Simon Hawkins

@mroeschke > * Deprecate the NumPy nullable types just to be clear, Int, Float, Boolean and pd.NA variants of StringArray only? > Deprecate mixing Arrow types and Numpy types in...

Thanks @jorisvandenbossche > 2\. General approach of the "PyArrow dtypes": This aligns with my expectation of the future direction of pandas. Do we have any umbrella discussion anywhere that could...

> FWIW, the early model of `ArrowDtype` almost followed a variant of the `StringDtype` model ([#46972](https://github.com/pandas-dev/pandas/pull/46972)). I have come to like the benefits of the current `ArrowDtype` (probably with some...

> > does that include numpy object type? > > I would say yes. ```python df = pd.DataFrame( { "int": pd.Series([1, 2, 3], dtype=pd.ArrowDtype(pa.int64())), "str": pd.Series(["a", "b", pd.NA], dtype=pd.ArrowDtype(pa.string())), }...

> 2\. I think at least initially it makes sense that if a user is specific about the dtype they want to use (e.g. `Series([1, 2], dtype="Int32")`) we let them...

@jorisvandenbossche @seberg are you happy to close this (and the numpy issue) as duplicate/fixed, or are additional tests needed to close. The two code samples in this discussion are now...

@Dr-Irv did #60170 also close this?

no problem. thanks for the update. incidentally have you tried WSL? I have a windows laptop but have not used any dev tools on Windows itself (except VS Code) for...

@chaarvii Thanks for the PR. Closing to clear queue. we can reopen if you're still interested in working on this.

reopening as I think this *could* be fixed on the pandas side, and without further investigation, suspect that it is an bug in pandas with the implementation of the numpy...