sheet and no record of what any column means. Every one of those is added by whatever opens it, which is why the same file can look different in two applications.

Converting to XLSX fixes the interpretation in place. Numbers are stored as numbers, dates as dates and text as text, so the file now carries its own meaning rather than depending on the reader to guess correctly.

That is the real argument for doing this before sharing data with somebody else. They open your interpretation instead of making their own, and the identifier column that would have become scientific notation on their machine does not.

Examples

A data export for a colleague

contacts.csv - 4,200 rows, quoted fields
contacts.xlsx - one sheet, columns typed, 310 KB

The recipient gets something they can sort and filter instead of a wall of text. The quoted fields containing commas parsed correctly, which is the failure a copy and paste would have produced.

An inventory file with codes

stock.csv - codes like 00417, dates as 03/04/2026
stock.xlsx - 417 as a number, 3 April or 4 March by locale

Both cells changed meaning. The code lost its leading zero and the date resolved by locale rather than by intent. Format those columns as text in the CSV or fix them in the workbook afterwards.

Frequently asked questions

Why did my leading zeros vanish?

Because the column looked numeric and was typed as a number, and a number has no leading zeros. This is the single most common CSV import problem and it affects postcodes, product codes, account references and phone numbers. If those identifiers matter, the reliable fix is in the destination: set the column format to text in the workbook and re-enter or re-import the affected values.

How are ambiguous dates handled?

By inference, which is exactly the problem with a value like 03/04/2026: it is 3 April in most of the world and 4 March in the United States, and the CSV carries nothing to say which. The conversion applies a consistent interpretation, but it cannot know your intent. If a file contains dates, the safest source format is ISO 8601, written as 2026-04-03, which is unambiguous everywhere.

Does the first row become a header?

It becomes the first row of the sheet. CSV has no way to mark a header, so nothing is set as a frozen or styled header row automatically. In practice most spreadsheet applications will treat the first row as labels when you sort or filter, and you can freeze it in one click. Nothing is lost either way.