Excel cells containing literal strings such as NA, NULL, None, n/a, and nan are converted to NaN. Real blank cells also appear as NaN. This loses distinctions in spreadsheet data, for example a region code NA versus an empty region.

Reproduced on main at eb31b5c9453628def5e6758a27a8e3a87b4ab101:

import io
from openpyxl import Workbook
from markitdown import MarkItDown

workbook = Workbook()
workbook.active.append(["region", "status", "empty"])
workbook.active.append(["NA", "NULL", None])
stream = io.BytesIO()
workbook.save(stream)
stream.seek(0)
print(MarkItDown().convert_stream(stream, file_extension=".xlsx").markdown)

The data row is | NaN | NaN | NaN |; it should be | NA | NULL | |.

Both XLSX and XLS converters use pandas' default missing-value recognition, which is useful for analysis but changes literal document text. keep_default_na=False preserves these strings and leaves blank cells empty. The XLSX fallback that repairs legacy showZeroes attributes also needs the same option.

I reproduced the failure for XLS, XLSX, and repaired XLSX and prepared a focused fix with regression tests. No model or remote service is needed. AI assistance: OpenAI Codex.