Accepting request 1304697 from devel:languages:python:numeric

- update to 2.3.2:
  * Fix to_json() with orient="table" to correctly use the
    “string” type in the JSON Table Schema for StringDtype columns
  * Boolean operations (|, &, ^) with bool-dtype objects on the
    left and StringDtype objects on the right now cast the string
    to bool, with a deprecation warning
  * Fixed match(), fullmatch() and contains() string methods with
    compiled regex for the Arrow-backed string dtype
  * Bug in Series.replace() and DataFrame.replace() inconsistently
    replacing matching values when missing values are present
    for string dtypes

- Change skipped tests to also support Python 3.13.
- Skip two tests that fail with Numpy 2.1.
- Prepare for Python 3.13, by skipping it if we aren't building for it.
- enable py312 testing, remove py39 testing
    RangeIndex
    the "c" and "python" engines
  * Bug in Series.str.split() and Series.str.rsplit() with expand=True
    (GH42915)
  * Fixed regression in DataFrame.groupby.rolling.cov() and
  * The deprecated attributes _AXIS_NAMES and _AXIS_NUMBERS of
  * Bumped minimum fastparquet version to 0.4.0 to avoid
  * Bumped minimum pymysql version to 0.8.1 to avoid test failures
  * Added reference to backwards incompatible check_freq arg of
    testing.assert_frame_equal() and testing.assert_series_equal()
  * WARNING:
    no longer maintained. The xlrd package is now only for reading
      Previously, the default argument engine=None to read_excel()
    would result in using the xlrd engine in many cases, including

OBS-URL: https://build.opensuse.org/request/show/1304697
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-pandas?expand=0&rev=78

_multibuild

@@ -2,4 +2,5 @@
   <package>test-py310</package>
   <package>test-py311</package>
   <package>test-py312</package>
+  <package>test-py313</package>
 </multibuild>

_service

@@ -1,16 +1,16 @@
 <services>
-  <service name="tar_scm" mode="disabled">
+  <service name="tar_scm" mode="manual">
     <param name="url">https://github.com/pandas-dev/pandas.git</param>
     <param name="scm">git</param>
-    <param name="revision">v2.2.2</param>
+    <param name="revision">v2.3.2</param>
     <param name="versionformat">@PARENT_TAG@</param>
     <param name="versionrewrite-pattern">v(.*)</param>
     <param name="filename">pandas</param>
     <param name="package-meta">yes</param>
   </service>
-  <service name="recompress" mode="disabled">
+  <service name="recompress" mode="manual">
     <param name="file">*.tar</param>
     <param name="compression">gz</param>
   </service>
-  <service name="set_version" mode="disabled" />
+  <service name="set_version" mode="manual" />
 </services>

pandas-2.2.2.tar.gz

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8f044538e419c7d5c03434c96b1439cbd88701dcd02d6a79b08947fbb656c2f4
-size 50782448

pandas-2.3.2.tar.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd1680a92a849ea183199f53098f0a9cc0083a2893ef31c597defdd4a10bd7d8
+size 406331098

pandas-pr58269-pyarrow16xpass.patch

@@ -1,40 +0,0 @@
-From 1828b62ee913da44ec4402642ef7baaafeb65677 Mon Sep 17 00:00:00 2001
-From: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>
-Date: Mon, 15 Apr 2024 09:47:31 -1000
-Subject: [PATCH] Backport PR #58268: CI/TST: Unxfail
- test_slice_locs_negative_step Pyarrow test
-
----
- pandas/tests/indexes/object/test_indexing.py | 12 +-----------
- 1 file changed, 1 insertion(+), 11 deletions(-)
-
-diff --git a/pandas/tests/indexes/object/test_indexing.py b/pandas/tests/indexes/object/test_indexing.py
-index 443cacf94d239..ebf9dac715f8d 100644
---- a/pandas/tests/indexes/object/test_indexing.py
-+++ b/pandas/tests/indexes/object/test_indexing.py
-@@ -7,7 +7,6 @@
-     NA,
-     is_matching_na,
- )
--from pandas.compat import pa_version_under16p0
- import pandas.util._test_decorators as td
- 
- import pandas as pd
-@@ -201,16 +200,7 @@ class TestSliceLocs:
-             (pd.IndexSlice["m":"m":-1], ""),  # type: ignore[misc]
-         ],
-     )
--    def test_slice_locs_negative_step(self, in_slice, expected, dtype, request):
--        if (
--            not pa_version_under16p0
--            and dtype == "string[pyarrow_numpy]"
--            and in_slice == slice("a", "a", -1)
--        ):
--            request.applymarker(
--                pytest.mark.xfail(reason="https://github.com/apache/arrow/issues/40642")
--            )
--
-+    def test_slice_locs_negative_step(self, in_slice, expected, dtype):
-         index = Index(list("bcdxy"), dtype=dtype)
- 
-         s_start, s_stop = index.slice_locs(in_slice.start, in_slice.stop, in_slice.step)

pandas-pr58484-matplotlib.patch

@@ -1,71 +0,0 @@
-From 0cab756077f5291f8d6a7fcfacaf374f62b866a0 Mon Sep 17 00:00:00 2001
-From: Elliott Sales de Andrade <quantum.analyst@gmail.com>
-Date: Mon, 29 Apr 2024 23:11:21 -0400
-Subject: [PATCH 1/2] Remove deprecated plot_date calls
-
-These were deprecated in Matplotlib 3.9.
----
- pandas/tests/plotting/test_datetimelike.py | 10 ++++------
- 1 file changed, 4 insertions(+), 6 deletions(-)
-
-diff --git a/pandas/tests/plotting/test_datetimelike.py b/pandas/tests/plotting/test_datetimelike.py
-index 6b709522bab70..b91bde41bf4c4 100644
---- a/pandas/tests/plotting/test_datetimelike.py
-+++ b/pandas/tests/plotting/test_datetimelike.py
-@@ -1432,13 +1432,11 @@ def test_mpl_nopandas(self):
-         values1 = np.arange(10.0, 11.0, 0.5)
-         values2 = np.arange(11.0, 12.0, 0.5)
- 
--        kw = {"fmt": "-", "lw": 4}
--
-         _, ax = mpl.pyplot.subplots()
--        ax.plot_date([x.toordinal() for x in dates], values1, **kw)
--        ax.plot_date([x.toordinal() for x in dates], values2, **kw)
--
--        line1, line2 = ax.get_lines()
-+        line1, line2, = ax.plot(
-+            [x.toordinal() for x in dates], values1, "-",
-+            [x.toordinal() for x in dates], values2, "-",
-+            linewidth=4)
- 
-         exp = np.array([x.toordinal() for x in dates], dtype=np.float64)
-         tm.assert_numpy_array_equal(line1.get_xydata()[:, 0], exp)
-
-From 6d6574c4e71e3bab91503f85c8aa80c927785865 Mon Sep 17 00:00:00 2001
-From: "pre-commit-ci[bot]"
- <66853113+pre-commit-ci[bot]@users.noreply.github.com>
-Date: Tue, 30 Apr 2024 16:47:26 +0000
-Subject: [PATCH 2/2] [pre-commit.ci] auto fixes from pre-commit.com hooks
-
-for more information, see https://pre-commit.ci
----
- pandas/tests/plotting/test_datetimelike.py | 16 ++++++++++++----
- 1 file changed, 12 insertions(+), 4 deletions(-)
-
-diff --git a/pandas/tests/plotting/test_datetimelike.py b/pandas/tests/plotting/test_datetimelike.py
-index b91bde41bf4c4..4b4eeada58366 100644
---- a/pandas/tests/plotting/test_datetimelike.py
-+++ b/pandas/tests/plotting/test_datetimelike.py
-@@ -1433,10 +1433,18 @@ def test_mpl_nopandas(self):
-         values2 = np.arange(11.0, 12.0, 0.5)
- 
-         _, ax = mpl.pyplot.subplots()
--        line1, line2, = ax.plot(
--            [x.toordinal() for x in dates], values1, "-",
--            [x.toordinal() for x in dates], values2, "-",
--            linewidth=4)
-+        (
-+            line1,
-+            line2,
-+        ) = ax.plot(
-+            [x.toordinal() for x in dates],
-+            values1,
-+            "-",
-+            [x.toordinal() for x in dates],
-+            values2,
-+            "-",
-+            linewidth=4,
-+        )
- 
-         exp = np.array([x.toordinal() for x in dates], dtype=np.float64)
-         tm.assert_numpy_array_equal(line1.get_xydata()[:, 0], exp)

pandas-pr59175-matplotlib.patch

@@ -1,29 +0,0 @@
-From d4e803caf7aabd464f6fb1d43ef39903911a3cec Mon Sep 17 00:00:00 2001
-From: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>
-Date: Wed, 3 Jul 2024 06:45:24 -1000
-Subject: [PATCH] Backport PR #59168: TST: Address UserWarning in matplotlib
- test
-
----
- pandas/plotting/_matplotlib/core.py | 8 +++++++-
- 1 file changed, 7 insertions(+), 1 deletion(-)
-
-diff --git a/pandas/plotting/_matplotlib/core.py b/pandas/plotting/_matplotlib/core.py
-index 2979903edf360..52382d9f7d572 100644
---- a/pandas/plotting/_matplotlib/core.py
-+++ b/pandas/plotting/_matplotlib/core.py
-@@ -893,7 +893,13 @@ def _make_legend(self) -> None:
-         elif self.subplots and self.legend:
-             for ax in self.axes:
-                 if ax.get_visible():
--                    ax.legend(loc="best")
-+                    with warnings.catch_warnings():
-+                        warnings.filterwarnings(
-+                            "ignore",
-+                            "No artists with labels found to put in legend.",
-+                            UserWarning,
-+                        )
-+                        ax.legend(loc="best")
- 
-     @final
-     @staticmethod

pandas-pr59353-np2eval.patch

@@ -1,174 +0,0 @@
-diff --git a/pandas/_testing/__init__.py b/pandas/_testing/__init__.py
-index 361998db8e..87d419e2db 100644
---- a/pandas/_testing/__init__.py
-+++ b/pandas/_testing/__init__.py
-@@ -111,6 +111,7 @@ ALL_FLOAT_DTYPES: list[Dtype] = [*FLOAT_NUMPY_DTYPES, *FLOAT_EA_DTYPES]
- 
- COMPLEX_DTYPES: list[Dtype] = [complex, "complex64", "complex128"]
- STRING_DTYPES: list[Dtype] = [str, "str", "U"]
-+COMPLEX_FLOAT_DTYPES: list[Dtype] = [*COMPLEX_DTYPES, *FLOAT_NUMPY_DTYPES]
- 
- DATETIME64_DTYPES: list[Dtype] = ["datetime64[ns]", "M8[ns]"]
- TIMEDELTA64_DTYPES: list[Dtype] = ["timedelta64[ns]", "m8[ns]"]
-diff --git a/pandas/conftest.py b/pandas/conftest.py
-index 7c35dfdde9..10134c90f8 100644
---- a/pandas/conftest.py
-+++ b/pandas/conftest.py
-@@ -1403,6 +1403,21 @@ def complex_dtype(request):
-     return request.param
- 
- 
-+@pytest.fixture(params=tm.COMPLEX_FLOAT_DTYPES)
-+def complex_or_float_dtype(request):
-+    """
-+    Parameterized fixture for complex and numpy float dtypes.
-+
-+    * complex
-+    * 'complex64'
-+    * 'complex128'
-+    * float
-+    * 'float32'
-+    * 'float64'
-+    """
-+    return request.param
-+
-+
- @pytest.fixture(params=tm.SIGNED_INT_NUMPY_DTYPES)
- def any_signed_int_numpy_dtype(request):
-     """
-diff --git a/pandas/core/computation/expr.py b/pandas/core/computation/expr.py
-index b5861fbaeb..d642c37cea 100644
---- a/pandas/core/computation/expr.py
-+++ b/pandas/core/computation/expr.py
-@@ -31,7 +31,6 @@ from pandas.core.computation.ops import (
-     UNARY_OPS_SYMS,
-     BinOp,
-     Constant,
--    Div,
-     FuncNode,
-     Op,
-     Term,
-@@ -370,7 +369,7 @@ class BaseExprVisitor(ast.NodeVisitor):
-         "Add",
-         "Sub",
-         "Mult",
--        None,
-+        "Div",
-         "Pow",
-         "FloorDiv",
-         "Mod",
-@@ -533,9 +532,6 @@ class BaseExprVisitor(ast.NodeVisitor):
-         left, right = self._maybe_downcast_constants(left, right)
-         return self._maybe_evaluate_binop(op, op_class, left, right)
- 
--    def visit_Div(self, node, **kwargs):
--        return lambda lhs, rhs: Div(lhs, rhs)
--
-     def visit_UnaryOp(self, node, **kwargs):
-         op = self.visit(node.op)
-         operand = self.visit(node.operand)
-diff --git a/pandas/core/computation/ops.py b/pandas/core/computation/ops.py
-index 95ac20ba39..ea8b1c0457 100644
---- a/pandas/core/computation/ops.py
-+++ b/pandas/core/computation/ops.py
-@@ -332,31 +332,6 @@ for d in (_cmp_ops_dict, _bool_ops_dict, _arith_ops_dict):
-     _binary_ops_dict.update(d)
- 
- 
--def _cast_inplace(terms, acceptable_dtypes, dtype) -> None:
--    """
--    Cast an expression inplace.
--
--    Parameters
--    ----------
--    terms : Op
--        The expression that should cast.
--    acceptable_dtypes : list of acceptable numpy.dtype
--        Will not cast if term's dtype in this list.
--    dtype : str or numpy.dtype
--        The dtype to cast to.
--    """
--    dt = np.dtype(dtype)
--    for term in terms:
--        if term.type in acceptable_dtypes:
--            continue
--
--        try:
--            new_value = term.value.astype(dt)
--        except AttributeError:
--            new_value = dt.type(term.value)
--        term.update(new_value)
--
--
- def is_term(obj) -> bool:
-     return isinstance(obj, Term)
- 
-@@ -516,31 +491,6 @@ class BinOp(Op):
- def isnumeric(dtype) -> bool:
-     return issubclass(np.dtype(dtype).type, np.number)
- 
--
--class Div(BinOp):
--    """
--    Div operator to special case casting.
--
--    Parameters
--    ----------
--    lhs, rhs : Term or Op
--        The Terms or Ops in the ``/`` expression.
--    """
--
--    def __init__(self, lhs, rhs) -> None:
--        super().__init__("/", lhs, rhs)
--
--        if not isnumeric(lhs.return_type) or not isnumeric(rhs.return_type):
--            raise TypeError(
--                f"unsupported operand type(s) for {self.op}: "
--                f"'{lhs.return_type}' and '{rhs.return_type}'"
--            )
--
--        # do not upcast float32s to float64 un-necessarily
--        acceptable_dtypes = [np.float32, np.float64]
--        _cast_inplace(com.flatten(self), acceptable_dtypes, np.float64)
--
--
- UNARY_OPS_SYMS = ("+", "-", "~", "not")
- _unary_ops_funcs = (operator.pos, operator.neg, operator.invert, operator.invert)
- _unary_ops_dict = dict(zip(UNARY_OPS_SYMS, _unary_ops_funcs))
-diff --git a/pandas/tests/computation/test_eval.py b/pandas/tests/computation/test_eval.py
-index 17630f14b0..e8fad6b8cb 100644
---- a/pandas/tests/computation/test_eval.py
-+++ b/pandas/tests/computation/test_eval.py
-@@ -747,16 +747,26 @@ class TestTypeCasting:
-     @pytest.mark.parametrize("op", ["+", "-", "*", "**", "/"])
-     # maybe someday... numexpr has too many upcasting rules now
-     # chain(*(np.core.sctypes[x] for x in ['uint', 'int', 'float']))
--    @pytest.mark.parametrize("dt", [np.float32, np.float64])
-     @pytest.mark.parametrize("left_right", [("df", "3"), ("3", "df")])
--    def test_binop_typecasting(self, engine, parser, op, dt, left_right):
--        df = DataFrame(np.random.default_rng(2).standard_normal((5, 3)), dtype=dt)
-+    def test_binop_typecasting(
-+        self, engine, parser, op, complex_or_float_dtype, left_right, request
-+    ):
-+        # GH#21374
-+        dtype = complex_or_float_dtype
-+        df = DataFrame(np.random.default_rng(2).standard_normal((5, 3)), dtype=dtype)
-         left, right = left_right
-         s = f"{left} {op} {right}"
-         res = pd.eval(s, engine=engine, parser=parser)
--        assert df.values.dtype == dt
--        assert res.values.dtype == dt
--        tm.assert_frame_equal(res, eval(s))
-+        if dtype == "complex64" and engine == "numexpr":
-+            mark = pytest.mark.xfail(
-+                reason="numexpr issue with complex that are upcast "
-+                "to complex 128 "
-+                "https://github.com/pydata/numexpr/issues/492"
-+            )
-+            request.applymarker(mark)
-+        assert df.values.dtype == dtype
-+        assert res.values.dtype == dtype
-+        tm.assert_frame_equal(res, eval(s), check_exact=False)
- 
- 
- # -------------------------------------

pandas-pr61132-dropna.patch

@@ -0,0 +1,316 @@
+From 1e899afbd9ca20f4ce9d6f93e1f62c072be0ed23 Mon Sep 17 00:00:00 2001
+From: Gen Sato <52241300+halogen22@users.noreply.github.com>
+Date: Tue, 18 Mar 2025 01:33:40 +0900
+Subject: [PATCH] BUG: .mode(dropna=False) doesn't work with nullable integers
+ (#61132)
+
+* Fix dropna bug when mode
+
+* Fix test cases
+
+* Fix data type incompatible
+---
+ doc/source/whatsnew/v3.0.0.rst            |  1 +
+ pandas/_libs/hashtable_func_helper.pxi.in |  2 +-
+ pandas/core/algorithms.py                 | 12 +++---
+ pandas/core/arrays/base.py                |  5 ++-
+ pandas/core/arrays/categorical.py         |  2 +-
+ pandas/core/arrays/datetimelike.py        |  2 +-
+ pandas/core/arrays/masked.py              |  8 +---
+ pandas/core/series.py                     |  2 +-
+ pandas/tests/series/test_reductions.py    | 23 +++++++++++
+ pandas/tests/test_algos.py                | 47 +++++++++++++++--------
+ 10 files changed, 71 insertions(+), 33 deletions(-)
+
+Index: pandas-2.3.1/pandas/_libs/hashtable_func_helper.pxi.in
+===================================================================
+--- pandas-2.3.1.orig/pandas/_libs/hashtable_func_helper.pxi.in
++++ pandas-2.3.1/pandas/_libs/hashtable_func_helper.pxi.in
+@@ -443,7 +443,7 @@ def mode(ndarray[htfunc_t] values, bint
+ 
+     if na_counter > 0:
+         res_mask = np.zeros(j+1, dtype=np.bool_)
+-        res_mask[j] = True
++        res_mask[j] = (na_counter == max_count)
+     return modes[:j + 1], res_mask
+ 
+ 
+Index: pandas-2.3.1/pandas/core/algorithms.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/core/algorithms.py
++++ pandas-2.3.1/pandas/core/algorithms.py
+@@ -1022,7 +1022,7 @@ def duplicated(
+ 
+ def mode(
+     values: ArrayLike, dropna: bool = True, mask: npt.NDArray[np.bool_] | None = None
+-) -> ArrayLike:
++) -> tuple[np.ndarray, npt.NDArray[np.bool_]] | ExtensionArray:
+     """
+     Returns the mode(s) of an array.
+ 
+@@ -1035,7 +1035,7 @@ def mode(
+ 
+     Returns
+     -------
+-    np.ndarray or ExtensionArray
++    Union[Tuple[np.ndarray, npt.NDArray[np.bool_]], ExtensionArray]
+     """
+     values = _ensure_arraylike(values, func_name="mode")
+     original = values
+@@ -1049,8 +1049,10 @@ def mode(
+     values = _ensure_data(values)
+ 
+     npresult, res_mask = htable.mode(values, dropna=dropna, mask=mask)
+-    if res_mask is not None:
+-        return npresult, res_mask  # type: ignore[return-value]
++    if res_mask is None:
++        res_mask = np.zeros(npresult.shape, dtype=np.bool_)
++    else:
++        return npresult, res_mask
+ 
+     try:
+         npresult = safe_sort(npresult)
+@@ -1061,7 +1063,7 @@ def mode(
+         )
+ 
+     result = _reconstruct_data(npresult, original.dtype, original)
+-    return result
++    return result, res_mask
+ 
+ 
+ def rank(
+Index: pandas-2.3.1/pandas/core/arrays/base.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/core/arrays/base.py
++++ pandas-2.3.1/pandas/core/arrays/base.py
+@@ -2270,8 +2270,9 @@ class ExtensionArray:
+             Sorted, if possible.
+         """
+         # error: Incompatible return value type (got "Union[ExtensionArray,
+-        # ndarray[Any, Any]]", expected "Self")
+-        return mode(self, dropna=dropna)  # type: ignore[return-value]
++        # Tuple[np.ndarray, npt.NDArray[np.bool_]]", expected "Self")
++        result, _ = mode(self, dropna=dropna)
++        return result  # type: ignore[return-value]
+ 
+     def __array_ufunc__(self, ufunc: np.ufunc, method: str, *inputs, **kwargs):
+         if any(
+Index: pandas-2.3.1/pandas/core/arrays/categorical.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/core/arrays/categorical.py
++++ pandas-2.3.1/pandas/core/arrays/categorical.py
+@@ -2459,7 +2459,7 @@ class Categorical(NDArrayBackedExtension
+         if dropna:
+             mask = self.isna()
+ 
+-        res_codes = algorithms.mode(codes, mask=mask)
++        res_codes, _ = algorithms.mode(codes, mask=mask)
+         res_codes = cast(np.ndarray, res_codes)
+         assert res_codes.dtype == codes.dtype
+         res = self._from_backing_data(res_codes)
+Index: pandas-2.3.1/pandas/core/arrays/datetimelike.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/core/arrays/datetimelike.py
++++ pandas-2.3.1/pandas/core/arrays/datetimelike.py
+@@ -1669,7 +1669,7 @@ class DatetimeLikeArrayMixin(  # type: i
+         if dropna:
+             mask = self.isna()
+ 
+-        i8modes = algorithms.mode(self.view("i8"), mask=mask)
++        i8modes, _ = algorithms.mode(self.view("i8"), mask=mask)
+         npmodes = i8modes.view(self._ndarray.dtype)
+         npmodes = cast(np.ndarray, npmodes)
+         return self._from_backing_data(npmodes)
+Index: pandas-2.3.1/pandas/core/arrays/masked.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/core/arrays/masked.py
++++ pandas-2.3.1/pandas/core/arrays/masked.py
+@@ -1124,12 +1124,8 @@ class BaseMaskedArray(OpsMixin, Extensio
+         return Series(arr, index=index, name="count", copy=False)
+ 
+     def _mode(self, dropna: bool = True) -> Self:
+-        if dropna:
+-            result = mode(self._data, dropna=dropna, mask=self._mask)
+-            res_mask = np.zeros(result.shape, dtype=np.bool_)
+-        else:
+-            result, res_mask = mode(self._data, dropna=dropna, mask=self._mask)
+-        result = type(self)(result, res_mask)  # type: ignore[arg-type]
++        result, res_mask = mode(self._data, dropna=dropna, mask=self._mask)
++        result = type(self)(result, res_mask)
+         return result[result.argsort()]
+ 
+     @doc(ExtensionArray.equals)
+Index: pandas-2.3.1/pandas/core/series.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/core/series.py
++++ pandas-2.3.1/pandas/core/series.py
+@@ -2337,7 +2337,7 @@ class Series(base.IndexOpsMixin, NDFrame
+         # TODO: Add option for bins like value_counts()
+         values = self._values
+         if isinstance(values, np.ndarray):
+-            res_values = algorithms.mode(values, dropna=dropna)
++            res_values, _ = algorithms.mode(values, dropna=dropna)
+         else:
+             res_values = values._mode(dropna=dropna)
+ 
+Index: pandas-2.3.1/pandas/tests/series/test_reductions.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/tests/series/test_reductions.py
++++ pandas-2.3.1/pandas/tests/series/test_reductions.py
+@@ -51,6 +51,29 @@ def test_mode_nullable_dtype(any_numeric
+     tm.assert_series_equal(result, expected)
+ 
+ 
++def test_mode_nullable_dtype_edge_case(any_numeric_ea_dtype):
++    # GH##58926
++    ser = Series([1, 2, 3, 1], dtype=any_numeric_ea_dtype)
++    result = ser.mode(dropna=False)
++    expected = Series([1], dtype=any_numeric_ea_dtype)
++    tm.assert_series_equal(result, expected)
++
++    ser2 = Series([1, 1, 2, 3, pd.NA], dtype=any_numeric_ea_dtype)
++    result = ser2.mode(dropna=False)
++    expected = Series([1], dtype=any_numeric_ea_dtype)
++    tm.assert_series_equal(result, expected)
++
++    ser3 = Series([1, pd.NA, pd.NA], dtype=any_numeric_ea_dtype)
++    result = ser3.mode(dropna=False)
++    expected = Series([pd.NA], dtype=any_numeric_ea_dtype)
++    tm.assert_series_equal(result, expected)
++
++    ser4 = Series([1, 1, pd.NA, pd.NA], dtype=any_numeric_ea_dtype)
++    result = ser4.mode(dropna=False)
++    expected = Series([1, pd.NA], dtype=any_numeric_ea_dtype)
++    tm.assert_series_equal(result, expected)
++
++
+ def test_mode_infer_string():
+     # GH#56183
+     pytest.importorskip("pyarrow")
+Index: pandas-2.3.1/pandas/tests/test_algos.py
+===================================================================
+--- pandas-2.3.1.orig/pandas/tests/test_algos.py
++++ pandas-2.3.1/pandas/tests/test_algos.py
+@@ -1855,7 +1855,8 @@ class TestRank:
+ class TestMode:
+     def test_no_mode(self):
+         exp = Series([], dtype=np.float64, index=Index([], dtype=int))
+-        tm.assert_numpy_array_equal(algos.mode(np.array([])), exp.values)
++        result, _ = algos.mode(np.array([]))
++        tm.assert_numpy_array_equal(result, exp.values)
+ 
+     @pytest.mark.parametrize("dt", np.typecodes["AllInteger"] + np.typecodes["Float"])
+     def test_mode_single(self, dt):
+@@ -1868,20 +1869,24 @@ class TestMode:
+ 
+         ser = Series(data_single, dtype=dt)
+         exp = Series(exp_single, dtype=dt)
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+         ser = Series(data_multi, dtype=dt)
+         exp = Series(exp_multi, dtype=dt)
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+     def test_mode_obj_int(self):
+         exp = Series([1], dtype=int)
+-        tm.assert_numpy_array_equal(algos.mode(exp.values), exp.values)
++        result, _ = algos.mode(exp.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+ 
+         exp = Series(["a", "b", "c"], dtype=object)
+-        tm.assert_numpy_array_equal(algos.mode(exp.values), exp.values)
++        result, _ = algos.mode(exp.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+ 
+     @pytest.mark.parametrize("dt", np.typecodes["AllInteger"] + np.typecodes["Float"])
+     def test_number_mode(self, dt):
+@@ -1893,12 +1898,14 @@ class TestMode:
+ 
+         ser = Series(data_single, dtype=dt)
+         exp = Series(exp_single, dtype=dt)
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+         ser = Series(data_multi, dtype=dt)
+         exp = Series(exp_multi, dtype=dt)
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+     def test_strobj_mode(self):
+@@ -1907,7 +1914,8 @@ class TestMode:
+ 
+         ser = Series(data, dtype="c")
+         exp = Series(exp, dtype="c")
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+     @pytest.mark.parametrize("dt", [str, object])
+@@ -1920,7 +1928,8 @@ class TestMode:
+         if using_infer_string and dt is str:
+             tm.assert_extension_array_equal(algos.mode(ser.values), exp.values)
+         else:
+-            tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++            result, _ = algos.mode(ser.values)
++            tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+     def test_datelike_mode(self):
+@@ -1954,18 +1963,21 @@ class TestMode:
+     def test_mixed_dtype(self):
+         exp = Series(["foo"], dtype=object)
+         ser = Series([1, "foo", "foo"])
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+     def test_uint64_overflow(self):
+         exp = Series([2**63], dtype=np.uint64)
+         ser = Series([1, 2**63, 2**63], dtype=np.uint64)
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+         exp = Series([1, 2**63], dtype=np.uint64)
+         ser = Series([1, 2**63], dtype=np.uint64)
+-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
++        result, _ = algos.mode(ser.values)
++        tm.assert_numpy_array_equal(result, exp.values)
+         tm.assert_series_equal(ser.mode(), exp)
+ 
+     def test_categorical(self):
+@@ -1987,15 +1999,18 @@ class TestMode:
+     def test_index(self):
+         idx = Index([1, 2, 3])
+         exp = Series([1, 2, 3], dtype=np.int64)
+-        tm.assert_numpy_array_equal(algos.mode(idx), exp.values)
++        result, _ = algos.mode(idx)
++        tm.assert_numpy_array_equal(result, exp.values)
+ 
+         idx = Index([1, "a", "a"])
+         exp = Series(["a"], dtype=object)
+-        tm.assert_numpy_array_equal(algos.mode(idx), exp.values)
++        result, _ = algos.mode(idx)
++        tm.assert_numpy_array_equal(result, exp.values)
+ 
+         idx = Index([1, 1, 2, 3, 3])
+         exp = Series([1, 3], dtype=np.int64)
+-        tm.assert_numpy_array_equal(algos.mode(idx), exp.values)
++        result, _ = algos.mode(idx)
++        tm.assert_numpy_array_equal(result, exp.values)
+ 
+         idx = Index(
+             ["1 day", "1 day", "-1 day", "-1 day 2 min", "2 min", "2 min"],

python-pandas.changes

@@ -1,3 +1,181 @@
+-------------------------------------------------------------------
+Sun Sep 14 21:48:11 UTC 2025 - Dirk Müller <dmueller@suse.com>
+
+- update to 2.3.2:
+  * Fix to_json() with orient="table" to correctly use the
+    “string” type in the JSON Table Schema for StringDtype columns
+  * Boolean operations (|, &, ^) with bool-dtype objects on the
+    left and StringDtype objects on the right now cast the string
+    to bool, with a deprecation warning
+  * Fixed match(), fullmatch() and contains() string methods with
+    compiled regex for the Arrow-backed string dtype
+  * Bug in Series.replace() and DataFrame.replace() inconsistently
+    replacing matching values when missing values are present
+    for string dtypes
+
+-------------------------------------------------------------------
+Fri Jul 11 19:29:45 UTC 2025 - Ben Greiner <code@bnavigator.de>
+
+- 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)
+  * Improved repr of NumpyExtensionArray to account for NEP51 (GH
+    61085)
+  * The Series.str.decode() has gained the argument dtype to
+    control the dtype of the result (GH 60940)
+  * The cumsum(), cummin(), and cummax() reductions are now
+    implemented for StringDtype columns (GH 60633)
+  * The sum() reduction is now implemented for StringDtype columns
+    (GH 59853)
+  ## Deprecations
+  * Deprecated allowing non-bool values for na in str.contains(),
+    str.startswith(), and str.endswith() for dtypes that do not
+    already disallow these (GH 59615)
+  * Deprecated the "pyarrow_numpy" storage option for StringDtype
+    (GH 60152)
+  * The deprecation of setting the argument include_groups to True
+    in DataFrameGroupBy.apply() has been promoted from a
+    DeprecationWarning to FutureWarning; only False will be allowed
+    (GH 7155)
+  ## Bug fixes
+  ### Numeric
+  * Bug in Series.mode() and DataFrame.mode() with dropna=False
+    where not all dtypes would sort in the presence of NA values
+    (GH 60702)
+  * Bug in Series.round() where a TypeError would always raise with
+    object dtype (GH 61206)
+  ### Strings
+  * Bug in Series.__pos__() and DataFrame.__pos__() where an
+    Exception was not raised for StringDtype with storage="pyarrow"
+    (GH 60710)
+  * Bug in Series.rank() for StringDtype with storage="pyarrow"
+    that incorrectly returned integer results with method="average"
+    and raised an error if it would truncate results (GH 59768)
+  * Bug in Series.replace() with StringDtype when replacing with a
+    non-string value was not upcasting to object dtype (GH 60282)
+  * Bug in Series.str.center() with StringDtype with
+    storage="pyarrow" not matching the python behavior in corner
+    cases with an odd number of fill characters (GH 54792)
+  * Bug in Series.str.replace() when n < 0 for StringDtype with
+    storage="pyarrow" (GH 59628)
+  * Bug in Series.str.slice() with negative step with ArrowDtype
+    and StringDtype with storage="pyarrow" giving incorrect results
+    (GH 59710)
+  ### Indexing
+    Bug in Index.get_indexer() round-tripping through string dtype
+    when infer_string is enabled (GH 55834)
+  ### I/O
+  * Bug in DataFrame.to_excel() which stored decimals as strings
+    instead of numbers (GH 49598)
+  ### Other
+  * Fixed usage of inspect when the optional dependencies pyarrow
+    or jinja2 are not installed (GH 60196)
+- Drop patches:
+  * timedelta.patch
+  * pandas-pr60545-arrow-exception.patch
+  * pandas-pr60584-60586-mpl-vert.patch
+- Refresh dropna.patch to pandas-pr61132-dropna.patch
+  * gh#pandas-dev/pandas#61132
+
+-------------------------------------------------------------------
+Thu Mar 20 11:36:22 UTC 2025 - Markéta Machová <mmachova@suse.com>
+
+- Add dropna.patch and timedelta.patch to fix tests with Numpy 2.2
+
+-------------------------------------------------------------------
+Thu Feb 20 11:23:33 UTC 2025 - Ben Greiner <code@bnavigator.de>
+
+- Support pyarrow 19
+  * Add pandas-pr60545-arrow-exception.patch
+    gh#pandas-dev/pandas#60545
+  * Skip TestParquetPyArrow.test_roundtrip_decimal: Would require
+    gh#pandas-dev/pandas#60755 and all other backports of the new
+    string type system.
+
+-------------------------------------------------------------------
+Fri Feb  7 18:40:46 UTC 2025 - Ben Greiner <code@bnavigator.de>
+
+- Add pandas-pr60584-60586-mpl-vert.patch
+  * Fixes matplotlib deprecation errors in the test suite
+  * gh#pandas-dev/pandas#60584
+  * backported in gh#pandas-dev/pandas#60586
+
+-------------------------------------------------------------------
+Fri Dec 13 06:51:11 UTC 2024 - Steve Kowalik <steven.kowalik@suse.com>
+
+- Change skipped tests to also support Python 3.13.
+
+-------------------------------------------------------------------
+Wed Nov 27 12:26:36 UTC 2024 - Markéta Machová <mmachova@suse.com>
+
+- Drop tests-nomkl.patch and tests-wasm.patch, not needed anymore
+- Skip a test failing with new xarray
+
+------------------------------------------------------------------
+Fri Oct 25 05:19:49 UTC 2024 - Steve Kowalik <steven.kowalik@suse.com>
+
+- Skip two tests that fail with Numpy 2.1.
+
+-------------------------------------------------------------------
+Fri Oct 11 04:40:52 UTC 2024 - Steve Kowalik <steven.kowalik@suse.com>
+
+- Prepare for Python 3.13, by skipping it if we aren't building for it.
+
+-------------------------------------------------------------------
+Tue Oct  1 12:35:22 UTC 2024 - John Paul Adrian Glaubitz <adrian.glaubitz@suse.com>
+
+- 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
+
+-------------------------------------------------------------------
+Mon Sep 16 19:39:38 UTC 2024 - Markéta Machová <mmachova@suse.com>
+
+- Add bunch of patches to fix the testsuite with NumPy 2.1
+  * tests-wasm.patch
+  * tests-nomkl.patch
+  * tests-timedelta.patch
+  * tests-npdev.patch
+- Skip one test failing with new timezone, the patch would be too big
+
 -------------------------------------------------------------------
 Sun Sep  8 10:02:47 UTC 2024 - Ben Greiner <code@bnavigator.de>
 

python-pandas.spec

@@ -1,7 +1,7 @@
 #
 # spec file for package python-pandas
 #
-# Copyright (c) 2024 SUSE LLC
+# Copyright (c) 2025 SUSE LLC and contributors
 #
 # All modifications and additions to the file contributed by third parties
 # remain the property of their copyright owners, unless otherwise agreed
@@ -34,7 +34,13 @@
 %if "%{flavor}" != "test-py312"
 %define skip_python312 1
 %endif
-# Skip empty buildsets, last one is for sle15_python_module_pythons
+%if "%{flavor}" != "test-py313"
+%define skip_python313 1
+%endif
+%if "%{flavor}" != "test-py314"
+%define skip_python314 1
+%endif
+# Skip empty buildsets on tumbleweed or flavors other than python311 on leap with sle15_python_module_pythons
 %if "%{shrink:%{pythons}}" == "" || ("%pythons" == "python311" && 0%{?skip_python311})
 ExclusiveArch:  donotbuild
 %define python_module() %flavor-not-enabled-in-buildset-for-suse-%{?suse_version}
@@ -55,13 +61,13 @@ ExclusiveArch:  donotbuild
 # depend/not depend on python-pyarrow and apache-arrow [bsc#1218592]
 %bcond_without pyarrow
 
-%if %{suse_version} <= 1500
+%if 0%{?suse_version} && %{suse_version} <= 1500
 # requires __has_builtin with keywords
-%define gccver 13
+%define gccver 14
 %endif
 Name:           python-pandas%{psuffix}
 # Set version through _service
-Version:        2.2.2
+Version:        2.3.2
 Release:        0
 Summary:        Python data structures for data analysis, time series, and statistics
 License:        BSD-3-Clause
@@ -69,26 +75,20 @@ URL:            https://pandas.pydata.org/
 # SourceRepository: https://github.com/pandas-dev/pandas
 # Must be created by cloning through `osc service runall`: gh#pandas-dev/pandas#54903, gh#pandas-dev/pandas#54907
 Source0:        pandas-%{version}.tar.gz
-# PATCH-FIX-UPSTREAM pandas-pr58269-pyarrow16xpass.patch -- gh#pandas-dev/pandas#58269
+# PATCH-FIX-UPSTREAM pandas-pr61132-dropna.patch gh#pandas-dev/pandas#61132 BUG: .mode(dropna=False) doesn't work with nullable integers
-Patch0:         pandas-pr58269-pyarrow16xpass.patch
+Patch1:         pandas-pr61132-dropna.patch
-# PATCH-FIX-UPSTREAM pandas-pr58484-matplotlib.patch -- gh#pandas-dev/pandas#58484 mcepl@suse.com, make pandas compatible with the modern matplotlib
-Patch2:         pandas-pr58484-matplotlib.patch
-# PATCH-FIX-UPSTREAM pandas-pr59175-matplotlib.patch -- gh#pandas-dev/pandas#59175
-Patch3:         https://github.com/pandas-dev/pandas/pull/59175.patch#/pandas-pr59175-matplotlib.patch
-# PATCH-FIX-UPSTREAM pandas-pr59353-np2eval.patch -- gh#pandas-dev/pandas#59144 backported to 2.2, no new tests, see gh#pandas-dev/pandas#58548, gh#pandas-dev/pandas#59353
-Patch4:         pandas-pr59353-np2eval.patch
 %if !%{with test}
 BuildRequires:  %{python_module Cython >= 3.0.5}
 BuildRequires:  %{python_module devel >= 3.9}
 BuildRequires:  %{python_module meson-python >= 0.13.1}
-BuildRequires:  %{python_module numpy-devel >= 1.26}
+BuildRequires:  %{python_module numpy-devel >= 1.22.4}
 BuildRequires:  %{python_module pip}
 BuildRequires:  %{python_module versioneer-toml}
 BuildRequires:  %{python_module wheel}
 BuildRequires:  fdupes
 BuildRequires:  gcc%{?gccver}-c++
 BuildRequires:  git-core
-BuildRequires:  meson >= 1.2.1
+BuildRequires:  (meson >= 1.2.1 with meson < 2)
 %endif
 BuildRequires:  python-rpm-macros
 Requires:       python-python-dateutil >= 2.8.2
@@ -102,7 +102,7 @@ Requires:       python-numpy >= 1.22.4
 %if 0%{python_version_nodots} == 311
 Requires:       python-numpy >= 1.23.2
 %else
-Requires:       python-numpy >= 1.26
+Requires:       python-numpy >= 1.26.0
 %endif
 %endif
 # SECTION extras
@@ -209,7 +209,7 @@ provide speed improvements, especially when working with large data sets.
 %package computation
 Summary:        The python pandas[computation] extra
 Requires:       python-pandas = %{version}
-Requires:       python-scipy >= 1.10.0
+Requires:       python-scipy >= 1.12.0
 Requires:       python-xarray >= 2022.12.0
 BuildArch:      noarch
 
@@ -218,7 +218,7 @@ This package provides the [computation] extra for python-pandas
 
 %package fss
 Summary:        The python pandas[fss] extra
-Requires:       python-fsspec >= 2022.11
+Requires:       python-fsspec >= 2023.12.2
 Requires:       python-pandas = %{version}
 BuildArch:      noarch
 
@@ -410,7 +410,7 @@ Requires:       python-beautifulsoup4 >= 4.11.2
 Requires:       python-blosc
 %{?with_calamine:Requires:       python-calamine >= 0.1.7}
 %{?with_pyarrow:Requires:   python-fastparquet >= 2022.12}
-Requires:       python-fsspec >= 2022.11
+Requires:       python-fsspec >= 2023.12.2
 Requires:       python-gcsfs >= 2022.11
 Requires:       python-html5lib >= 1.1
 Requires:       python-hypothesis >= 6.46.1
@@ -426,7 +426,7 @@ Requires:       python-psycopg2 >= 2.9.6
 Requires:       python-pyreadstat >= 1.2.0
 Requires:       python-pytest >= 7.3.2
 Requires:       python-pytest-xdist >= 2.2.0
-Requires:       python-scipy >= 1.10.0
+Requires:       python-scipy >= 1.12.0
 Requires:       python-tables >= 3.8.0
 Requires:       python-tabulate >= 0.9
 Requires:       python-xarray >= 2022.12
@@ -514,13 +514,16 @@ SKIP_TESTS+=" or test_psycopg2_schema_support"
 SKIP_TESTS+=" or test_self_join_date_columns"
 # expects a dirty git revision from git repo
 SKIP_TESTS+=" or test_git_version"
-%if "%{flavor}" == "test-py312"
 # https://github.com/pandas-dev/pandas/pull/57391, proposed change is not necessarily the right one
+%if "%{flavor}" == "test-py312" || "%{flavor}" == "test-py313"
 SKIP_TESTS+=" or (test_scalar_unary and numexpr-pandas)"
 %endif
-# Numpy2: unexpected 'np.str_(...)' in error message
+# https://github.com/pandas-dev/pandas/pull/55901, not gonna merge this huge patch to fix one test failing with new timezone, will be included in 3.0
-SKIP_TESTS+=" or test_group_subplot_invalid_column_name"
+SKIP_TESTS+=" or test_array_inference[data7-expected7]"
-
+# too new xarray, gh#pandas-dev/pandas#60109 backport too much
+SKIP_TESTS+=" or (TestDataFrameToXArray and test_to_xarray_index_types)"
+# xpass strict: our xarray seems to handle this fine
+SKIP_TESTS+=" or (TestSeriesToXArray and test_to_xarray_index_types)"
 %ifarch %{ix86} %{arm32}
 # https://github.com/pandas-dev/pandas/issues/31856
 SKIP_TESTS+=" or test_maybe_promote_int_with_int"