From 0c6c0299e1da4273aa47ab1426cc4ffd7e054b5e Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Mon, 9 Jan 2023 16:29:05 +0800
Subject: [PATCH 01/11] add-FutureWarning-pandas.io.sql.execute

---
 doc/source/whatsnew/v2.0.0.rst | 2 +-
 pandas/io/sql.py               | 6 ++++++
 pandas/tests/io/test_sql.py    | 9 +++++++++
 3 files changed, 16 insertions(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v2.0.0.rst b/doc/source/whatsnew/v2.0.0.rst
index 3ea4447cdfa93..95c760ebaef9a 100644
--- a/doc/source/whatsnew/v2.0.0.rst
+++ b/doc/source/whatsnew/v2.0.0.rst
@@ -510,7 +510,7 @@ Other API changes
 Deprecations
 ~~~~~~~~~~~~
 - Deprecated argument ``infer_datetime_format`` in :func:`to_datetime` and :func:`read_csv`, as a strict version of it is now the default (:issue:`48621`)
-
+- Deprecated :func:`pandas.io.sql.execute`(:issue:`50185`)
 .. ---------------------------------------------------------------------------
 
 .. _whatsnew_200.prior_deprecations:
diff --git a/pandas/io/sql.py b/pandas/io/sql.py
index 2b845786b0366..eea97fc0d9760 100644
--- a/pandas/io/sql.py
+++ b/pandas/io/sql.py
@@ -201,6 +201,12 @@ def execute(sql, con, params=None):
     -------
     Results Iterable
     """
+    warnings.warn(
+        "`pandas.io.sql.execute` is deprecated and "
+        "will be removed in the future version.",
+        FutureWarning,
+        stacklevel=find_stack_level(),
+    )  # GH50185
     sqlalchemy = import_optional_dependency("sqlalchemy", errors="ignore")
 
     if sqlalchemy is not None and isinstance(con, (str, sqlalchemy.engine.Engine)):
diff --git a/pandas/tests/io/test_sql.py b/pandas/tests/io/test_sql.py
index 31ca060e36ad1..15c45821f959e 100644
--- a/pandas/tests/io/test_sql.py
+++ b/pandas/tests/io/test_sql.py
@@ -668,6 +668,15 @@ def test_execute_typeerror(sqlite_iris_engine):
         sql.execute("select * from iris", sqlite_iris_engine)
 
 
+def test_execute_deprecated(sqlite_buildin_iris):
+    with tm.assert_produces_warning(
+        FutureWarning,
+        match="`pandas.io.sql.execute` is deprecated and "
+        "will be removed in the future version.",
+    ):
+        sql.execute("select * from iris", sqlite_buildin_iris)
+
+
 class MixInBase:
     def teardown_method(self):
         # if setup fails, there may not be a connection to close.

From d055ee0027d8a0a762fee68d461e978d07afbbe4 Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Mon, 9 Jan 2023 23:32:48 +0800
Subject: [PATCH 02/11] add GH and try fix doc build

---
 doc/source/whatsnew/v2.0.0.rst | 2 +-
 pandas/tests/io/test_sql.py    | 1 +
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v2.0.0.rst b/doc/source/whatsnew/v2.0.0.rst
index 95c760ebaef9a..efbdd52aa30b3 100644
--- a/doc/source/whatsnew/v2.0.0.rst
+++ b/doc/source/whatsnew/v2.0.0.rst
@@ -510,7 +510,7 @@ Other API changes
 Deprecations
 ~~~~~~~~~~~~
 - Deprecated argument ``infer_datetime_format`` in :func:`to_datetime` and :func:`read_csv`, as a strict version of it is now the default (:issue:`48621`)
-- Deprecated :func:`pandas.io.sql.execute`(:issue:`50185`)
+- Deprecated ``pandas.io.sql.execute``(:issue:`50185`)
 .. ---------------------------------------------------------------------------
 
 .. _whatsnew_200.prior_deprecations:
diff --git a/pandas/tests/io/test_sql.py b/pandas/tests/io/test_sql.py
index 15c45821f959e..f83b6b0373a87 100644
--- a/pandas/tests/io/test_sql.py
+++ b/pandas/tests/io/test_sql.py
@@ -669,6 +669,7 @@ def test_execute_typeerror(sqlite_iris_engine):
 
 
 def test_execute_deprecated(sqlite_buildin_iris):
+    # GH50185
     with tm.assert_produces_warning(
         FutureWarning,
         match="`pandas.io.sql.execute` is deprecated and "

From eca7ca39467f56fba626159ff3aa36421af7e518 Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Tue, 10 Jan 2023 11:38:16 +0800
Subject: [PATCH 03/11] try fix doc build

---
 doc/source/whatsnew/v2.0.0.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v2.0.0.rst b/doc/source/whatsnew/v2.0.0.rst
index 992b51387eda8..27053a9a5df23 100644
--- a/doc/source/whatsnew/v2.0.0.rst
+++ b/doc/source/whatsnew/v2.0.0.rst
@@ -553,7 +553,7 @@ Other API changes
 Deprecations
 ~~~~~~~~~~~~
 - Deprecated argument ``infer_datetime_format`` in :func:`to_datetime` and :func:`read_csv`, as a strict version of it is now the default (:issue:`48621`)
-- Deprecated ``pandas.io.sql.execute``(:issue:`50185`)
+- Deprecated :func:`pandas.io.sql.execute`(:issue:`50185`)
 .. ---------------------------------------------------------------------------
 
 .. _whatsnew_200.prior_deprecations:

From 224ce2e96cc99d26125f38e5ebc4e351a8700b4c Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Tue, 10 Jan 2023 21:14:04 +0800
Subject: [PATCH 04/11] change comments in core/generic.py

---
 pandas/core/generic.py | 32 ++++++++++++++++++++++----------
 1 file changed, 22 insertions(+), 10 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 561422c868e91..73ed223ec013b 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2858,8 +2858,12 @@ def to_sql(
 
         >>> df.to_sql('users', con=engine)
         3
-        >>> engine.execute("SELECT * FROM users").fetchall()
-        [(0, 'User 1'), (1, 'User 2'), (2, 'User 3')]
+        >>> pd.read_sql_query("SELECT * FROM users", con=engine)
+            index    name
+        0      0  User 1
+        1      1  User 2
+        2      2  User 3
+
 
         An `sqlalchemy.engine.Connection` can also be passed to `con`:
 
@@ -2874,18 +2878,25 @@ def to_sql(
         >>> df2 = pd.DataFrame({'name' : ['User 6', 'User 7']})
         >>> df2.to_sql('users', con=engine, if_exists='append')
         2
-        >>> engine.execute("SELECT * FROM users").fetchall()
-        [(0, 'User 1'), (1, 'User 2'), (2, 'User 3'),
-         (0, 'User 4'), (1, 'User 5'), (0, 'User 6'),
-         (1, 'User 7')]
+        >>> pd.read_sql_query("SELECT * FROM users", con=engine)
+            index    name
+        0      0  User 1
+        1      1  User 2
+        2      2  User 3
+        3      0  User 4
+        4      1  User 5
+        5      0  User 6
+        6      1  User 7
 
         Overwrite the table with just ``df2``.
 
         >>> df2.to_sql('users', con=engine, if_exists='replace',
         ...            index_label='id')
         2
-        >>> engine.execute("SELECT * FROM users").fetchall()
-        [(0, 'User 6'), (1, 'User 7')]
+        >>> pd.read_sql_query("SELECT * FROM users", con=engine)
+            index    name
+        0      0  User 6
+        1      1  User 7
 
         Specify the dtype (especially useful for integers with missing values).
         Notice that while pandas is forced to store the data as floating point,
@@ -2904,8 +2915,9 @@ def to_sql(
         ...           dtype={"A": Integer()})
         3
 
-        >>> engine.execute("SELECT * FROM integers").fetchall()
-        [(1,), (None,), (2,)]
+        >>> pd.read_sql("SELECT * FROM integers", con=engine)
+             A
+        0  1.0
         """  # noqa:E501
         from pandas.io import sql
 

From ce00e61a440a195b72a8a803844ca0c433e83928 Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Tue, 10 Jan 2023 21:23:52 +0800
Subject: [PATCH 05/11] fix an res error

---
 pandas/core/generic.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 73ed223ec013b..5c5fe866ea280 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2918,6 +2918,8 @@ def to_sql(
         >>> pd.read_sql("SELECT * FROM integers", con=engine)
              A
         0  1.0
+        1  NaN
+        2  2.0
         """  # noqa:E501
         from pandas.io import sql
 

From 8138721407f3cbad0b24818b447bd19f41524488 Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Tue, 10 Jan 2023 22:21:38 +0800
Subject: [PATCH 06/11] fix double break line

---
 pandas/core/generic.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 5c5fe866ea280..b97efcb82a0c6 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2864,7 +2864,6 @@ def to_sql(
         1      1  User 2
         2      2  User 3
 
-
         An `sqlalchemy.engine.Connection` can also be passed to `con`:
 
         >>> with engine.begin() as connection:

From 8e15910d631174e1a271fa091ddd0929590a86ba Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Tue, 10 Jan 2023 23:11:06 +0800
Subject: [PATCH 07/11] fix example res error

---
 pandas/core/generic.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index b97efcb82a0c6..3e0972d5df6ae 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2893,9 +2893,9 @@ def to_sql(
         ...            index_label='id')
         2
         >>> pd.read_sql_query("SELECT * FROM users", con=engine)
-            index    name
-        0      0  User 6
-        1      1  User 7
+           id    name
+        0   0  User 6
+        1   1  User 7
 
         Specify the dtype (especially useful for integers with missing values).
         Notice that while pandas is forced to store the data as floating point,

From 5a198bc61f4597b3395c4475cfe215808b19d98d Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Wed, 11 Jan 2023 01:15:51 +0800
Subject: [PATCH 08/11] add blank line

---
 doc/source/whatsnew/v2.0.0.rst | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v2.0.0.rst b/doc/source/whatsnew/v2.0.0.rst
index 27053a9a5df23..3c914bb16ecde 100644
--- a/doc/source/whatsnew/v2.0.0.rst
+++ b/doc/source/whatsnew/v2.0.0.rst
@@ -554,8 +554,9 @@ Deprecations
 ~~~~~~~~~~~~
 - Deprecated argument ``infer_datetime_format`` in :func:`to_datetime` and :func:`read_csv`, as a strict version of it is now the default (:issue:`48621`)
 - Deprecated :func:`pandas.io.sql.execute`(:issue:`50185`)
-.. ---------------------------------------------------------------------------
+-
 
+.. ---------------------------------------------------------------------------
 .. _whatsnew_200.prior_deprecations:
 
 Removal of prior version deprecations/changes

From bba740595dd6519a1e2ba1ddf8168bfe47d62436 Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Wed, 11 Jan 2023 22:51:42 +0800
Subject: [PATCH 09/11] Revert "change comments in core/generic.py"

---
 pandas/core/generic.py | 20 ++++++--------------
 1 file changed, 6 insertions(+), 14 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 3e0972d5df6ae..0c83ab78c940a 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2858,11 +2858,8 @@ def to_sql(
 
         >>> df.to_sql('users', con=engine)
         3
-        >>> pd.read_sql_query("SELECT * FROM users", con=engine)
-            index    name
-        0      0  User 1
-        1      1  User 2
-        2      2  User 3
+        >>> engine.execute("SELECT * FROM users").fetchall()
+        [(0, 'User 1'), (1, 'User 2'), (2, 'User 3')]
 
         An `sqlalchemy.engine.Connection` can also be passed to `con`:
 
@@ -2892,10 +2889,8 @@ def to_sql(
         >>> df2.to_sql('users', con=engine, if_exists='replace',
         ...            index_label='id')
         2
-        >>> pd.read_sql_query("SELECT * FROM users", con=engine)
-           id    name
-        0   0  User 6
-        1   1  User 7
+        >>> engine.execute("SELECT * FROM users").fetchall()
+        [(0, 'User 6'), (1, 'User 7')]
 
         Specify the dtype (especially useful for integers with missing values).
         Notice that while pandas is forced to store the data as floating point,
@@ -2914,11 +2909,8 @@ def to_sql(
         ...           dtype={"A": Integer()})
         3
 
-        >>> pd.read_sql("SELECT * FROM integers", con=engine)
-             A
-        0  1.0
-        1  NaN
-        2  2.0
+        >>> engine.execute("SELECT * FROM integers").fetchall()
+        [(1,), (None,), (2,)]
         """  # noqa:E501
         from pandas.io import sql
 

From 364c98a3b14626a359b79703b50513f8bdadd019 Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Wed, 11 Jan 2023 22:52:40 +0800
Subject: [PATCH 10/11] Revert "DEPR: Enforce certain DataFrame reductions w/
 axis=None to return scalars (#50593)"

This reverts commit 47c9ee7b32d8bde2ff8cf50288a8787b11d512cb.
---
 doc/source/whatsnew/v2.0.0.rst                |  1 -
 pandas/core/frame.py                          | 10 ++--
 pandas/core/generic.py                        | 51 +++++++++++--------
 pandas/tests/frame/test_reductions.py         | 31 ++++++-----
 pandas/tests/groupby/test_categorical.py      |  8 ++-
 pandas/tests/groupby/test_function.py         | 16 ++++--
 .../tests/groupby/transform/test_transform.py | 17 +++++--
 7 files changed, 80 insertions(+), 54 deletions(-)

diff --git a/doc/source/whatsnew/v2.0.0.rst b/doc/source/whatsnew/v2.0.0.rst
index 3c914bb16ecde..c5e51d27ba5f3 100644
--- a/doc/source/whatsnew/v2.0.0.rst
+++ b/doc/source/whatsnew/v2.0.0.rst
@@ -761,7 +761,6 @@ Removal of prior version deprecations/changes
 - Changed behavior of :meth:`Series.fillna` and :meth:`DataFrame.fillna` with ``timedelta64[ns]`` dtype and an incompatible ``fill_value``; this now casts to ``object`` dtype instead of raising, consistent with the behavior with other dtypes (:issue:`45746`)
 - Change the default argument of ``regex`` for :meth:`Series.str.replace` from ``True`` to ``False``. Additionally, a single character ``pat`` with ``regex=True`` is now treated as a regular expression instead of a string literal. (:issue:`36695`, :issue:`24804`)
 - Changed behavior of :meth:`DataFrame.any` and :meth:`DataFrame.all` with ``bool_only=True``; object-dtype columns with all-bool values will no longer be included, manually cast to ``bool`` dtype first (:issue:`46188`)
-- Changed behavior of :meth:`DataFrame.max`, :class:`DataFrame.min`, :class:`DataFrame.mean`, :class:`DataFrame.median`, :class:`DataFrame.skew`, :class:`DataFrame.kurt` with ``axis=None`` to return a scalar applying the aggregation across both axes (:issue:`45072`)
 - Changed behavior of comparison of a :class:`Timestamp` with a ``datetime.date`` object; these now compare as un-equal and raise on inequality comparisons, matching the ``datetime.datetime`` behavior (:issue:`36131`)
 - Changed behavior of comparison of ``NaT`` with a ``datetime.date`` object; these now raise on inequality comparisons (:issue:`39196`)
 - Enforced deprecation of silently dropping columns that raised a ``TypeError`` in :class:`Series.transform` and :class:`DataFrame.transform` when used with a list or dictionary (:issue:`43740`)
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 6491081c54592..fed92dc80a99b 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -10357,8 +10357,9 @@ def _reduce(
         assert filter_type is None or filter_type == "bool", filter_type
         out_dtype = "bool" if filter_type == "bool" else None
 
-        if axis is not None:
-            axis = self._get_axis_number(axis)
+        # TODO: Make other agg func handle axis=None properly GH#21597
+        axis = self._get_axis_number(axis)
+        assert axis in [0, 1]
 
         def func(values: np.ndarray):
             # We only use this in the case that operates on self.values
@@ -10409,7 +10410,7 @@ def _get_data() -> DataFrame:
 
             return out
 
-        assert not numeric_only and axis in (1, None)
+        assert not numeric_only and axis == 1
 
         data = self
         values = data.values
@@ -10425,9 +10426,6 @@ def _get_data() -> DataFrame:
                     # try to coerce to the original dtypes item by item if we can
                     pass
 
-        if axis is None:
-            return result
-
         labels = self._get_agg_axis(axis)
         result = self._constructor_sliced(result, index=labels)
         return result
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 0c83ab78c940a..ded8c394edf83 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -10949,7 +10949,7 @@ def _stat_function(
         self,
         name: str,
         func,
-        axis: Axis | None = 0,
+        axis: Axis | None | lib.NoDefault = None,
         skipna: bool_t = True,
         numeric_only: bool_t = False,
         **kwargs,
@@ -10961,13 +10961,30 @@ def _stat_function(
 
         validate_bool_kwarg(skipna, "skipna", none_allowed=False)
 
+        if axis is None and self.ndim > 1:
+            # user must have explicitly passed axis=None
+            # GH#21597
+            warnings.warn(
+                f"In a future version, DataFrame.{name}(axis=None) will return a "
+                f"scalar {name} over the entire DataFrame. To retain the old "
+                f"behavior, use 'frame.{name}(axis=0)' or just 'frame.{name}()'",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+
+        if axis is lib.no_default:
+            axis = None
+
+        if axis is None:
+            axis = self._stat_axis_number
+
         return self._reduce(
             func, name=name, axis=axis, skipna=skipna, numeric_only=numeric_only
         )
 
     def min(
         self,
-        axis: Axis | None = 0,
+        axis: Axis | None | lib.NoDefault = lib.no_default,
         skipna: bool_t = True,
         numeric_only: bool_t = False,
         **kwargs,
@@ -10983,7 +11000,7 @@ def min(
 
     def max(
         self,
-        axis: Axis | None = 0,
+        axis: Axis | None | lib.NoDefault = lib.no_default,
         skipna: bool_t = True,
         numeric_only: bool_t = False,
         **kwargs,
@@ -10999,7 +11016,7 @@ def max(
 
     def mean(
         self,
-        axis: Axis | None = 0,
+        axis: Axis | None | lib.NoDefault = lib.no_default,
         skipna: bool_t = True,
         numeric_only: bool_t = False,
         **kwargs,
@@ -11010,7 +11027,7 @@ def mean(
 
     def median(
         self,
-        axis: Axis | None = 0,
+        axis: Axis | None | lib.NoDefault = lib.no_default,
         skipna: bool_t = True,
         numeric_only: bool_t = False,
         **kwargs,
@@ -11021,7 +11038,7 @@ def median(
 
     def skew(
         self,
-        axis: Axis | None = 0,
+        axis: Axis | None | lib.NoDefault = lib.no_default,
         skipna: bool_t = True,
         numeric_only: bool_t = False,
         **kwargs,
@@ -11032,7 +11049,7 @@ def skew(
 
     def kurt(
         self,
-        axis: Axis | None = 0,
+        axis: Axis | None | lib.NoDefault = lib.no_default,
         skipna: bool_t = True,
         numeric_only: bool_t = False,
         **kwargs,
@@ -11354,7 +11371,7 @@ def prod(
         )
         def mean(
             self,
-            axis: AxisInt | None = 0,
+            axis: AxisInt | None | lib.NoDefault = lib.no_default,
             skipna: bool_t = True,
             numeric_only: bool_t = False,
             **kwargs,
@@ -11375,7 +11392,7 @@ def mean(
         )
         def skew(
             self,
-            axis: AxisInt | None = 0,
+            axis: AxisInt | None | lib.NoDefault = lib.no_default,
             skipna: bool_t = True,
             numeric_only: bool_t = False,
             **kwargs,
@@ -11399,7 +11416,7 @@ def skew(
         )
         def kurt(
             self,
-            axis: Axis | None = 0,
+            axis: Axis | None | lib.NoDefault = lib.no_default,
             skipna: bool_t = True,
             numeric_only: bool_t = False,
             **kwargs,
@@ -11421,7 +11438,7 @@ def kurt(
         )
         def median(
             self,
-            axis: AxisInt | None = 0,
+            axis: AxisInt | None | lib.NoDefault = lib.no_default,
             skipna: bool_t = True,
             numeric_only: bool_t = False,
             **kwargs,
@@ -11444,7 +11461,7 @@ def median(
         )
         def max(
             self,
-            axis: AxisInt | None = 0,
+            axis: AxisInt | None | lib.NoDefault = lib.no_default,
             skipna: bool_t = True,
             numeric_only: bool_t = False,
             **kwargs,
@@ -11467,7 +11484,7 @@ def max(
         )
         def min(
             self,
-            axis: AxisInt | None = 0,
+            axis: AxisInt | None | lib.NoDefault = lib.no_default,
             skipna: bool_t = True,
             numeric_only: bool_t = False,
             **kwargs,
@@ -11696,12 +11713,6 @@ def _doc_params(cls):
 axis : {axis_descr}
     Axis for the function to be applied on.
     For `Series` this parameter is unused and defaults to 0.
-
-    For DataFrames, specifying ``axis=None`` will apply the aggregation
-    across both axes.
-
-    .. versionadded:: 2.0.0
-
 skipna : bool, default True
     Exclude NA/null values when computing the result.
 numeric_only : bool, default False
@@ -11713,7 +11724,7 @@ def _doc_params(cls):
 
 Returns
 -------
-{name1} or scalar\
+{name1} or {name2} (if level specified)\
 {see_also}\
 {examples}
 """
diff --git a/pandas/tests/frame/test_reductions.py b/pandas/tests/frame/test_reductions.py
index f1d176e59373f..2e0aa5fd0cf40 100644
--- a/pandas/tests/frame/test_reductions.py
+++ b/pandas/tests/frame/test_reductions.py
@@ -1488,6 +1488,7 @@ def test_median_categorical_dtype_nuisance_column(self):
         # TODO: np.median(df, axis=0) gives np.array([2.0, 2.0]) instead
         #  of expected.values
 
+    @pytest.mark.filterwarnings("ignore:.*will return a scalar.*:FutureWarning")
     @pytest.mark.parametrize("method", ["min", "max"])
     def test_min_max_categorical_dtype_non_ordered_nuisance_column(self, method):
         # GH#28949 DataFrame.min should behave like Series.min
@@ -1509,7 +1510,7 @@ def test_min_max_categorical_dtype_non_ordered_nuisance_column(self, method):
             getattr(df, method)()
 
         with pytest.raises(TypeError, match="is not ordered for operation"):
-            getattr(np, method)(df, axis=0)
+            getattr(np, method)(df)
 
         # same thing, but with an additional non-categorical column
         df["B"] = df["A"].astype(object)
@@ -1517,7 +1518,7 @@ def test_min_max_categorical_dtype_non_ordered_nuisance_column(self, method):
             getattr(df, method)()
 
         with pytest.raises(TypeError, match="is not ordered for operation"):
-            getattr(np, method)(df, axis=0)
+            getattr(np, method)(df)
 
 
 def test_sum_timedelta64_skipna_false(using_array_manager, request):
@@ -1599,22 +1600,20 @@ def test_prod_sum_min_count_mixed_object():
 
 
 @pytest.mark.parametrize("method", ["min", "max", "mean", "median", "skew", "kurt"])
-def test_reduction_axis_none_returns_scalar(method):
-    # GH#21597 As of 2.0, axis=None reduces over all axes.
+def test_reduction_axis_none_deprecation(method):
+    # GH#21597 deprecate axis=None defaulting to axis=0 so that we can change it
+    #  to reducing over all axes.
 
     df = DataFrame(np.random.randn(4, 4))
-
-    result = getattr(df, method)(axis=None)
-    np_arr = df.to_numpy()
-    if method in {"skew", "kurt"}:
-        comp_mod = pytest.importorskip("scipy.stats")
-        if method == "kurt":
-            method = "kurtosis"
-        expected = getattr(comp_mod, method)(np_arr, bias=False, axis=None)
-        tm.assert_almost_equal(result, expected)
-    else:
-        expected = getattr(np, method)(np_arr, axis=None)
-        assert result == expected
+    meth = getattr(df, method)
+
+    msg = f"scalar {method} over the entire DataFrame"
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        res = meth(axis=None)
+    with tm.assert_produces_warning(None):
+        expected = meth()
+    tm.assert_series_equal(res, expected)
+    tm.assert_series_equal(res, meth(axis=0))
 
 
 @pytest.mark.parametrize(
diff --git a/pandas/tests/groupby/test_categorical.py b/pandas/tests/groupby/test_categorical.py
index 0fabdf84e5e86..d9181830925f7 100644
--- a/pandas/tests/groupby/test_categorical.py
+++ b/pandas/tests/groupby/test_categorical.py
@@ -147,7 +147,11 @@ def f(x):
     tm.assert_frame_equal(df.groupby(c, observed=False).transform(sum), df[["a"]])
 
     gbc = df.groupby(c, observed=False)
-    result = gbc.transform(lambda xs: np.max(xs, axis=0))
+    with tm.assert_produces_warning(
+        FutureWarning, match="scalar max", check_stacklevel=False
+    ):
+        # stacklevel is thrown off (i think) bc the stack goes through numpy C code
+        result = gbc.transform(lambda xs: np.max(xs))
     tm.assert_frame_equal(result, df[["a"]])
 
     with tm.assert_produces_warning(None):
@@ -291,7 +295,7 @@ def test_apply(ordered):
     idx = MultiIndex.from_arrays([missing, dense], names=["missing", "dense"])
     expected = DataFrame([0, 1, 2.0], index=idx, columns=["values"])
 
-    result = grouped.apply(lambda x: np.mean(x, axis=0))
+    result = grouped.apply(lambda x: np.mean(x))
     tm.assert_frame_equal(result, expected)
 
     result = grouped.mean()
diff --git a/pandas/tests/groupby/test_function.py b/pandas/tests/groupby/test_function.py
index 875037b390883..bb15783f4607f 100644
--- a/pandas/tests/groupby/test_function.py
+++ b/pandas/tests/groupby/test_function.py
@@ -80,12 +80,20 @@ def test_builtins_apply(keys, f):
     assert_msg = f"invalid frame shape: {result.shape} (expected ({ngroups}, 3))"
     assert result.shape == (ngroups, 3), assert_msg
 
-    npfunc = lambda x: getattr(np, fname)(x, axis=0)  # numpy's equivalent function
-    expected = gb.apply(npfunc)
+    npfunc = getattr(np, fname)  # numpy's equivalent function
+    if f in [max, min]:
+        warn = FutureWarning
+    else:
+        warn = None
+    msg = "scalar (max|min) over the entire DataFrame"
+    with tm.assert_produces_warning(warn, match=msg, check_stacklevel=False):
+        # stacklevel can be thrown off because (i think) the stack
+        #  goes through some of numpy's C code.
+        expected = gb.apply(npfunc)
     tm.assert_frame_equal(result, expected)
 
     with tm.assert_produces_warning(None):
-        expected2 = gb.apply(lambda x: npfunc(x))
+        expected2 = gb.apply(lambda x: npfunc(x, axis=0))
     tm.assert_frame_equal(result, expected2)
 
     if f != sum:
@@ -93,7 +101,7 @@ def test_builtins_apply(keys, f):
         expected.set_index(keys, inplace=True, drop=False)
         tm.assert_frame_equal(result, expected, check_dtype=False)
 
-    tm.assert_series_equal(getattr(result, fname)(axis=0), getattr(df, fname)(axis=0))
+    tm.assert_series_equal(getattr(result, fname)(), getattr(df, fname)())
 
 
 class TestNumericOnly:
diff --git a/pandas/tests/groupby/transform/test_transform.py b/pandas/tests/groupby/transform/test_transform.py
index cb3b7def39c52..8f1d52c2ea03d 100644
--- a/pandas/tests/groupby/transform/test_transform.py
+++ b/pandas/tests/groupby/transform/test_transform.py
@@ -57,7 +57,7 @@ def test_transform():
     tm.assert_frame_equal(result, expected)
 
     def demean(arr):
-        return arr - arr.mean(axis=0)
+        return arr - arr.mean()
 
     people = DataFrame(
         np.random.randn(5, 5),
@@ -144,7 +144,7 @@ def test_transform_broadcast(tsframe, ts):
     result = grouped.transform(np.mean)
     tm.assert_index_equal(result.index, tsframe.index)
     for _, gp in grouped:
-        agged = gp.mean(axis=0)
+        agged = gp.mean()
         res = result.reindex(gp.index)
         for col in tsframe:
             assert_fp_equal(res[col], agged[col])
@@ -214,7 +214,7 @@ def test_transform_axis_ts(tsframe):
     ts = tso
     grouped = ts.groupby(lambda x: x.weekday(), group_keys=False)
     result = ts - grouped.transform("mean")
-    expected = grouped.apply(lambda x: x - x.mean(axis=0))
+    expected = grouped.apply(lambda x: x - x.mean())
     tm.assert_frame_equal(result, expected)
 
     ts = ts.T
@@ -227,7 +227,7 @@ def test_transform_axis_ts(tsframe):
     ts = tso.iloc[[1, 0] + list(range(2, len(base)))]
     grouped = ts.groupby(lambda x: x.weekday(), group_keys=False)
     result = ts - grouped.transform("mean")
-    expected = grouped.apply(lambda x: x - x.mean(axis=0))
+    expected = grouped.apply(lambda x: x - x.mean())
     tm.assert_frame_equal(result, expected)
 
     ts = ts.T
@@ -477,9 +477,16 @@ def test_transform_coercion():
 
     expected = g.transform(np.mean)
 
-    result = g.transform(lambda x: np.mean(x, axis=0))
+    # in 2.0 np.mean on a DataFrame is equivalent to frame.mean(axis=None)
+    #  which not gives a scalar instead of Series
+    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        result = g.transform(lambda x: np.mean(x))
     tm.assert_frame_equal(result, expected)
 
+    with tm.assert_produces_warning(None):
+        result2 = g.transform(lambda x: np.mean(x, axis=0))
+    tm.assert_frame_equal(result2, expected)
+
 
 def test_groupby_transform_with_int():
 

From ade630fa69ffee6d6b094e3982edfe835d0f35db Mon Sep 17 00:00:00 2001
From: luke <2736230899@qq.com>
Date: Wed, 11 Jan 2023 22:57:46 +0800
Subject: [PATCH 11/11] Revert "change comments in core/generic.py"

This reverts commit 224ce2e96cc99d26125f38e5ebc4e351a8700b4c.
---
 pandas/core/generic.py | 13 ++++---------
 1 file changed, 4 insertions(+), 9 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index ded8c394edf83..3cade2568d921 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2874,15 +2874,10 @@ def to_sql(
         >>> df2 = pd.DataFrame({'name' : ['User 6', 'User 7']})
         >>> df2.to_sql('users', con=engine, if_exists='append')
         2
-        >>> pd.read_sql_query("SELECT * FROM users", con=engine)
-            index    name
-        0      0  User 1
-        1      1  User 2
-        2      2  User 3
-        3      0  User 4
-        4      1  User 5
-        5      0  User 6
-        6      1  User 7
+        >>> engine.execute("SELECT * FROM users").fetchall()
+        [(0, 'User 1'), (1, 'User 2'), (2, 'User 3'),
+         (0, 'User 4'), (1, 'User 5'), (0, 'User 6'),
+         (1, 'User 7')]
 
         Overwrite the table with just ``df2``.