- Update to 2.3.1
* This release includes some improvements and fixes to the future
string data type (preview feature for the upcoming pandas 3.0)
## Improvements and fixes for the StringDtype
* Comparisons between different string dtypes
* Index set operations ignore empty RangeIndex and object dtype
Index
## Bug fixes
* Bug in DataFrameGroupBy.min(), DataFrameGroupBy.max(),
Resampler.min(), Resampler.max() where all NA values of string
dtype would return float instead of string dtype (GH 60810)
* Bug in DataFrame.join() incorrectly downcasting object-dtype
indexes (GH 61771)
* Bug in DataFrame.sum() with axis=1, DataFrameGroupBy.sum() or
SeriesGroupBy.sum() with skipna=True, and Resampler.sum() with
all NA values of StringDtype resulted in 0 instead of the empty
string "" (GH 60229)
* Fixed bug in DataFrame.explode() and Series.explode() where
methods would fail with dtype="str" (GH 61623)
* Fixed bug in unpickling objects pickled in pandas versions
pre-2.3.0 that used StringDtype (GH 61763)
- Release 2.3.0
## Enhancements
* The semantics for the copy keyword in __array__ methods (i.e.
called when using np.array() or np.asarray() on pandas objects)
has been updated to work correctly with NumPy >= 2 (GH 57739)
* Series.str.decode() result now has StringDtype when
future.infer_string is True (GH 60709)
* to_hdf() and to_hdf() now round-trip with StringDtype (GH
60663)
OBS-URL: https://build.opensuse.org/request/show/1292272
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-pandas?expand=0&rev=77
* This release includes some improvements and fixes to the future
string data type (preview feature for the upcoming pandas 3.0)
## Improvements and fixes for the StringDtype
* Comparisons between different string dtypes
* Index set operations ignore empty RangeIndex and object dtype
Index
## Bug fixes
* Bug in DataFrameGroupBy.min(), DataFrameGroupBy.max(),
Resampler.min(), Resampler.max() where all NA values of string
dtype would return float instead of string dtype (GH 60810)
* Bug in DataFrame.join() incorrectly downcasting object-dtype
indexes (GH 61771)
* Bug in DataFrame.sum() with axis=1, DataFrameGroupBy.sum() or
SeriesGroupBy.sum() with skipna=True, and Resampler.sum() with
all NA values of StringDtype resulted in 0 instead of the empty
string "" (GH 60229)
* Fixed bug in DataFrame.explode() and Series.explode() where
methods would fail with dtype="str" (GH 61623)
* Fixed bug in unpickling objects pickled in pandas versions
pre-2.3.0 that used StringDtype (GH 61763)
- Release 2.3.0
## Enhancements
* The semantics for the copy keyword in __array__ methods (i.e.
called when using np.array() or np.asarray() on pandas objects)
has been updated to work correctly with NumPy >= 2 (GH 57739)
* Series.str.decode() result now has StringDtype when
future.infer_string is True (GH 60709)
* to_hdf() and to_hdf() now round-trip with StringDtype (GH
60663)
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=146
- Skip two tests that fail with Numpy 2.1.
- Prepare for Python 3.13, by skipping it if we aren't building for it.
- Update to 2.2.3
* Bug in eval() on complex including division /
discards imaginary part. (GH 21374)
* Minor fixes for numpy 2.1 compatibility. (GH 59444)
* Missing licenses for 3rd party dependencies were
added back into the wheels. (GH 58632)
- Drop pandas-pr58269-pyarrow16xpass.patch, merged upstream
- Drop pandas-pr58484-matplotlib.patch, merged upstream
- Drop pandas-pr59175-matplotlib.patch, merged upstream
- Drop pandas-pr59353-np2eval.patch, merged upstream
- Drop tests-npdev.patch, merged upstream
- Drop tests-timedelta.patch, merged upstream
- Refresh tests-nomkl.patch
- Renumber remaining patches
OBS-URL: https://build.opensuse.org/request/show/1218705
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-pandas?expand=0&rev=71
* Bug in eval() on complex including division /
discards imaginary part. (GH 21374)
* Minor fixes for numpy 2.1 compatibility. (GH 59444)
* Missing licenses for 3rd party dependencies were
added back into the wheels. (GH 58632)
- Drop pandas-pr58269-pyarrow16xpass.patch, merged upstream
- Drop pandas-pr58484-matplotlib.patch, merged upstream
- Drop pandas-pr59175-matplotlib.patch, merged upstream
- Drop pandas-pr59353-np2eval.patch, merged upstream
- Drop tests-npdev.patch, merged upstream
- Drop tests-timedelta.patch, merged upstream
- Refresh tests-nomkl.patch
- Renumber remaining patches
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=131
- Add pandas-pr58269-pyarrow16xpass.patch
(gh#pandas-dev/pandas!58269)
- Add pandas-pr58720-xarray-dp.patch
(gh#pandas-dev/pandas!58720), which makes pandas compatible
with the modern xarray
- Add pandas-pr58484-matplotlib.patch
(gh#pandas-dev/pandas!58484), which makes pandas compatible
with the modern matplotlib
- Skip also test_plot_scatter_shape (gh#pandas-dev/pandas#58851)
OBS-URL: https://build.opensuse.org/request/show/1179390
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-pandas?expand=0&rev=66
- Update 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)
- Remove obsolete python39 multibuild
- Add pandas-pr58269-pyarrow16xpass.patch
gh#pandas-dev/pandas#58269
OBS-URL: https://build.opensuse.org/request/show/1171775
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=114
- Update to 2.2.1
## Enhancements
* Added pyarrow pip extra so users can install pandas and pyarrow
with pip with pip install pandas[pyarrow] (#54466)
## Fixed regressions
* Fixed memory leak in `read_csv` (#57039)
* Fixed performance regression in `Series.combine_first` (#55845)
* Fixed regression causing overflow for near-minimum timestamps
(#57150)
* Fixed regression in `concat` changing long-standing behavior
that always sorted the non-concatenation axis when the axis was
a `DatetimeIndex` (#57006)
* Fixed regression in `merge_ordered` raising TypeError for
fill_method="ffill" and how="left" (#57010)
* Fixed regression in `pandas.testing.assert_series_equal`
defaulting to check_exact=True when checking the `Index`
(#57067)
* Fixed regression in `read_json` where an `Index` would be
returned instead of a `RangeIndex` (#57429)
* Fixed regression in `wide_to_long` raising an AttributeError
for string columns (#57066)
* Fixed regression in `.DataFrameGroupBy.idxmin`,
`.DataFrameGroupBy.idxmax`, `.SeriesGroupBy.idxmin`,
`.SeriesGroupBy.idxmax` ignoring the skipna argument (#57040)
* Fixed regression in `.DataFrameGroupBy.idxmin`,
`.DataFrameGroupBy.idxmax`, `.SeriesGroupBy.idxmin`,
`.SeriesGroupBy.idxmax` where values containing the minimum or
maximum value for the dtype could produce incorrect results
(#57040)
* Fixed regression in `CategoricalIndex.difference` raising
KeyError when other contains null values other than NaN
(#57318)
* Fixed regression in `DataFrame.groupby` raising ValueError when
grouping by a `Series` in some cases (#57276)
* Fixed regression in `DataFrame.loc` raising IndexError for
non-unique, masked dtype indexes where result has more than
10,000 rows (#57027)
* Fixed regression in `DataFrame.loc` which was unnecessarily
throwing "incompatible dtype warning" when expanding with
partial row indexer and multiple columns (see PDEP6) (#56503)
* Fixed regression in `DataFrame.map` with na_action="ignore" not
being respected for NumPy nullable and `ArrowDtypes` (#57316)
* Fixed regression in `DataFrame.merge` raising ValueError for
certain types of 3rd-party extension arrays (#57316)
* Fixed regression in `DataFrame.query` with all NaT column with
object dtype (#57068)
* Fixed regression in `DataFrame.shift` raising AssertionError
for axis=1 and empty `DataFrame` (#57301)
* Fixed regression in `DataFrame.sort_index` not producing a
stable sort for a index with duplicates (#57151)
* Fixed regression in `DataFrame.to_dict` with orient='list' and
datetime or timedelta types returning integers (#54824)
* Fixed regression in `DataFrame.to_json` converting nullable
integers to floats (#57224)
* Fixed regression in `DataFrame.to_sql` when method="multi" is
passed and the dialect type is not Oracle (#57310)
* Fixed regression in `DataFrame.transpose` with nullable
extension dtypes not having F-contiguous data potentially
causing exceptions when used (#57315)
* Fixed regression in `DataFrame.update` emitting incorrect
warnings about downcasting (#57124)
* Fixed regression in `DataFrameGroupBy.idxmin`,
`DataFrameGroupBy.idxmax`, `SeriesGroupBy.idxmin`,
`SeriesGroupBy.idxmax` ignoring the skipna argument (#57040)
* Fixed regression in `DataFrameGroupBy.idxmin`,
`DataFrameGroupBy.idxmax`, `SeriesGroupBy.idxmin`,
`SeriesGroupBy.idxmax` where values containing the minimum or
maximum value for the dtype could produce incorrect results
(#57040)
* Fixed regression in `ExtensionArray.to_numpy` raising for
non-numeric masked dtypes (#56991)
* Fixed regression in `Index.join` raising TypeError when joining
an empty index to a non-empty index containing mixed dtype
values (#57048)
* Fixed regression in `Series.astype` introducing decimals when
converting from integer with missing values to string dtype
(#57418)
* Fixed regression in `Series.pct_change` raising a ValueError
for an empty `Series` (#57056)
* Fixed regression in `Series.to_numpy` when dtype is given as
float and the data contains NaNs (#57121)
* Fixed regression in addition or subtraction of `DateOffset`
objects with millisecond components to datetime64 `Index`,
`Series`, or `DataFrame` (#57529)
## Bug fixes
* Fixed bug in `pandas.api.interchange.from_dataframe` which was
raising for Nullable integers (#55069)
* Fixed bug in `pandas.api.interchange.from_dataframe` which was
raising for empty inputs (#56700)
* Fixed bug in `pandas.api.interchange.from_dataframe` which
wasn't converting columns names to strings (#55069)
* Fixed bug in `DataFrame.__getitem__` for empty `DataFrame` with
Copy-on-Write enabled (#57130)
* Fixed bug in `PeriodIndex.asfreq` which was silently converting
frequencies which are not supported as period frequencies
instead of raising an error (#56945)
## Note
* The DeprecationWarning that was raised when pandas was imported
without PyArrow being installed has been removed. This decision
was made because the warning was too noisy for too many users
and a lot of feedback was collected about the decision to make
PyArrow a required dependency. Pandas is currently considering
the decision whether or not PyArrow should be added as a hard
dependency in 3.0. Interested users can follow the discussion
here.
* Added the argument skipna to `DataFrameGroupBy.first`,
`DataFrameGroupBy.last`, `SeriesGroupBy.first`, and
`SeriesGroupBy.last`; achieving skipna=False used to be
available via `DataFrameGroupBy.nth`, but the behavior was
changed in pandas 2.0.0 (#57019)
* Added the argument skipna to `Resampler.first`,
`Resampler.last` (#57019)
- Release notes for 2.2.0
* For full changelog see
https://github.com/pandas-dev/pandas/blob/main/doc/source/whatsnew/v2.2.0.rst
## Enhancements
* ADBC Driver support in to_sql and read_sql
* Create a pandas Series based on one or more conditions
* to_numpy for NumPy nullable and Arrow types converts to
suitable NumPy dtype
* Series.struct accessor for PyArrow structured data
* Series.list accessor for PyArrow list data
* Calamine engine for `read_excel`
## Notable bug fixes
* `merge` and `DataFrame.join` now consistently follow documented
sort behavior
* `merge` and `DataFrame.join` no longer reorder levels when
levels differ
* Increased minimum versions for dependencies
## Deprecations
* Chained assignment
* Deprecate aliases M, Q, Y, etc. in favour of ME, QE, YE, etc.
for offsets
* Deprecated automatic downcasting
- Simplify flavor test setup: obs can evaluate %{shrink:} now
OBS-URL: https://build.opensuse.org/request/show/1152058
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=110
- Update to 2.1.4
## Fixed regressions
* Fixed regression when trying to read a pickled pandas DataFrame
from pandas 1.3 (GH 55137)
## Bug fixes
* Bug in Series constructor raising DeprecationWarning when index
is a list of Series (GH 55228)
* Bug in Series when trying to cast date-like string inputs to
ArrowDtype of pyarrow.timestamp (GH 56266)
* Bug in DataFrame.apply() where passing raw=True ignored args
passed to the applied function (GH 55753)
* Bug in Index.__getitem__() returning wrong result for Arrow
dtypes and negative stepsize (GH 55832)
* Fixed bug in to_numeric() converting to extension dtype for
string[pyarrow_numpy] dtype (GH 56179)
* Fixed bug in DataFrameGroupBy.min() and DataFrameGroupBy.max()
not preserving extension dtype for empty object (GH 55619)
* Fixed bug in DataFrame.__setitem__() casting Index with
object-dtype to PyArrow backed strings when infer_string option
is set (GH 55638)
* Fixed bug in DataFrame.to_hdf() raising when columns have
StringDtype (GH 55088)
* Fixed bug in Index.insert() casting object-dtype to PyArrow
backed strings when infer_string option is set (GH 55638)
* Fixed bug in Series.__ne__() resulting in False for comparison
between NA and string value for dtype="string[pyarrow_numpy]"
(GH 56122)
* Fixed bug in Series.mode() not keeping object dtype when
infer_string is set (GH 56183)
* Fixed bug in Series.reset_index() not preserving object dtype
when infer_string is set (GH 56160)
* Fixed bug in Series.str.split() and Series.str.rsplit() when
pat=None for ArrowDtype with pyarrow.string (GH 56271)
* Fixed bug in Series.str.translate() losing object dtype when
string option is set (GH 56152)
- Go back to Cython0, it has NOT been unpinned by upstream released
version
* https://github.com/pandas-dev/pandas/blob/v2.1.4/pyproject.toml#L8
* See also gh#jsonpickle/jsonpickle#460
OBS-URL: https://build.opensuse.org/request/show/1133481
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=104
- Update to 2.1.3:
* Reverted deprecation of fill_method=None in DataFrame.pct_change(),
Series.pct_change(), DataFrameGroupBy.pct_change(), and
SeriesGroupBy.pct_change(); the values 'backfill', 'bfill', 'pad', and
'ffill' are still deprecated
* Fixed regressions
+ Fixed infinite recursion from operations that return a new object on
some DataFrame subclasses
+ Fixed regression in DataFrame.join() where result has missing values
and dtype is arrow backed string
+ Fixed regression in rolling() where non-nanosecond index or on column
would produce incorrect results
+ Fixed regression in DataFrame.resample() which was extrapolating back
to origin when origin was outside its bounds
+ Fixed regression in DataFrame.sort_index() which was not sorting
correctly when the index was a sliced MultiIndex
+ Fixed regression in DataFrameGroupBy.agg() and SeriesGroupBy.agg()
where if the option compute.use_numba was set to True, groupby methods
not supported by the numba engine would raise a TypeError
+ Fixed performance regression with wide DataFrames, typically
involving methods where all columns were accessed individually
+ Fixed regression in merge_asof() raising TypeError for by with
datetime and timedelta dtypes
+ Fixed regression in read_parquet() when reading a file with a string
column consisting of more than 2 GB of string data and using the
"string" dtype
+ Fixed regression in DataFrame.to_sql() not roundtripping datetime
columns correctly for sqlite when using detect_types
+ Fixed regression in construction of certain DataFrame or Series
subclasses
OBS-URL: https://build.opensuse.org/request/show/1130126
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-pandas?expand=0&rev=58
* Reverted deprecation of fill_method=None in DataFrame.pct_change(),
Series.pct_change(), DataFrameGroupBy.pct_change(), and
SeriesGroupBy.pct_change(); the values 'backfill', 'bfill', 'pad', and
'ffill' are still deprecated
* Fixed regressions
+ Fixed infinite recursion from operations that return a new object on
some DataFrame subclasses
+ Fixed regression in DataFrame.join() where result has missing values
and dtype is arrow backed string
+ Fixed regression in rolling() where non-nanosecond index or on column
would produce incorrect results
+ Fixed regression in DataFrame.resample() which was extrapolating back
to origin when origin was outside its bounds
+ Fixed regression in DataFrame.sort_index() which was not sorting
correctly when the index was a sliced MultiIndex
+ Fixed regression in DataFrameGroupBy.agg() and SeriesGroupBy.agg()
where if the option compute.use_numba was set to True, groupby methods
not supported by the numba engine would raise a TypeError
+ Fixed performance regression with wide DataFrames, typically
involving methods where all columns were accessed individually
+ Fixed regression in merge_asof() raising TypeError for by with
datetime and timedelta dtypes
+ Fixed regression in read_parquet() when reading a file with a string
column consisting of more than 2 GB of string data and using the
"string" dtype
+ Fixed regression in DataFrame.to_sql() not roundtripping datetime
columns correctly for sqlite when using detect_types
+ Fixed regression in construction of certain DataFrame or Series
subclasses
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=102
- Update to 2.1.1
## Fixed regressions
* Fixed regression in concat() when DataFrame ‘s have two
different extension dtypes (GH 54848)
* Fixed regression in merge() when merging over a PyArrow string
index (GH 54894)
* Fixed regression in read_csv() when usecols is given and dtypes
is a dict for engine="python" (GH 54868)
* Fixed regression in read_csv() when delim_whitespace is True
(GH 54918, GH 54931)
* Fixed regression in GroupBy.get_group() raising for axis=1 (GH
54858)
* Fixed regression in DataFrame.__setitem__() raising
AssertionError when setting a Series with a partial MultiIndex
(GH 54875)
* Fixed regression in DataFrame.filter() not respecting the order
of elements for filter (GH 54980)
* Fixed regression in DataFrame.to_sql() not roundtripping
datetime columns correctly for sqlite (GH 54877)
* Fixed regression in DataFrameGroupBy.agg() when aggregating a
DataFrame with duplicate column names using a dictionary (GH
55006)
* Fixed regression in MultiIndex.append() raising when appending
overlapping IntervalIndex levels (GH 54934)
* Fixed regression in Series.drop_duplicates() for PyArrow
strings (GH 54904)
* Fixed regression in Series.interpolate() raising when
fill_value was given (GH 54920)
* Fixed regression in Series.value_counts() raising for numeric
data if bins was specified (GH 54857)
* Fixed regression in comparison operations for PyArrow backed
columns not propagating exceptions correctly (GH 54944)
* Fixed regression when comparing a Series with datetime64 dtype
with None (GH 54870)
## Bug fixes
* Fixed bug for ArrowDtype raising NotImplementedError for
fixed-size list (GH 55000)
* Fixed bug in DataFrame.stack() with future_stack=True and
columns a non-MultiIndex consisting of tuples (GH 54948)
* Fixed bug in Series.dt.tz() with ArrowDtype where a string was
returned instead of a tzinfo object (GH 55003)
* Fixed bug in Series.pct_change() and DataFrame.pct_change()
showing unnecessary FutureWarning (GH 54981)
## Other
* Reverted the deprecation that disallowed Series.apply()
returning a DataFrame when the passed-in callable returns a
Series object (GH 52116)
- Drop pandas-pr55073-pyarrow13.patch merged upstream
OBS-URL: https://build.opensuse.org/request/show/1116287
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=98
