Upgrade to release 1.3.2:
- Performance regression in DataFrame.isin() and Series.isin() for
nullable data types
- Regression in updating values of Series using boolean index,
created by using DataFrame.pop()
- Regression in DataFrame.from_records() with empty records
- Fixed regression in DataFrame.shift() where TypeError occurred
when shifting DataFrame created by concatenation of slices and
fills with values
- Regression in DataFrame.agg() when the func argument returned
lists and axis=1
- Regression in DataFrame.drop() does nothing if MultiIndex has
duplicates and indexer is a tuple or list of tuples
- Fixed regression where read_csv() raised a ValueError when
parameters names and prefix were both set to None
- Fixed regression in comparisons between Timestamp object and
datetime64 objects outside the implementation bounds for
nanosecond datetime64
- Fixed regression in Styler.highlight_min() and
Styler.highlight_max() where pandas.NA was not successfully
ignored
- Fixed regression in concat() where copy=False was not honored
in axis=1 Series concatenation
- Regression in Series.nlargest() and Series.nsmallest() with
nullable integer or float dtype
- Fixed regression in Series.quantile() with Int64Dtype
- Bug in read_excel() modifies the dtypes dictionary when reading
a file with duplicate columns
- 1D slices over extension types turn into N-dimensional slices
over ExtensionArrays
- Fixed bug in Series.rolling() and DataFrame.rolling() not
calculating window bounds correctly for the first row when
center=True and window is an offset that covers all the rows
- Styler.hide_columns() now hides the index name header row as
well as column headers
- Styler.set_sticky() has amended CSS to control the column/index
names and ensure the correct sticky positions
- Bug in de-serializing datetime indexes in PYTHONOPTIMIZED mode
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>
