From 91aa285144d2a3dd5c276eec549f3cdbe01772f2 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Thu, 26 Aug 2021 00:14:22 +0530
Subject: [PATCH 01/26] BUG: groupby agg fails silently with mixed dtypes

---
 doc/source/whatsnew/v1.3.3.rst       |  2 +-
 pandas/core/groupby/generic.py       |  4 +++-
 pandas/tests/groupby/test_groupby.py | 14 ++++++++++++++
 3 files changed, 18 insertions(+), 2 deletions(-)

diff --git a/doc/source/whatsnew/v1.3.3.rst b/doc/source/whatsnew/v1.3.3.rst
index 1340188c3d609..f4e4134346e15 100644
--- a/doc/source/whatsnew/v1.3.3.rst
+++ b/doc/source/whatsnew/v1.3.3.rst
@@ -17,7 +17,7 @@ Fixed regressions
 - Fixed regression in :class:`DataFrame` constructor failing to broadcast for defined :class:`Index` and len one list of :class:`Timestamp` (:issue:`42810`)
 - Performance regression in :meth:`core.window.ewm.ExponentialMovingWindow.mean` (:issue:`42333`)
 - Fixed regression in :meth:`.GroupBy.agg` incorrectly raising in some cases (:issue:`42390`)
--
+- Fixed regression in :meth:`.GroupBy.sum`, :meth:`.GroupBy.std` and :meth:`.GroupBy.var` (:issue:`43209`)
 
 .. ---------------------------------------------------------------------------
 
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 35cb247e96bc3..5409f33c238f6 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -41,6 +41,7 @@
     doc,
 )
 
+from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import (
     ensure_int64,
     is_bool,
@@ -1597,7 +1598,8 @@ def _gotitem(self, key, ndim: int, subset=None):
     def _get_data_to_aggregate(self) -> Manager2D:
         obj = self._obj_with_exclusions
         if self.axis == 1:
-            return obj.T._mgr
+            transposed_dtype = find_common_type(obj.dtypes.tolist())
+            return obj.T.astype(transposed_dtype)._mgr
         else:
             return obj._mgr
 
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index a714abd461461..3d91cd4354178 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2419,3 +2419,17 @@ def test_rolling_wrong_param_min_period():
     result_error_msg = r"__init__\(\) got an unexpected keyword argument 'min_period'"
     with pytest.raises(TypeError, match=result_error_msg):
         test_df.groupby("name")["val"].rolling(window=2, min_period=1).sum()
+
+
+@pytest.mark.parametrize("dtype", [int, "Int64"])
+def test_multiindex_groupby(dtype):
+    # GH#43209
+    df = DataFrame(
+        [[1, 2, 3, 4, 5, 6]] * 3,
+        columns=MultiIndex.from_product([["a", "b"], ["i", "j", "k"]]),
+    ).astype({("a", "j"): dtype, ("b", "j"): dtype})
+    result = df.groupby(level=1, axis=1).sum()
+    expected = DataFrame(
+        [[5, 7, 9], [5, 7, 9], [5, 7, 9]], columns=["i", "j", "k"], dtype=dtype
+    )
+    tm.assert_frame_equal(result, expected)

From 9b9b7af8f0c4cbfafce4a29959101a72f4122323 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Thu, 26 Aug 2021 00:18:18 +0530
Subject: [PATCH 02/26] updated whatsnew

---
 doc/source/whatsnew/v1.3.3.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v1.3.3.rst b/doc/source/whatsnew/v1.3.3.rst
index f4e4134346e15..f7e3609301991 100644
--- a/doc/source/whatsnew/v1.3.3.rst
+++ b/doc/source/whatsnew/v1.3.3.rst
@@ -17,7 +17,7 @@ Fixed regressions
 - Fixed regression in :class:`DataFrame` constructor failing to broadcast for defined :class:`Index` and len one list of :class:`Timestamp` (:issue:`42810`)
 - Performance regression in :meth:`core.window.ewm.ExponentialMovingWindow.mean` (:issue:`42333`)
 - Fixed regression in :meth:`.GroupBy.agg` incorrectly raising in some cases (:issue:`42390`)
-- Fixed regression in :meth:`.GroupBy.sum`, :meth:`.GroupBy.std` and :meth:`.GroupBy.var` (:issue:`43209`)
+- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types  (:issue:`43209`)
 
 .. ---------------------------------------------------------------------------
 

From d968e5772f08b399eba956fa4f59d0a003fc6a16 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Thu, 26 Aug 2021 01:01:06 +0530
Subject: [PATCH 03/26] added tests for var and std

---
 pandas/core/groupby/generic.py       |  3 ++-
 pandas/tests/groupby/test_groupby.py | 15 +++++++++------
 2 files changed, 11 insertions(+), 7 deletions(-)

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 5409f33c238f6..9d6ac77223146 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1057,7 +1057,8 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
     def _iterate_slices(self) -> Iterable[Series]:
         obj = self._selected_obj
         if self.axis == 1:
-            obj = obj.T
+            transposed_dtype = find_common_type(obj.dtypes.tolist())
+            obj = obj.T.astype(transposed_dtype)
 
         if isinstance(obj, Series) and obj.name not in self.exclusions:
             # Occurs when doing DataFrameGroupBy(...)["X"]
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 3d91cd4354178..eb1b31f65655a 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2421,15 +2421,18 @@ def test_rolling_wrong_param_min_period():
         test_df.groupby("name")["val"].rolling(window=2, min_period=1).sum()
 
 
+@pytest.mark.parametrize(
+    "func, expected",
+    [("sum", [5, 7, 9]), ("std", [4.5 ** 0.5] * 3), ("var", [4.5] * 3)],
+)
 @pytest.mark.parametrize("dtype", [int, "Int64"])
-def test_multiindex_groupby(dtype):
+def test_multiindex_groupby(dtype, func, expected):
     # GH#43209
     df = DataFrame(
         [[1, 2, 3, 4, 5, 6]] * 3,
         columns=MultiIndex.from_product([["a", "b"], ["i", "j", "k"]]),
     ).astype({("a", "j"): dtype, ("b", "j"): dtype})
-    result = df.groupby(level=1, axis=1).sum()
-    expected = DataFrame(
-        [[5, 7, 9], [5, 7, 9], [5, 7, 9]], columns=["i", "j", "k"], dtype=dtype
-    )
-    tm.assert_frame_equal(result, expected)
+    result = df.groupby(level=1, axis=1).agg(func)
+    out_dtype = dtype if func == "sum" else None
+    expected = DataFrame([expected] * 3, columns=["i", "j", "k"], dtype=out_dtype)
+    tm.assert_frame_equal(result, expected, check_dtype=False)

From 46a29e05bae0b0a77d6cc617f27fb649be1adece Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Mon, 30 Aug 2021 20:13:30 +0530
Subject: [PATCH 04/26] reorganized tests

---
 pandas/tests/groupby/test_groupby.py | 20 +++++++++++++-------
 1 file changed, 13 insertions(+), 7 deletions(-)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index eb1b31f65655a..52d48800519a0 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2422,17 +2422,23 @@ def test_rolling_wrong_param_min_period():
 
 
 @pytest.mark.parametrize(
-    "func, expected",
-    [("sum", [5, 7, 9]), ("std", [4.5 ** 0.5] * 3), ("var", [4.5] * 3)],
+    "func, expected, dtype, result_dtype",
+    [
+        ("sum", [5, 7, 9], int, int),
+        ("std", [4.5 ** 0.5] * 3, int, float),
+        ("var", [4.5] * 3, int, float),
+        ("sum", [5, 7, 9], "Int64", "Int64"),
+        # result_dtype should ideally be Float64
+        ("std", [4.5 ** 0.5] * 3, "Int64", float),
+        ("var", [4.5] * 3, "Int64", "Float64"),
+    ],
 )
-@pytest.mark.parametrize("dtype", [int, "Int64"])
-def test_multiindex_groupby(dtype, func, expected):
+def test_multiindex_groupby(func, expected, dtype, result_dtype):
     # GH#43209
     df = DataFrame(
         [[1, 2, 3, 4, 5, 6]] * 3,
         columns=MultiIndex.from_product([["a", "b"], ["i", "j", "k"]]),
     ).astype({("a", "j"): dtype, ("b", "j"): dtype})
     result = df.groupby(level=1, axis=1).agg(func)
-    out_dtype = dtype if func == "sum" else None
-    expected = DataFrame([expected] * 3, columns=["i", "j", "k"], dtype=out_dtype)
-    tm.assert_frame_equal(result, expected, check_dtype=False)
+    expected = DataFrame([expected] * 3, columns=["i", "j", "k"], dtype=result_dtype)
+    tm.assert_frame_equal(result, expected)

From 16e28db834c477d28d9eaa45eb6656c8a99707b7 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Mon, 30 Aug 2021 22:03:10 +0530
Subject: [PATCH 05/26] specified int64 in result

---
 pandas/tests/groupby/test_groupby.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 52d48800519a0..1afd448759a31 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2424,7 +2424,7 @@ def test_rolling_wrong_param_min_period():
 @pytest.mark.parametrize(
     "func, expected, dtype, result_dtype",
     [
-        ("sum", [5, 7, 9], int, int),
+        ("sum", [5, 7, 9], int, "int64"),
         ("std", [4.5 ** 0.5] * 3, int, float),
         ("var", [4.5] * 3, int, float),
         ("sum", [5, 7, 9], "Int64", "Int64"),

From 854ecda409b2505d8018e376290f08c7244b55f4 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Tue, 31 Aug 2021 21:25:47 +0530
Subject: [PATCH 06/26] added copy=False to astype

---
 pandas/core/groupby/generic.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 9d6ac77223146..1987baa96e44c 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1058,7 +1058,7 @@ def _iterate_slices(self) -> Iterable[Series]:
         obj = self._selected_obj
         if self.axis == 1:
             transposed_dtype = find_common_type(obj.dtypes.tolist())
-            obj = obj.T.astype(transposed_dtype)
+            obj = obj.T.astype(transposed_dtype, copy=False)
 
         if isinstance(obj, Series) and obj.name not in self.exclusions:
             # Occurs when doing DataFrameGroupBy(...)["X"]
@@ -1600,7 +1600,7 @@ def _get_data_to_aggregate(self) -> Manager2D:
         obj = self._obj_with_exclusions
         if self.axis == 1:
             transposed_dtype = find_common_type(obj.dtypes.tolist())
-            return obj.T.astype(transposed_dtype)._mgr
+            return obj.T.astype(transposed_dtype, copy=False)._mgr
         else:
             return obj._mgr
 

From 7dd27f3ff34220073628f91e71e4b4110e121de9 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Wed, 1 Sep 2021 01:26:36 +0530
Subject: [PATCH 07/26] updated whatsnew

---
 doc/source/whatsnew/v1.3.3.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v1.3.3.rst b/doc/source/whatsnew/v1.3.3.rst
index 29eb5e2d95650..af39c7fd492fe 100644
--- a/doc/source/whatsnew/v1.3.3.rst
+++ b/doc/source/whatsnew/v1.3.3.rst
@@ -17,7 +17,7 @@ Fixed regressions
 - Fixed regression in :class:`DataFrame` constructor failing to broadcast for defined :class:`Index` and len one list of :class:`Timestamp` (:issue:`42810`)
 - Performance regression in :meth:`core.window.ewm.ExponentialMovingWindow.mean` (:issue:`42333`)
 - Fixed regression in :meth:`.GroupBy.agg` incorrectly raising in some cases (:issue:`42390`)
-- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types  (:issue:`43209`)
+- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types along ``axis=1`` and :class:`Multiindex` (:issue:`43209`)
 - Fixed regression in :meth:`RangeIndex.where` and :meth:`RangeIndex.putmask` raising ``AssertionError`` when result did not represent a :class:`RangeIndex` (:issue:`43240`)
 
 .. ---------------------------------------------------------------------------

From 309ee59478023166021384db6edc6fe898d5394f Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Wed, 1 Sep 2021 01:28:26 +0530
Subject: [PATCH 08/26] typo corrected

---
 doc/source/whatsnew/v1.3.3.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v1.3.3.rst b/doc/source/whatsnew/v1.3.3.rst
index af39c7fd492fe..1a18e4485997b 100644
--- a/doc/source/whatsnew/v1.3.3.rst
+++ b/doc/source/whatsnew/v1.3.3.rst
@@ -17,7 +17,7 @@ Fixed regressions
 - Fixed regression in :class:`DataFrame` constructor failing to broadcast for defined :class:`Index` and len one list of :class:`Timestamp` (:issue:`42810`)
 - Performance regression in :meth:`core.window.ewm.ExponentialMovingWindow.mean` (:issue:`42333`)
 - Fixed regression in :meth:`.GroupBy.agg` incorrectly raising in some cases (:issue:`42390`)
-- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types along ``axis=1`` and :class:`Multiindex` (:issue:`43209`)
+- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types along ``axis=1`` and :class:`MultiIndex` (:issue:`43209`)
 - Fixed regression in :meth:`RangeIndex.where` and :meth:`RangeIndex.putmask` raising ``AssertionError`` when result did not represent a :class:`RangeIndex` (:issue:`43240`)
 
 .. ---------------------------------------------------------------------------

From 8d1bfb1cb92e3d632f460334df30f10824c0fad1 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Wed, 1 Sep 2021 11:20:01 +0530
Subject: [PATCH 09/26] added issue ref

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

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 1987baa96e44c..de7627515ce68 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1057,6 +1057,7 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
     def _iterate_slices(self) -> Iterable[Series]:
         obj = self._selected_obj
         if self.axis == 1:
+            # To be removed post #GH #43337 fix
             transposed_dtype = find_common_type(obj.dtypes.tolist())
             obj = obj.T.astype(transposed_dtype, copy=False)
 
@@ -1599,6 +1600,7 @@ def _gotitem(self, key, ndim: int, subset=None):
     def _get_data_to_aggregate(self) -> Manager2D:
         obj = self._obj_with_exclusions
         if self.axis == 1:
+            # To be removed post #GH #43337 fix
             transposed_dtype = find_common_type(obj.dtypes.tolist())
             return obj.T.astype(transposed_dtype, copy=False)._mgr
         else:

From 41471aa464962cbc64450f588482d21025e8b50b Mon Sep 17 00:00:00 2001
From: Shoham Debnath <debnathshoham@gmail.com>
Date: Thu, 2 Sep 2021 23:27:05 +0530
Subject: [PATCH 10/26] added issue ref to test

---
 pandas/tests/groupby/test_groupby.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 1afd448759a31..91d2c00843cbe 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2429,6 +2429,7 @@ def test_rolling_wrong_param_min_period():
         ("var", [4.5] * 3, int, float),
         ("sum", [5, 7, 9], "Int64", "Int64"),
         # result_dtype should ideally be Float64
+        # GH#43330
         ("std", [4.5 ** 0.5] * 3, "Int64", float),
         ("var", [4.5] * 3, "Int64", "Float64"),
     ],

From d6992e54f4fd684a1e291e7409209d4840c914b2 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Sun, 5 Sep 2021 21:06:43 +0530
Subject: [PATCH 11/26] reverted old; raising DataError as 1.2.5

---
 pandas/core/groupby/generic.py       | 17 ++++----
 pandas/core/groupby/groupby.py       | 61 +++++++++++++++++++---------
 pandas/tests/groupby/test_groupby.py | 22 +++++-----
 3 files changed, 61 insertions(+), 39 deletions(-)

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index de7627515ce68..a4b366b118b8b 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -41,7 +41,6 @@
     doc,
 )
 
-from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import (
     ensure_int64,
     is_bool,
@@ -67,7 +66,10 @@
     validate_func_kwargs,
 )
 from pandas.core.apply import GroupByApply
-from pandas.core.base import SpecificationError
+from pandas.core.base import (
+    DataError,
+    SpecificationError,
+)
 import pandas.core.common as com
 from pandas.core.construction import create_series_with_explicit_dtype
 from pandas.core.frame import DataFrame
@@ -1057,9 +1059,7 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
     def _iterate_slices(self) -> Iterable[Series]:
         obj = self._selected_obj
         if self.axis == 1:
-            # To be removed post #GH #43337 fix
-            transposed_dtype = find_common_type(obj.dtypes.tolist())
-            obj = obj.T.astype(transposed_dtype, copy=False)
+            obj = obj.T
 
         if isinstance(obj, Series) and obj.name not in self.exclusions:
             # Occurs when doing DataFrameGroupBy(...)["X"]
@@ -1099,6 +1099,9 @@ def array_func(values: ArrayLike) -> ArrayLike:
         #  continue and exclude the block
         new_mgr = data.grouped_reduce(array_func, ignore_failures=True)
 
+        if not len(new_mgr) and len(data):
+            raise DataError("No numeric types to aggregate")
+
         if len(new_mgr) < len(data):
             warnings.warn(
                 f"Dropping invalid columns in {type(self).__name__}.{how} "
@@ -1600,9 +1603,7 @@ def _gotitem(self, key, ndim: int, subset=None):
     def _get_data_to_aggregate(self) -> Manager2D:
         obj = self._obj_with_exclusions
         if self.axis == 1:
-            # To be removed post #GH #43337 fix
-            transposed_dtype = find_common_type(obj.dtypes.tolist())
-            return obj.T.astype(transposed_dtype, copy=False)._mgr
+            return obj.T._mgr
         else:
             return obj._mgr
 
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 79ee71ddb1047..5852794631d87 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1361,12 +1361,19 @@ def _agg_general(
 
         with group_selection_context(self):
             # try a cython aggregation if we can
-            result = self._cython_agg_general(
-                how=alias,
-                alt=npfunc,
-                numeric_only=numeric_only,
-                min_count=min_count,
-            )
+            result = None
+            try:
+                result = self._cython_agg_general(
+                    how=alias,
+                    alt=npfunc,
+                    numeric_only=numeric_only,
+                    min_count=min_count,
+                )
+            except DataError:
+                pass
+
+            if result is None:
+                result = self.aggregate(lambda x: npfunc(x, axis=self.axis))
             return result.__finalize__(self.obj, method="groupby")
 
     def _agg_py_fallback(
@@ -1740,16 +1747,21 @@ def std(self, ddof: int = 1):
         Series or DataFrame
             Standard deviation of values within each group.
         """
-        return self._get_cythonized_result(
-            libgroupby.group_var,
-            aggregate=True,
-            needs_counts=True,
-            needs_values=True,
-            needs_2d=True,
-            cython_dtype=np.dtype(np.float64),
-            post_processing=lambda vals, inference: np.sqrt(vals),
-            ddof=ddof,
-        )
+        try:
+            return self._get_cythonized_result(
+                libgroupby.group_var,
+                aggregate=True,
+                needs_counts=True,
+                needs_values=True,
+                needs_2d=True,
+                cython_dtype=np.dtype(np.float64),
+                post_processing=lambda vals, inference: np.sqrt(vals),
+                ddof=ddof,
+            )
+        except DataError:
+            func = lambda x: x.std(ddof=ddof)
+            with group_selection_context(self):
+                return self._python_agg_general(func)
 
     @final
     @Substitution(name="groupby")
@@ -1771,10 +1783,17 @@ def var(self, ddof: int = 1):
             Variance of values within each group.
         """
         if ddof == 1:
-            numeric_only = self._resolve_numeric_only(lib.no_default)
-            return self._cython_agg_general(
-                "var", alt=lambda x: Series(x).var(ddof=ddof), numeric_only=numeric_only
-            )
+            try:
+                numeric_only = self._resolve_numeric_only(lib.no_default)
+                return self._cython_agg_general(
+                    "var",
+                    alt=lambda x: Series(x).var(ddof=ddof),
+                    numeric_only=numeric_only,
+                )
+            except DataError:
+                func = lambda x: x.var(ddof=ddof)
+                with group_selection_context(self):
+                    return self._python_agg_general(func)
         else:
             func = lambda x: x.var(ddof=ddof)
             with group_selection_context(self):
@@ -3049,6 +3068,8 @@ def blk_func(values: ArrayLike) -> ArrayLike:
         # error_msg is "" on an frame/series with no rows or columns
         if not output and error_msg != "":
             raise TypeError(error_msg)
+        elif not output and error_msg == "" and not self._obj_with_exclusions.empty:
+            raise DataError("No numeric types to aggregate")
 
         if aggregate:
             return self._wrap_aggregated_output(output)
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index c96e0c94a7134..13bc1f7912319 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2446,24 +2446,24 @@ def test_rolling_wrong_param_min_period():
 
 
 @pytest.mark.parametrize(
-    "func, expected, dtype, result_dtype",
+    "func, expected, dtype, result_dtype_dict",
     [
-        ("sum", [5, 7, 9], int, "int64"),
-        ("std", [4.5 ** 0.5] * 3, int, float),
-        ("var", [4.5] * 3, int, float),
-        ("sum", [5, 7, 9], "Int64", "Int64"),
-        # result_dtype should ideally be Float64
-        # GH#43330
-        ("std", [4.5 ** 0.5] * 3, "Int64", float),
-        ("var", [4.5] * 3, "Int64", "Float64"),
+        ("sum", [5, 7, 9], "int64", {}),
+        ("std", [4.5 ** 0.5] * 3, int, {"i": float, "j": float, "k": float}),
+        ("var", [4.5] * 3, int, {"i": float, "j": float, "k": float}),
+        ("sum", [5, 7, 9], "Int64", {"j": "float64"}),
+        ("std", [4.5 ** 0.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
+        ("var", [4.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
     ],
 )
-def test_multiindex_groupby(func, expected, dtype, result_dtype):
+def test_multiindex_groupby(func, expected, dtype, result_dtype_dict):
     # GH#43209
     df = DataFrame(
         [[1, 2, 3, 4, 5, 6]] * 3,
         columns=MultiIndex.from_product([["a", "b"], ["i", "j", "k"]]),
     ).astype({("a", "j"): dtype, ("b", "j"): dtype})
     result = df.groupby(level=1, axis=1).agg(func)
-    expected = DataFrame([expected] * 3, columns=["i", "j", "k"], dtype=result_dtype)
+    expected = DataFrame([expected] * 3, columns=["i", "j", "k"]).astype(
+        result_dtype_dict
+    )
     tm.assert_frame_equal(result, expected)

From ab1fd879ec856efecbae53cf980dc13eb1a25efd Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Sun, 5 Sep 2021 23:27:01 +0530
Subject: [PATCH 12/26] used _selected_obj instead of mgr

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

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index a4b366b118b8b..05253a849541f 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1099,7 +1099,7 @@ def array_func(values: ArrayLike) -> ArrayLike:
         #  continue and exclude the block
         new_mgr = data.grouped_reduce(array_func, ignore_failures=True)
 
-        if not len(new_mgr) and len(data):
+        if not len(new_mgr) and len(self._selected_obj):
             raise DataError("No numeric types to aggregate")
 
         if len(new_mgr) < len(data):

From 9039124269b055e8cf54da73e169d5168bb3ec07 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Mon, 6 Sep 2021 00:23:48 +0530
Subject: [PATCH 13/26] =0

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

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 05253a849541f..e4db5084d17f5 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1099,7 +1099,7 @@ def array_func(values: ArrayLike) -> ArrayLike:
         #  continue and exclude the block
         new_mgr = data.grouped_reduce(array_func, ignore_failures=True)
 
-        if not len(new_mgr) and len(self._selected_obj):
+        if not len(new_mgr) and len(self._selected_obj) == 0:
             raise DataError("No numeric types to aggregate")
 
         if len(new_mgr) < len(data):

From 64ca85a9004d141d86d1968dc91b0336b31cf2e8 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Fri, 10 Sep 2021 00:22:11 +0530
Subject: [PATCH 14/26] draft

---
 pandas/core/groupby/generic.py | 17 +++++-----
 pandas/core/groupby/groupby.py | 61 ++++++++++++----------------------
 2 files changed, 30 insertions(+), 48 deletions(-)

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 240c1eac34e03..150b8f6832ce3 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -41,6 +41,7 @@
     doc,
 )
 
+from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import (
     ensure_int64,
     is_bool,
@@ -66,10 +67,7 @@
     validate_func_kwargs,
 )
 from pandas.core.apply import GroupByApply
-from pandas.core.base import (
-    DataError,
-    SpecificationError,
-)
+from pandas.core.base import SpecificationError
 import pandas.core.common as com
 from pandas.core.construction import create_series_with_explicit_dtype
 from pandas.core.frame import DataFrame
@@ -1041,7 +1039,9 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
     def _iterate_slices(self) -> Iterable[Series]:
         obj = self._selected_obj
         if self.axis == 1:
-            obj = obj.T
+            # To be removed post #GH #43337 fix
+            transposed_dtype = find_common_type(obj.dtypes.tolist())
+            obj = obj.T.astype(transposed_dtype, copy=False)
 
         if isinstance(obj, Series) and obj.name not in self.exclusions:
             # Occurs when doing DataFrameGroupBy(...)["X"]
@@ -1081,9 +1081,6 @@ def array_func(values: ArrayLike) -> ArrayLike:
         #  continue and exclude the block
         new_mgr = data.grouped_reduce(array_func, ignore_failures=True)
 
-        if not len(new_mgr) and len(self._selected_obj) == 0:
-            raise DataError("No numeric types to aggregate")
-
         if len(new_mgr) < len(data):
             warnings.warn(
                 f"Dropping invalid columns in {type(self).__name__}.{how} "
@@ -1585,7 +1582,9 @@ def _gotitem(self, key, ndim: int, subset=None):
     def _get_data_to_aggregate(self) -> Manager2D:
         obj = self._obj_with_exclusions
         if self.axis == 1:
-            return obj.T._mgr
+            # To be removed post #GH #43337 fix
+            transposed_dtype = find_common_type(obj.dtypes.tolist())
+            return obj.T.astype(transposed_dtype, copy=False)._mgr
         else:
             return obj._mgr
 
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 1cfa6e1d2e714..fe57d47d9b740 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1410,19 +1410,12 @@ def _agg_general(
 
         with group_selection_context(self):
             # try a cython aggregation if we can
-            result = None
-            try:
-                result = self._cython_agg_general(
-                    how=alias,
-                    alt=npfunc,
-                    numeric_only=numeric_only,
-                    min_count=min_count,
-                )
-            except DataError:
-                pass
-
-            if result is None:
-                result = self.aggregate(lambda x: npfunc(x, axis=self.axis))
+            result = self._cython_agg_general(
+                how=alias,
+                alt=npfunc,
+                numeric_only=numeric_only,
+                min_count=min_count,
+            )
             return result.__finalize__(self.obj, method="groupby")
 
     def _agg_py_fallback(
@@ -1796,21 +1789,16 @@ def std(self, ddof: int = 1):
         Series or DataFrame
             Standard deviation of values within each group.
         """
-        try:
-            return self._get_cythonized_result(
-                libgroupby.group_var,
-                aggregate=True,
-                needs_counts=True,
-                needs_values=True,
-                needs_2d=True,
-                cython_dtype=np.dtype(np.float64),
-                post_processing=lambda vals, inference: np.sqrt(vals),
-                ddof=ddof,
-            )
-        except DataError:
-            func = lambda x: x.std(ddof=ddof)
-            with group_selection_context(self):
-                return self._python_agg_general(func)
+        return self._get_cythonized_result(
+            libgroupby.group_var,
+            aggregate=True,
+            needs_counts=True,
+            needs_values=True,
+            needs_2d=True,
+            cython_dtype=np.dtype(np.float64),
+            post_processing=lambda vals, inference: np.sqrt(vals),
+            ddof=ddof,
+        )
 
     @final
     @Substitution(name="groupby")
@@ -1832,17 +1820,12 @@ def var(self, ddof: int = 1):
             Variance of values within each group.
         """
         if ddof == 1:
-            try:
-                numeric_only = self._resolve_numeric_only(lib.no_default)
-                return self._cython_agg_general(
-                    "var",
-                    alt=lambda x: Series(x).var(ddof=ddof),
-                    numeric_only=numeric_only,
-                )
-            except DataError:
-                func = lambda x: x.var(ddof=ddof)
-                with group_selection_context(self):
-                    return self._python_agg_general(func)
+            numeric_only = self._resolve_numeric_only(lib.no_default)
+            return self._cython_agg_general(
+                "var",
+                alt=lambda x: Series(x).var(ddof=ddof),
+                numeric_only=numeric_only,
+            )
         else:
             func = lambda x: x.var(ddof=ddof)
             with group_selection_context(self):

From 4ae0d6bfd221e6087ac5da80dcb63a7856dac889 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Fri, 10 Sep 2021 02:29:23 +0530
Subject: [PATCH 15/26] cast mi groupbysum

---
 pandas/core/groupby/groupby.py       | 13 ++++++++-----
 pandas/tests/groupby/test_groupby.py |  4 ++--
 2 files changed, 10 insertions(+), 7 deletions(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index b3c7a0b8b9ee9..732b961c525cf 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1855,9 +1855,7 @@ def var(self, ddof: int = 1):
         if ddof == 1:
             numeric_only = self._resolve_numeric_only(lib.no_default)
             return self._cython_agg_general(
-                "var",
-                alt=lambda x: Series(x).var(ddof=ddof),
-                numeric_only=numeric_only,
+                "var", alt=lambda x: Series(x).var(ddof=ddof), numeric_only=numeric_only
             )
         else:
             func = lambda x: x.var(ddof=ddof)
@@ -1937,6 +1935,13 @@ def sum(
                 alias="add",
                 npfunc=np.sum,
             )
+        if self.axis == 1 and isinstance(self.obj.columns, MultiIndex):
+            dtypes_df = self.obj.dtypes.unstack().head(1)
+            if len(set(dtypes_df.values[0])) > 1:
+                # if self.obj has mixed dtype
+                result = result.astype(
+                    dict(zip(dtypes_df.columns, dtypes_df.values[0]))
+                )
 
         return self._reindex_output(result, fill_value=0)
 
@@ -3130,8 +3135,6 @@ def blk_func(values: ArrayLike) -> ArrayLike:
         # error_msg is "" on an frame/series with no rows or columns
         if not output and error_msg != "":
             raise TypeError(error_msg)
-        elif not output and error_msg == "" and not self._obj_with_exclusions.empty:
-            raise DataError("No numeric types to aggregate")
 
         if aggregate:
             return self._wrap_aggregated_output(output)
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 13bc1f7912319..41330ef698039 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2451,9 +2451,9 @@ def test_rolling_wrong_param_min_period():
         ("sum", [5, 7, 9], "int64", {}),
         ("std", [4.5 ** 0.5] * 3, int, {"i": float, "j": float, "k": float}),
         ("var", [4.5] * 3, int, {"i": float, "j": float, "k": float}),
-        ("sum", [5, 7, 9], "Int64", {"j": "float64"}),
+        ("sum", [5, 7, 9], "Int64", {"j": "Int64"}),
         ("std", [4.5 ** 0.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
-        ("var", [4.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
+        ("var", [4.5] * 3, "Int64", {"i": "Float64", "j": "Float64", "k": "Float64"}),
     ],
 )
 def test_multiindex_groupby(func, expected, dtype, result_dtype_dict):

From 572f23c3baaaef81543578a5126e62e66350e539 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Fri, 10 Sep 2021 11:46:38 +0530
Subject: [PATCH 16/26] dropped na

---
 pandas/core/groupby/groupby.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 349a5630f893a..696344da14481 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1944,7 +1944,7 @@ def sum(
                 npfunc=np.sum,
             )
         if self.axis == 1 and isinstance(self.obj.columns, MultiIndex):
-            dtypes_df = self.obj.dtypes.unstack().head(1)
+            dtypes_df = self.obj.dtypes.unstack().head(1).dropna(axis=1)
             if len(set(dtypes_df.values[0])) > 1:
                 # if self.obj has mixed dtype
                 result = result.astype(

From 625a7517f5de233ab86a71325722e52ab3bb2207 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Sat, 11 Sep 2021 21:19:13 +0530
Subject: [PATCH 17/26] try casting in _wrap_agged_manager

---
 pandas/core/groupby/generic.py | 23 +++++++++++++++++++++++
 pandas/core/groupby/groupby.py |  8 --------
 2 files changed, 23 insertions(+), 8 deletions(-)

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 7ef3159bc5e3b..dd27bb0c39e6f 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1594,11 +1594,34 @@ def _wrap_agged_manager(self, mgr: Manager2D) -> DataFrame:
 
         if self.axis == 1:
             result = result.T
+            result = self._maybe_recast_columns_if_transposed(result)
 
         # Note: we only need to pass datetime=True in order to get numeric
         #  values converted
         return self._reindex_output(result)._convert(datetime=True)
 
+    def _maybe_recast_columns_if_transposed(self, result) -> DataFrame:
+        obj = self._selected_obj
+        dtype_df = obj.dtypes
+        if obj._is_homogeneous_type:
+            # not mixed dtype
+            return result
+        if isinstance(obj.columns, MultiIndex):
+            dtype_df_dict = (
+                dtype_df.reset_index(level=self.level)
+                .drop_duplicates(f"level_{self.level}")
+                .set_index(f"level_{self.level}")
+                .to_dict()[0]
+            )
+        else:
+            dtype_df_dict = dtype_df.drop_duplicates().loc[result.index].to_dict()
+        result_cast = result.astype(dtype_df_dict, copy=False, errors="ignore")
+        if np.array_equal(result_cast.values, result.values):
+            # able to safely cast
+            return result_cast
+        else:
+            return result
+
     def _iterate_column_groupbys(self, obj: FrameOrSeries):
         for i, colname in enumerate(obj.columns):
             yield colname, SeriesGroupBy(
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 343d372f4bf3a..fe3eaa5be2173 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1956,14 +1956,6 @@ def sum(
                 alias="add",
                 npfunc=np.sum,
             )
-        if self.axis == 1 and isinstance(self.obj.columns, MultiIndex):
-            dtypes_df = self.obj.dtypes.unstack().head(1).dropna(axis=1)
-            if len(set(dtypes_df.values[0])) > 1:
-                # if self.obj has mixed dtype
-                result = result.astype(
-                    dict(zip(dtypes_df.columns, dtypes_df.values[0]))
-                )
-
         return self._reindex_output(result, fill_value=0)
 
     @final

From 9b0acd73a0eeade01fc8601b7802dc2346ef33e9 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Sat, 11 Sep 2021 22:52:41 +0530
Subject: [PATCH 18/26] added test axis=1

---
 pandas/core/groupby/generic.py       |  2 +-
 pandas/tests/groupby/test_groupby.py | 27 ++++++++++++++++++++++++++-
 2 files changed, 27 insertions(+), 2 deletions(-)

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index dd27bb0c39e6f..22bf056ef814f 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1614,7 +1614,7 @@ def _maybe_recast_columns_if_transposed(self, result) -> DataFrame:
                 .to_dict()[0]
             )
         else:
-            dtype_df_dict = dtype_df.drop_duplicates().loc[result.index].to_dict()
+            dtype_df_dict = dtype_df.drop_duplicates().loc[result.columns].to_dict()
         result_cast = result.astype(dtype_df_dict, copy=False, errors="ignore")
         if np.array_equal(result_cast.values, result.values):
             # able to safely cast
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 2469c7fc5ecfe..fe1d28241bc51 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2522,7 +2522,7 @@ def test_rolling_wrong_param_min_period():
         ("var", [4.5] * 3, "Int64", {"i": "Float64", "j": "Float64", "k": "Float64"}),
     ],
 )
-def test_multiindex_groupby(func, expected, dtype, result_dtype_dict):
+def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype_dict):
     # GH#43209
     df = DataFrame(
         [[1, 2, 3, 4, 5, 6]] * 3,
@@ -2533,3 +2533,28 @@ def test_multiindex_groupby(func, expected, dtype, result_dtype_dict):
         result_dtype_dict
     )
     tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "func, expected_data, result_dtype_dict",
+    [
+        ("sum", [[2, 4], [10, 12], [18, 20]], {10: "Int64", 20: "int64"}),
+        # should ideally by Int64 #43330
+        ("std", [[2 ** 0.5] * 2] * 3, float),
+        ("var", [[2] * 2] * 3, {10: "Int64", 20: "int64"}),
+    ],
+)
+def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):
+    # GH#43209
+    df = DataFrame(
+        np.arange(12).reshape(3, 4),
+        index=Index([0, 1, 0], name="y"),
+        columns=Index([10, 20, 10, 20], name="x"),
+    ).astype({10: "Int64"})
+    result = df.groupby("x", axis=1).agg(func)
+    expected = DataFrame(
+        data=expected_data,
+        index=Index([0, 1, 0], name="y"),
+        columns=Index([10, 20], name="x"),
+    ).astype(result_dtype_dict)
+    tm.assert_frame_equal(result, expected)

From 265b3bb17c33d18ec40165646eb6341ae6a4ef32 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Sun, 12 Sep 2021 01:22:03 +0530
Subject: [PATCH 19/26] overrid int64; failing in 32bit

---
 pandas/tests/groupby/test_groupby.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index fe1d28241bc51..b318eae6528bb 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2550,6 +2550,7 @@ def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):
         np.arange(12).reshape(3, 4),
         index=Index([0, 1, 0], name="y"),
         columns=Index([10, 20, 10, 20], name="x"),
+        dtype="int64",
     ).astype({10: "Int64"})
     result = df.groupby("x", axis=1).agg(func)
     expected = DataFrame(

From 753c7dfe30a5dc5eae2cab716a414c7c48e99623 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Mon, 13 Sep 2021 21:18:23 +0530
Subject: [PATCH 20/26] updated whatsnew

---
 doc/source/whatsnew/v1.3.3.rst | 1 -
 doc/source/whatsnew/v1.3.4.rst | 2 +-
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/doc/source/whatsnew/v1.3.3.rst b/doc/source/whatsnew/v1.3.3.rst
index 0bd660d47ae8f..ecec6d975ccb7 100644
--- a/doc/source/whatsnew/v1.3.3.rst
+++ b/doc/source/whatsnew/v1.3.3.rst
@@ -16,7 +16,6 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression in :class:`DataFrame` constructor failing to broadcast for defined :class:`Index` and len one list of :class:`Timestamp` (:issue:`42810`)
 - Fixed regression in :meth:`.GroupBy.agg` incorrectly raising in some cases (:issue:`42390`)
-- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types along ``axis=1`` and :class:`MultiIndex` (:issue:`43209`)
 - Fixed regression in :meth:`.GroupBy.apply` where ``nan`` values were dropped even with ``dropna=False`` (:issue:`43205`)
 - Fixed regression in :meth:`.GroupBy.quantile` which was failing with ``pandas.NA`` (:issue:`42849`)
 - Fixed regression in :meth:`merge` where ``on`` columns with ``ExtensionDtype`` or ``bool`` data types were cast to ``object`` in ``right`` and ``outer`` merge (:issue:`40073`)
diff --git a/doc/source/whatsnew/v1.3.4.rst b/doc/source/whatsnew/v1.3.4.rst
index 273686f0aaa8f..231bae94bf6c3 100644
--- a/doc/source/whatsnew/v1.3.4.rst
+++ b/doc/source/whatsnew/v1.3.4.rst
@@ -14,7 +14,7 @@ including other versions of pandas.
 
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
--
+- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types along ``axis=1`` and :class:`MultiIndex` (:issue:`43209`)
 -
 
 .. ---------------------------------------------------------------------------

From de86f725c61fe3aa180799d8c49634b9138f56ea Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Mon, 13 Sep 2021 22:59:26 +0530
Subject: [PATCH 21/26] astype for std

---
 pandas/core/groupby/groupby.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 4ae29b4b64e64..6acc76d251cb4 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -62,6 +62,7 @@ class providing the base-class of operations.
 )
 from pandas.util._exceptions import find_stack_level
 
+from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import (
     is_bool_dtype,
     is_datetime64_dtype,
@@ -3140,7 +3141,9 @@ def blk_func(values: ArrayLike) -> ArrayLike:
 
         mgr = obj._mgr
         if self.axis == 1:
-            mgr = obj.T._mgr
+            # To be removed post #GH #43337 fix
+            transposed_dtype = find_common_type(obj.dtypes.tolist())
+            mgr = obj.T.astype(transposed_dtype, copy=False)._mgr
 
         if numeric_only:
             mgr = mgr.get_numeric_data()

From 2a29451207520ab76694742ddeb9b18dd57fd510 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Tue, 14 Sep 2021 20:36:53 +0530
Subject: [PATCH 22/26] smaller patch for 1.3.x

---
 pandas/core/groupby/generic.py       | 32 ++--------------------------
 pandas/core/groupby/groupby.py       | 11 +++++-----
 pandas/tests/groupby/test_groupby.py | 10 ++++-----
 3 files changed, 13 insertions(+), 40 deletions(-)

diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 53b21a89e03c8..46e42326d4191 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -38,7 +38,6 @@
     doc,
 )
 
-from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import (
     ensure_int64,
     is_bool,
@@ -956,9 +955,7 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
     def _iterate_slices(self) -> Iterable[Series]:
         obj = self._selected_obj
         if self.axis == 1:
-            # To be removed post #GH #43337 fix
-            transposed_dtype = find_common_type(obj.dtypes.tolist())
-            obj = obj.T.astype(transposed_dtype, copy=False)
+            obj = obj.T
 
         if isinstance(obj, Series) and obj.name not in self.exclusions:
             # Occurs when doing DataFrameGroupBy(...)["X"]
@@ -1470,9 +1467,7 @@ def _gotitem(self, key, ndim: int, subset=None):
     def _get_data_to_aggregate(self) -> Manager2D:
         obj = self._obj_with_exclusions
         if self.axis == 1:
-            # To be removed post #GH #43337 fix
-            transposed_dtype = find_common_type(obj.dtypes.tolist())
-            return obj.T.astype(transposed_dtype, copy=False)._mgr
+            return obj.T._mgr
         else:
             return obj._mgr
 
@@ -1520,34 +1515,11 @@ def _wrap_agged_manager(self, mgr: Manager2D) -> DataFrame:
 
         if self.axis == 1:
             result = result.T
-            result = self._maybe_recast_columns_if_transposed(result)
 
         # Note: we only need to pass datetime=True in order to get numeric
         #  values converted
         return self._reindex_output(result)._convert(datetime=True)
 
-    def _maybe_recast_columns_if_transposed(self, result) -> DataFrame:
-        obj = self._selected_obj
-        dtype_df = obj.dtypes
-        if obj._is_homogeneous_type:
-            # not mixed dtype
-            return result
-        if isinstance(obj.columns, MultiIndex):
-            dtype_df_dict = (
-                dtype_df.reset_index(level=self.level)
-                .drop_duplicates(f"level_{self.level}")
-                .set_index(f"level_{self.level}")
-                .to_dict()[0]
-            )
-        else:
-            dtype_df_dict = dtype_df.drop_duplicates().loc[result.columns].to_dict()
-        result_cast = result.astype(dtype_df_dict, copy=False, errors="ignore")
-        if np.array_equal(result_cast.values, result.values):
-            # able to safely cast
-            return result_cast
-        else:
-            return result
-
     def _iterate_column_groupbys(self, obj: FrameOrSeries):
         for i, colname in enumerate(obj.columns):
             yield colname, SeriesGroupBy(
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 6acc76d251cb4..d4a595836481d 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -62,7 +62,6 @@ class providing the base-class of operations.
 )
 from pandas.util._exceptions import find_stack_level
 
-from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import (
     is_bool_dtype,
     is_datetime64_dtype,
@@ -1214,7 +1213,10 @@ def _resolve_numeric_only(self, numeric_only: bool | lib.NoDefault) -> bool:
                 numeric_only = True
                 # GH#42395 GH#43108 GH#43154
                 # Regression from 1.2.5 to 1.3 caused object columns to be dropped
-                obj = self._obj_with_exclusions
+                if self.axis:
+                    obj = self._obj_with_exclusions.T
+                else:
+                    obj = self._obj_with_exclusions
                 check = obj._get_numeric_data()
                 if len(obj.columns) and not len(check.columns) and not obj.empty:
                     numeric_only = False
@@ -1981,6 +1983,7 @@ def sum(
                 alias="add",
                 npfunc=np.sum,
             )
+
         return self._reindex_output(result, fill_value=0)
 
     @final
@@ -3141,9 +3144,7 @@ def blk_func(values: ArrayLike) -> ArrayLike:
 
         mgr = obj._mgr
         if self.axis == 1:
-            # To be removed post #GH #43337 fix
-            transposed_dtype = find_common_type(obj.dtypes.tolist())
-            mgr = obj.T.astype(transposed_dtype, copy=False)._mgr
+            mgr = obj.T._mgr
 
         if numeric_only:
             mgr = mgr.get_numeric_data()
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index b318eae6528bb..20ad6bb9f7224 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2517,9 +2517,9 @@ def test_rolling_wrong_param_min_period():
         ("sum", [5, 7, 9], "int64", {}),
         ("std", [4.5 ** 0.5] * 3, int, {"i": float, "j": float, "k": float}),
         ("var", [4.5] * 3, int, {"i": float, "j": float, "k": float}),
-        ("sum", [5, 7, 9], "Int64", {"j": "Int64"}),
+        ("sum", [5, 7, 9], "Int64", {"j": "int64"}),
         ("std", [4.5 ** 0.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
-        ("var", [4.5] * 3, "Int64", {"i": "Float64", "j": "Float64", "k": "Float64"}),
+        ("var", [4.5] * 3, "Int64", {"i": "float64", "j": "float64", "k": "float64"}),
     ],
 )
 def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype_dict):
@@ -2538,10 +2538,10 @@ def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype
 @pytest.mark.parametrize(
     "func, expected_data, result_dtype_dict",
     [
-        ("sum", [[2, 4], [10, 12], [18, 20]], {10: "Int64", 20: "int64"}),
+        ("sum", [[2, 4], [10, 12], [18, 20]], {10: "int64", 20: "int64"}),
         # should ideally by Int64 #43330
-        ("std", [[2 ** 0.5] * 2] * 3, float),
-        ("var", [[2] * 2] * 3, {10: "Int64", 20: "int64"}),
+        ("std", [[2 ** 0.5] * 2] * 3, "float64"),
+        ("var", [[2] * 2] * 3, {10: "float64", 20: "float64"}),
     ],
 )
 def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):

From 00838be6b8706fdfedb09af08aef3235d7f63c2c Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Fri, 17 Sep 2021 00:46:50 +0530
Subject: [PATCH 23/26] changes wrt 1.2.5

---
 pandas/tests/groupby/test_groupby.py | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 20ad6bb9f7224..6402b66cc8f01 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2516,10 +2516,17 @@ def test_rolling_wrong_param_min_period():
     [
         ("sum", [5, 7, 9], "int64", {}),
         ("std", [4.5 ** 0.5] * 3, int, {"i": float, "j": float, "k": float}),
+        # 1.2.5: ValueError: Length mismatch: Expected axis
+        # has 0 elements, new values have 3 elements
         ("var", [4.5] * 3, int, {"i": float, "j": float, "k": float}),
+        # 1.2.5: DataError: No numeric types to aggregate
         ("sum", [5, 7, 9], "Int64", {"j": "int64"}),
+        # 1.2.5: j:float64
         ("std", [4.5 ** 0.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
+        # 1.2.5: ValueError: Length mismatch: Expected axis
+        # has 0 elements, new values have 3 elements
         ("var", [4.5] * 3, "Int64", {"i": "float64", "j": "float64", "k": "float64"}),
+        # 1.2.5: DataError: No numeric types to aggregate
     ],
 )
 def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype_dict):
@@ -2539,9 +2546,13 @@ def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype
     "func, expected_data, result_dtype_dict",
     [
         ("sum", [[2, 4], [10, 12], [18, 20]], {10: "int64", 20: "int64"}),
-        # should ideally by Int64 #43330
+        # 1.2.5: 10: float64
+        # std should ideally return Int64 #43330
         ("std", [[2 ** 0.5] * 2] * 3, "float64"),
+        # 1.2.5: ValueError: Length mismatch: Expected axis
+        # has 0 elements, new values have 3 elements
         ("var", [[2] * 2] * 3, {10: "float64", 20: "float64"}),
+        # 1.2.5: DataError: No numeric types to aggregate
     ],
 )
 def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):

From 600b71e499b982768e8e3924d996c2f9c63ae849 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Wed, 29 Sep 2021 12:21:04 +0530
Subject: [PATCH 24/26] removed comments highlighting diff with 1.2.5 from test

---
 pandas/tests/groupby/test_groupby.py | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 6402b66cc8f01..2a691a723cfd4 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2546,13 +2546,9 @@ def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype
     "func, expected_data, result_dtype_dict",
     [
         ("sum", [[2, 4], [10, 12], [18, 20]], {10: "int64", 20: "int64"}),
-        # 1.2.5: 10: float64
         # std should ideally return Int64 #43330
         ("std", [[2 ** 0.5] * 2] * 3, "float64"),
-        # 1.2.5: ValueError: Length mismatch: Expected axis
-        # has 0 elements, new values have 3 elements
         ("var", [[2] * 2] * 3, {10: "float64", 20: "float64"}),
-        # 1.2.5: DataError: No numeric types to aggregate
     ],
 )
 def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):

From fe132784b9f08a9b322f51621a3132a925de0b79 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Wed, 29 Sep 2021 12:45:26 +0530
Subject: [PATCH 25/26] removed comments from test2

---
 pandas/tests/groupby/test_groupby.py | 9 +--------
 1 file changed, 1 insertion(+), 8 deletions(-)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 2a691a723cfd4..843e6765cee0d 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2516,17 +2516,10 @@ def test_rolling_wrong_param_min_period():
     [
         ("sum", [5, 7, 9], "int64", {}),
         ("std", [4.5 ** 0.5] * 3, int, {"i": float, "j": float, "k": float}),
-        # 1.2.5: ValueError: Length mismatch: Expected axis
-        # has 0 elements, new values have 3 elements
         ("var", [4.5] * 3, int, {"i": float, "j": float, "k": float}),
-        # 1.2.5: DataError: No numeric types to aggregate
         ("sum", [5, 7, 9], "Int64", {"j": "int64"}),
-        # 1.2.5: j:float64
         ("std", [4.5 ** 0.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
-        # 1.2.5: ValueError: Length mismatch: Expected axis
-        # has 0 elements, new values have 3 elements
         ("var", [4.5] * 3, "Int64", {"i": "float64", "j": "float64", "k": "float64"}),
-        # 1.2.5: DataError: No numeric types to aggregate
     ],
 )
 def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype_dict):
@@ -2546,7 +2539,7 @@ def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype
     "func, expected_data, result_dtype_dict",
     [
         ("sum", [[2, 4], [10, 12], [18, 20]], {10: "int64", 20: "int64"}),
-        # std should ideally return Int64 #43330
+        # std should ideally return Int64 / Float64 #43330
         ("std", [[2 ** 0.5] * 2] * 3, "float64"),
         ("var", [[2] * 2] * 3, {10: "float64", 20: "float64"}),
     ],

From 1aaf326a5c83eab9c8c2832a521cf7c8ee3878b7 Mon Sep 17 00:00:00 2001
From: debnathshoham <debnathshoham@gmail.com>
Date: Wed, 29 Sep 2021 22:34:40 +0530
Subject: [PATCH 26/26] moved tests to test_aggregate

---
 .../tests/groupby/aggregate/test_aggregate.py | 50 +++++++++++++++++++
 pandas/tests/groupby/test_groupby.py          | 50 -------------------
 2 files changed, 50 insertions(+), 50 deletions(-)

diff --git a/pandas/tests/groupby/aggregate/test_aggregate.py b/pandas/tests/groupby/aggregate/test_aggregate.py
index 7bb850d38340f..d8d53c355bd0f 100644
--- a/pandas/tests/groupby/aggregate/test_aggregate.py
+++ b/pandas/tests/groupby/aggregate/test_aggregate.py
@@ -225,6 +225,56 @@ def test_agg_str_with_kwarg_axis_1_raises(df, reduction_func):
         gb.agg(reduction_func, axis=1)
 
 
+@pytest.mark.parametrize(
+    "func, expected, dtype, result_dtype_dict",
+    [
+        ("sum", [5, 7, 9], "int64", {}),
+        ("std", [4.5 ** 0.5] * 3, int, {"i": float, "j": float, "k": float}),
+        ("var", [4.5] * 3, int, {"i": float, "j": float, "k": float}),
+        ("sum", [5, 7, 9], "Int64", {"j": "int64"}),
+        ("std", [4.5 ** 0.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
+        ("var", [4.5] * 3, "Int64", {"i": "float64", "j": "float64", "k": "float64"}),
+    ],
+)
+def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype_dict):
+    # GH#43209
+    df = DataFrame(
+        [[1, 2, 3, 4, 5, 6]] * 3,
+        columns=MultiIndex.from_product([["a", "b"], ["i", "j", "k"]]),
+    ).astype({("a", "j"): dtype, ("b", "j"): dtype})
+    result = df.groupby(level=1, axis=1).agg(func)
+    expected = DataFrame([expected] * 3, columns=["i", "j", "k"]).astype(
+        result_dtype_dict
+    )
+    tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "func, expected_data, result_dtype_dict",
+    [
+        ("sum", [[2, 4], [10, 12], [18, 20]], {10: "int64", 20: "int64"}),
+        # std should ideally return Int64 / Float64 #43330
+        ("std", [[2 ** 0.5] * 2] * 3, "float64"),
+        ("var", [[2] * 2] * 3, {10: "float64", 20: "float64"}),
+    ],
+)
+def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):
+    # GH#43209
+    df = DataFrame(
+        np.arange(12).reshape(3, 4),
+        index=Index([0, 1, 0], name="y"),
+        columns=Index([10, 20, 10, 20], name="x"),
+        dtype="int64",
+    ).astype({10: "Int64"})
+    result = df.groupby("x", axis=1).agg(func)
+    expected = DataFrame(
+        data=expected_data,
+        index=Index([0, 1, 0], name="y"),
+        columns=Index([10, 20], name="x"),
+    ).astype(result_dtype_dict)
+    tm.assert_frame_equal(result, expected)
+
+
 def test_aggregate_item_by_item(df):
     grouped = df.groupby("A")
 
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 843e6765cee0d..b9a6730996a02 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2509,53 +2509,3 @@ def test_rolling_wrong_param_min_period():
     result_error_msg = r"__init__\(\) got an unexpected keyword argument 'min_period'"
     with pytest.raises(TypeError, match=result_error_msg):
         test_df.groupby("name")["val"].rolling(window=2, min_period=1).sum()
-
-
-@pytest.mark.parametrize(
-    "func, expected, dtype, result_dtype_dict",
-    [
-        ("sum", [5, 7, 9], "int64", {}),
-        ("std", [4.5 ** 0.5] * 3, int, {"i": float, "j": float, "k": float}),
-        ("var", [4.5] * 3, int, {"i": float, "j": float, "k": float}),
-        ("sum", [5, 7, 9], "Int64", {"j": "int64"}),
-        ("std", [4.5 ** 0.5] * 3, "Int64", {"i": float, "j": float, "k": float}),
-        ("var", [4.5] * 3, "Int64", {"i": "float64", "j": "float64", "k": "float64"}),
-    ],
-)
-def test_multiindex_groupby_mixed_cols_axis1(func, expected, dtype, result_dtype_dict):
-    # GH#43209
-    df = DataFrame(
-        [[1, 2, 3, 4, 5, 6]] * 3,
-        columns=MultiIndex.from_product([["a", "b"], ["i", "j", "k"]]),
-    ).astype({("a", "j"): dtype, ("b", "j"): dtype})
-    result = df.groupby(level=1, axis=1).agg(func)
-    expected = DataFrame([expected] * 3, columns=["i", "j", "k"]).astype(
-        result_dtype_dict
-    )
-    tm.assert_frame_equal(result, expected)
-
-
-@pytest.mark.parametrize(
-    "func, expected_data, result_dtype_dict",
-    [
-        ("sum", [[2, 4], [10, 12], [18, 20]], {10: "int64", 20: "int64"}),
-        # std should ideally return Int64 / Float64 #43330
-        ("std", [[2 ** 0.5] * 2] * 3, "float64"),
-        ("var", [[2] * 2] * 3, {10: "float64", 20: "float64"}),
-    ],
-)
-def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):
-    # GH#43209
-    df = DataFrame(
-        np.arange(12).reshape(3, 4),
-        index=Index([0, 1, 0], name="y"),
-        columns=Index([10, 20, 10, 20], name="x"),
-        dtype="int64",
-    ).astype({10: "Int64"})
-    result = df.groupby("x", axis=1).agg(func)
-    expected = DataFrame(
-        data=expected_data,
-        index=Index([0, 1, 0], name="y"),
-        columns=Index([10, 20], name="x"),
-    ).astype(result_dtype_dict)
-    tm.assert_frame_equal(result, expected)