Spreadsheet formats & CSV

How To Convert XLSX To CSV Python?

Read the intended XLSX worksheet with pandas, preserve identifier columns as text, and write a separate UTF-8 CSV.

By Uddhav Gopani, FounderPublished 27 September 2026Updated 29 September 2026

Read the intended XLSX worksheet with pandas, preserve identifier columns as text, and write a separate UTF-8 CSV. Renaming the workbook extension does not convert its contents. Choose the sheet explicitly because a CSV has no worksheet tabs.

Set up the conversion

Install pandas and an XLSX reader such as openpyxl in the environment running the script. Use a worksheet name rather than relying on its position. The example treats every imported cell as a string and disables automatic missing-value strings, which is suitable for a text interchange contract. It does not promise to preserve Excel display formatting or formula expressions.

A reproducible conversion example

import pandas as pd

df = pd.read_excel("input.xlsx", sheet_name="Contacts",
                   dtype=str, keep_default_na=False, engine="openpyxl")
df.to_csv("contacts.csv", index=False, encoding="utf-8", lineterminator="\n")
check = pd.read_csv("contacts.csv", dtype=str, keep_default_na=False)
assert list(check.columns) == list(df.columns)
assert check.equals(df)

The code is an illustrative conversion core. Run it in an isolated working folder with the named test files, install only the dependencies used by the example, and handle its reported errors before applying it to a larger dataset. It does not contact a remote conversion service.

Check the expected result

Use a workbook whose Contacts sheet contains the headers id, name and note. Store 00123 as a text cell, include the name Lee, Ana, and put an embedded quotation mark in note. Include an empty middle cell in a second row. After export, the CSV parser must return the same three columns and the same strings. A numeric cell merely displayed with leading zeros is different from a text identifier: dtype=str cannot reconstruct zeros that exist only in a cell format.

Format-specific limits

The writer exports loaded values. It does not keep formulas, formatting, validation rules or workbook links. Formula results can depend on cached workbook values; recalculate with the spreadsheet application and verify the results before making an interchange export. For a workbook too large for available memory, use a bounded streaming workflow and explicit row counts.

Verify the file contract before using the result

Write down the delimiter, encoding, header names, field order and treatment of empty values. Keep the original file unchanged and write the converted output to a different path. Conversion is successful when a parser for the destination format recovers the intended values; a familiar filename extension or a successful save message is not enough.

Start with a small fixture that contains the cases your real data can contain. Include a leading-zero identifier, a quoted comma, an embedded quotation mark, a blank field and a non-ASCII character. Add a multiline field only if both formats and the receiving system support it. Verify the fixture first, then run a bounded sample from the real input. Record parsed row counts and check the first and last records so truncation or an accidental duplicate header is visible.

Keep identifiers separate from quantities. An account-like or product identifier may contain digits while still being text; converting it to a floating-point number can remove leading zeros or precision. Dates also need an agreed format. When a conversion produces an unexpected blank, investigate whether it came from an empty source cell, a missing field, an invalid value or an automatic missing-value rule. Those conditions can require different downstream handling.

Do not resolve malformed records by silently skipping them unless that behavior is an explicit requirement and the skipped records are reported. Use a failure message that identifies the record or field, retain enough context to correct the input, and avoid exposing sensitive contents in public logs. For production automation, write to a temporary destination and promote it only after validation so a failed run cannot replace a previously good export.

Where the browser tool fits

Convert Text to CSV helps with already extracted plain text. It does not replace a workbook reader, a JSON parser, an XML schema validator or a Parquet engine. Use it only when its input structure and delimiter choices match your actual data. For structured source files, perform the format-aware conversion above and check the result with an independent reader.

Primary reference

Official format and API documentation