Log Message:
py-pandas: updated to 2.2.2

Pandas 2.2.2 is now compatible with numpy 2.0

Pandas 2.2.2 is the first version of pandas that is generally compatible with \ 
the upcoming numpy 2.0 release, and wheels for pandas 2.2.2 will work with both \ 
numpy 1.x and 2.x.

One major caveat is that arrays created with numpy 2.0’s new StringDtype will \ 
convert to object dtyped arrays upon Series/DataFrame creation. Full support for \ 
numpy 2.0’s StringDtype is expected to land in pandas 3.0.

As usual please report any bugs discovered to our issue tracker

Fixed regressions

DataFrame.__dataframe__() was producing incorrect data buffers when the a \ 
column’s type was a pandas nullable on with missing values (GH 56702)
DataFrame.__dataframe__() was producing incorrect data buffers when the a \ 
column’s type was a pyarrow nullable on with missing values (GH 57664)
Avoid issuing a spurious DeprecationWarning when a custom DataFrame or Series \ 
subclass method is called (GH 57553)
Fixed regression in precision of to_datetime() with string and unit input (GH 57051)
Bug fixes

DataFrame.__dataframe__() was producing incorrect data buffers when the \ 
column’s type was nullable boolean (GH 55332)
DataFrame.__dataframe__() was showing bytemask instead of bitmask for \ 
'string[pyarrow]' validity buffer (GH 57762)
DataFrame.__dataframe__() was showing non-null validity buffer (instead of None) \ 
'string[pyarrow]' without missing values (GH 57761)
DataFrame.to_sql() was failing to find the right table when using the schema \ 
argument (GH 57539)