[Python] Pandas DtypeWarning "Columns have mixed types" for large CSV file (no error with one...

I am using Pandas (v2.2.3) to read/load a (relatively large) CSV file using read_csv(). The full file has about 500k lines.

The function throws a DtypeWarning stating that "Columns have mixed types" and suggests to either explicitly provide dtypes or use low_memory=false.

There is plenty of information about this warning available in the Internet (for example here: DtypeWarning: Columns have mixed types error in Pandas when loading csv) and I believe I understand what it means. The issue is that I believe the warning is not correct...

But, first of all, my code does provide dtypes. I have other CSV files where data is inconsistent and the same warning is silenced by providing dtypes. So in general everything is working as intended, it seems.

But not for this particular file.

I tried (basically using a "binary search" or "bisect" approach) to find the row(s) with different data to no avail. Finally I had (have) a file with 34926 lines that triggers the error. If i remove one line (and it does not seem to matter which one) the warning is not triggered any more.

As the data is confidential, I unfortunately cannot share the CSV file in question here.

Does anyone have an idea or pointer as to how (if at all) it is possible to avoid the warning (or rather, help Pandas to its job better)?
I know that I can ignore the warning (it's "just" a warning after all), but that feels a bit wrong?

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