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* python3-pandas: Upgrade 1.4.0 -> 1.4.1Leon Anavi2022-02-241-0/+26
Upgrade to release 1.4.1: - Regression in Series.mask() with inplace=True and PeriodDtype and an incompatible other coercing to a common dtype instead of raising - Regression in assert_frame_equal() not respecting check_flags=False - Regression in DataFrame.loc() raising ValueError when indexing (getting values) on a MultiIndex with one level - Regression in Series.fillna() with downcast=False incorrectly downcasting object dtype - Regression in api.types.is_bool_dtype() raising an AttributeError when evaluating a categorical Series - Regression in DataFrame.iat() setting values leading to not propagating correctly in subsequent lookups - Regression when setting values with DataFrame.loc() losing Index name if DataFrame was empty before - Regression in join() with overlapping IntervalIndex raising an InvalidIndexError - Regression when setting values with Series.loc() raising with all False indexer and Series on the right hand side - Regression in read_sql() with a DBAPI2 connection that is not an instance of sqlite3.Connection incorrectly requiring SQLAlchemy be installed - Regression in DateOffset when constructing with an integer argument with no keywords (e.g. pd.DateOffset(n)) would behave like datetime.timedelta(days=0) - Fixed segfault in DataFrame.to_json() when dumping tz-aware datetimes in Python 3.10 - Stopped emitting unnecessary FutureWarning in DataFrame.sort_values() with sparse columns - Fixed window aggregations in DataFrame.rolling() and Series.rolling() to skip over unused elements - Fixed builtin highlighters in Styler to be responsive to NA with nullable dtypes - Bug in apply() with axis=1 raising an erroneous ValueError - Reverted performance speedup of DataFrame.corr() for method=pearson to fix precision regression Signed-off-by: Leon Anavi <leon.anavi@konsulko.com> Signed-off-by: Khem Raj <raj.khem@gmail.com> Signed-off-by: Trevor Gamblin <trevor.gamblin@windriver.com>