Because Pandas is built on top of NumPy and NumPy has never had a proper NA value. I would call that a serious design problem in NumPy, but it seems to be difficult to fix. There have been multiple NEPs (NumPy Enhancement Proposals) over the years, but they haven't gone anywhere. Probably since things are not moving along in NumPy, a lot of development that should logically happen at the NumPy level is now happening in Pandas. But, I agree, I find it baffling how Python has gotten so big in data science and been around so long without having proper NA support.

https://numpy.org/neps/#deferred-and-superseded-neps