DEPR: Enforce deprecation of partial failure in transform for lists/d…

…icts (#49375)

* DEPR: Enforce deprecation of partial failure in transform for lists and dicts

* Warning message fix

* Cleaner msgs

doc/source/whatsnew/v2.0.0.rst

@@ -276,6 +276,7 @@ Removal of prior version deprecations/changes
 - Changed behavior of :class:`Index` constructor when passed a ``SparseArray`` or ``SparseDtype`` to retain that dtype instead of casting to ``numpy.ndarray`` (:issue:`43930`)
 - Removed the deprecated ``base`` and ``loffset`` arguments from :meth:`pandas.DataFrame.resample`, :meth:`pandas.Series.resample` and :class:`pandas.Grouper`. Use ``offset`` or ``origin`` instead (:issue:`31809`)
 - 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`)
+- 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`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/apply.py

@@ -266,34 +266,9 @@ def transform_dict_like(self, func):
         func = self.normalize_dictlike_arg("transform", obj, func)
 
         results: dict[Hashable, DataFrame | Series] = {}
-        failed_names = []
-        all_type_errors = True
         for name, how in func.items():
             colg = obj._gotitem(name, ndim=1)
-            try:
-                results[name] = colg.transform(how, 0, *args, **kwargs)
-            except Exception as err:
-                if str(err) in {
-                    "Function did not transform",
-                    "No transform functions were provided",
-                }:
-                    raise err
-                else:
-                    if not isinstance(err, TypeError):
-                        all_type_errors = False
-                    failed_names.append(name)
-        # combine results
-        if not results:
-            klass = TypeError if all_type_errors else ValueError
-            raise klass("Transform function failed")
-        if len(failed_names) > 0:
-            warnings.warn(
-                f"{failed_names} did not transform successfully. If any error is "
-                f"raised, this will raise in a future version of pandas. "
-                f"Drop these columns/ops to avoid this warning.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
+            results[name] = colg.transform(how, 0, *args, **kwargs)
         return concat(results, axis=1)
 
     def transform_str_or_callable(self, func) -> DataFrame | Series:

pandas/tests/apply/test_frame_transform.py

@@ -133,32 +133,37 @@ def func(x):
 @pytest.mark.parametrize("op", [*frame_kernels_raise, lambda x: x + 1])
 def test_transform_bad_dtype(op, frame_or_series, request):
     # GH 35964
-    if op == "rank":
-        request.node.add_marker(
-            pytest.mark.xfail(
-                raises=ValueError, reason="GH 40418: rank does not raise a TypeError"
-            )
-        )
-    elif op == "ngroup":
+    if op == "ngroup":
         request.node.add_marker(
             pytest.mark.xfail(raises=ValueError, reason="ngroup not valid for NDFrame")
         )
 
     obj = DataFrame({"A": 3 * [object]})  # DataFrame that will fail on most transforms
     obj = tm.get_obj(obj, frame_or_series)
+    if op == "rank":
+        error = ValueError
+        msg = "Transform function failed"
+    else:
+        error = TypeError
+        msg = "|".join(
+            [
+                "not supported between instances of 'type' and 'type'",
+                "unsupported operand type",
+            ]
+        )
 
-    with pytest.raises(TypeError, match="unsupported operand|not supported"):
+    with pytest.raises(error, match=msg):
         obj.transform(op)
-    with pytest.raises(TypeError, match="Transform function failed"):
+    with pytest.raises(error, match=msg):
         obj.transform([op])
-    with pytest.raises(TypeError, match="Transform function failed"):
+    with pytest.raises(error, match=msg):
         obj.transform({"A": op})
-    with pytest.raises(TypeError, match="Transform function failed"):
+    with pytest.raises(error, match=msg):
         obj.transform({"A": [op]})
 
 
 @pytest.mark.parametrize("op", frame_kernels_raise)
-def test_transform_partial_failure_typeerror(request, op):
+def test_transform_failure_typeerror(request, op):
     # GH 35964
 
     if op == "ngroup":
@@ -168,62 +173,52 @@ def test_transform_partial_failure_typeerror(request, op):
 
     # Using object makes most transform kernels fail
     df = DataFrame({"A": 3 * [object], "B": [1, 2, 3]})
+    if op == "rank":
+        error = ValueError
+        msg = "Transform function failed"
+    else:
+        error = TypeError
+        msg = "|".join(
+            [
+                "not supported between instances of 'type' and 'type'",
+                "unsupported operand type",
+            ]
+        )
 
-    expected = df[["B"]].transform([op])
-    match = r"\['A'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform([op])
-    tm.assert_equal(result, expected)
+    with pytest.raises(error, match=msg):
+        df.transform([op])
 
-    expected = df[["B"]].transform({"B": op})
-    match = r"\['A'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform({"A": op, "B": op})
-    tm.assert_equal(result, expected)
+    with pytest.raises(error, match=msg):
+        df.transform({"A": op, "B": op})
 
-    expected = df[["B"]].transform({"B": [op]})
-    match = r"\['A'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform({"A": [op], "B": [op]})
-    tm.assert_equal(result, expected)
+    with pytest.raises(error, match=msg):
+        df.transform({"A": [op], "B": [op]})
 
-    expected = df.transform({"A": ["shift"], "B": [op]})
-    match = rf"\['{op}'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform({"A": [op, "shift"], "B": [op]})
-    tm.assert_equal(result, expected)
+    with pytest.raises(error, match=msg):
+        df.transform({"A": [op, "shift"], "B": [op]})
 
 
-def test_transform_partial_failure_valueerror():
+def test_transform_failure_valueerror():
     # GH 40211
-    match = ".*did not transform successfully"
-
     def op(x):
         if np.sum(np.sum(x)) < 10:
             raise ValueError
         return x
 
     df = DataFrame({"A": [1, 2, 3], "B": [400, 500, 600]})
+    msg = "Transform function failed"
 
-    expected = df[["B"]].transform([op])
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform([op])
-    tm.assert_equal(result, expected)
+    with pytest.raises(ValueError, match=msg):
+        df.transform([op])
 
-    expected = df[["B"]].transform({"B": op})
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform({"A": op, "B": op})
-    tm.assert_equal(result, expected)
+    with pytest.raises(ValueError, match=msg):
+        df.transform({"A": op, "B": op})
 
-    expected = df[["B"]].transform({"B": [op]})
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform({"A": [op], "B": [op]})
-    tm.assert_equal(result, expected)
+    with pytest.raises(ValueError, match=msg):
+        df.transform({"A": [op], "B": [op]})
 
-    expected = df.transform({"A": ["shift"], "B": [op]})
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = df.transform({"A": [op, "shift"], "B": [op]})
-    tm.assert_equal(result, expected)
+    with pytest.raises(ValueError, match=msg):
+        df.transform({"A": [op, "shift"], "B": [op]})
 
 
 @pytest.mark.parametrize("use_apply", [True, False])

pandas/tests/apply/test_invalid_arg.py

@@ -283,7 +283,7 @@ def test_agg_none_to_type():
 def test_transform_none_to_type():
     # GH#34377
     df = DataFrame({"a": [None]})
-    msg = "Transform function failed"
+    msg = "argument must be a"
     with pytest.raises(TypeError, match=msg):
         df.transform({"a": int})
 

pandas/tests/apply/test_series_apply.py

@@ -280,72 +280,59 @@ def test_transform_partial_failure(op, request):
     # GH 35964
     if op in ("ffill", "bfill", "pad", "backfill", "shift"):
         request.node.add_marker(
-            pytest.mark.xfail(
-                raises=AssertionError, reason=f"{op} is successful on any dtype"
-            )
+            pytest.mark.xfail(reason=f"{op} is successful on any dtype")
         )
 
     # Using object makes most transform kernels fail
     ser = Series(3 * [object])
 
-    expected = ser.transform(["shift"])
-    match = rf"\['{op}'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform([op, "shift"])
-    tm.assert_equal(result, expected)
-
-    expected = ser.transform({"B": "shift"})
-    match = r"\['A'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform({"A": op, "B": "shift"})
-    tm.assert_equal(result, expected)
-
-    expected = ser.transform({"B": ["shift"]})
-    match = r"\['A'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform({"A": [op], "B": ["shift"]})
-    tm.assert_equal(result, expected)
-
-    match = r"\['B'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        expected = ser.transform({"A": ["shift"], "B": [op]})
-    match = rf"\['{op}'\] did not transform successfully"
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform({"A": [op, "shift"], "B": [op]})
-    tm.assert_equal(result, expected)
+    if op in ("fillna", "ngroup", "rank"):
+        error = ValueError
+        msg = "Transform function failed"
+    else:
+        error = TypeError
+        msg = "|".join(
+            [
+                "not supported between instances of 'type' and 'type'",
+                "unsupported operand type",
+            ]
+        )
+
+    with pytest.raises(error, match=msg):
+        ser.transform([op, "shift"])
+
+    with pytest.raises(error, match=msg):
+        ser.transform({"A": op, "B": "shift"})
+
+    with pytest.raises(error, match=msg):
+        ser.transform({"A": [op], "B": ["shift"]})
+
+    with pytest.raises(error, match=msg):
+        ser.transform({"A": [op, "shift"], "B": [op]})
 
 
 def test_transform_partial_failure_valueerror():
     # GH 40211
-    match = ".*did not transform successfully"
-
     def noop(x):
         return x
 
     def raising_op(_):
         raise ValueError
 
     ser = Series(3 * [object])
+    msg = "Transform function failed"
+
+    with pytest.raises(ValueError, match=msg):
+        ser.transform([noop, raising_op])
+
+    with pytest.raises(ValueError, match=msg):
+        ser.transform({"A": raising_op, "B": noop})
+
+    with pytest.raises(ValueError, match=msg):
+        ser.transform({"A": [raising_op], "B": [noop]})
 
-    expected = ser.transform([noop])
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform([noop, raising_op])
-    tm.assert_equal(result, expected)
-
-    expected = ser.transform({"B": noop})
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform({"A": raising_op, "B": noop})
-    tm.assert_equal(result, expected)
-
-    expected = ser.transform({"B": [noop]})
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform({"A": [raising_op], "B": [noop]})
-    tm.assert_equal(result, expected)
-
-    expected = ser.transform({"A": [noop], "B": [noop]})
-    with tm.assert_produces_warning(FutureWarning, match=match):
-        result = ser.transform({"A": [noop, raising_op], "B": [noop]})
-    tm.assert_equal(result, expected)
+    with pytest.raises(ValueError, match=msg):
+        ser.transform({"A": [noop, raising_op], "B": [noop]})
 
 
 def test_demo():