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窶冱 new StringDtype will convert to object dtyped arrays upon Series/DataFrame creation. Full support for numpy 2.0窶冱 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窶冱 type was a pandas nullable on with missing values (GH 56702)
DataFrame.__dataframe__() was producing incorrect data buffers when the a column窶冱 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窶冱 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)


(adam)