--- - branch: MAIN date: Mon Apr 15 08:10:23 UTC 2024 files: - new: '1.60' old: '1.59' path: pkgsrc/math/py-pandas/Makefile pathrev: pkgsrc/math/py-pandas/Makefile@1.60 type: modified - new: '1.42' old: '1.41' path: pkgsrc/math/py-pandas/distinfo pathrev: pkgsrc/math/py-pandas/distinfo@1.42 type: modified id: 20240415T081023Z.2020f2550d915f3d453769c1a9d02b779424a80d log: "py-pandas: updated to 2.2.2\n\nPandas 2.2.2 is now compatible with numpy 2.0\n\nPandas 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.\n\nOne major caveat is that arrays created with numpy 2.0窶å\x86± new StringDtype will convert to object dtyped arrays upon Series/DataFrame creation. Full support for numpy 2.0窶å\x86± StringDtype is expected to land in pandas 3.0.\n\nAs usual please report any bugs discovered to our issue tracker\n\nFixed regressions\n\nDataFrame.__dataframe__() was producing incorrect data buffers when the a column窶å\x86± type was a pandas nullable on with missing values (GH 56702)\nDataFrame.__dataframe__() was producing incorrect data buffers when the a column窶å\x86± type was a pyarrow nullable on with missing values (GH 57664)\nAvoid issuing a spurious DeprecationWarning when a custom DataFrame or Series subclass method is called (GH 57553)\nFixed regression in precision of to_datetime() with string and unit input (GH 57051)\nBug fixes\n\nDataFrame.__dataframe__() was producing incorrect data buffers when the column窶å\x86± type was nullable boolean (GH 55332)\nDataFrame.__dataframe__() was showing bytemask instead of bitmask for 'string[pyarrow]' validity buffer (GH 57762)\nDataFrame.__dataframe__() was showing non-null validity buffer (instead of None) 'string[pyarrow]' without missing values (GH 57761)\nDataFrame.to_sql() was failing to find the right table when using the schema argument (GH 57539)\n" module: pkgsrc subject: 'CVS commit: pkgsrc/math/py-pandas' unixtime: '1713168623' user: adam