Pass through user warnings, update whatsnew

Author: rhshadrach

doc/source/whatsnew/v1.4.0.rst

@@ -337,7 +337,7 @@ Other Deprecations
 - Deprecated the ``squeeze`` argument to :meth:`read_csv`, :meth:`read_table`, and :meth:`read_excel`. Users should squeeze the DataFrame afterwards with ``.squeeze("columns")`` instead. (:issue:`43242`)
 - Deprecated the ``index`` argument to :class:`SparseArray` construction (:issue:`23089`)
 - Deprecated :meth:`.Rolling.validate`, :meth:`.Expanding.validate`, and :meth:`.ExponentialMovingWindow.validate` (:issue:`43665`)
-- Deprecated silent dropping of columns that raised a ``TypeError``, ``DataError``, or some cases of ``ValueError`` in :class:`Series.aggregate` and :class:`DataFrame.aggregate` when used with a list (:issue:`43740`)
+- Deprecated silent dropping of columns that raised a ``TypeError``, ``DataError``, and some cases of ``ValueError`` in :meth:`Series.aggregate`, :meth:`DataFrame.aggregate`, :meth:`Series.groupby.aggregate`, and :meth:`DataFrame.groupby.aggregate` when used with a list (:issue:`43740`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/apply.py

@@ -4,6 +4,7 @@
 from collections import defaultdict
 from functools import partial
 import inspect
+import re
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -338,6 +339,12 @@ def agg_list_like(self) -> DataFrame | Series:
         keys = []
         failed_names = []
 
+        depr_nuisance_columns_msg = (
+            "{} did not aggregate successfully. If any error is "
+            "raised this will raise in a future version of pandas. "
+            "Drop these columns/ops to avoid this warning."
+        )
+
         # degenerate case
         if selected_obj.ndim == 1:
             for a in arg:
@@ -360,10 +367,24 @@ def agg_list_like(self) -> DataFrame | Series:
             for index, col in enumerate(selected_obj):
                 colg = obj._gotitem(col, ndim=1, subset=selected_obj.iloc[:, index])
                 try:
-                    with warnings.catch_warnings(record=True) as w:
+                    # Capture and suppress any warnings emitted by us in the call
+                    # to agg below, but pass through any warnings that were
+                    # generated otherwise.
+                    with warnings.catch_warnings(record=True) as record:
                         new_res = colg.aggregate(arg)
-                        if len(w) > 0:
-                            failed_names.append(col)
+                    if len(record) > 0:
+                        match = re.compile(depr_nuisance_columns_msg.format(".*"))
+                        for warning in record:
+                            if re.match(match, str(warning.message)):
+                                failed_names.append(col)
+                            else:
+                                warnings.warn_explicit(
+                                    message=warning.message,
+                                    category=warning.category,
+                                    filename=warning.filename,
+                                    lineno=warning.lineno,
+                                )
+
                 except (TypeError, DataError):
                     failed_names.append(col)
                 except ValueError as err:
@@ -391,9 +412,7 @@ def agg_list_like(self) -> DataFrame | Series:
 
         if len(failed_names) > 0:
             warnings.warn(
-                f"{failed_names} did not aggregate 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.",
+                depr_nuisance_columns_msg.format(failed_names),
                 FutureWarning,
                 stacklevel=find_stack_level(),
             )

pandas/tests/apply/test_frame_apply.py

@@ -1462,3 +1462,20 @@ def test_apply_getitem_axis_1():
     result = df[["a", "a"]].apply(lambda x: x[0] + x[1], axis=1)
     expected = Series([0, 2, 4])
     tm.assert_series_equal(result, expected)
+
+
+def test_nuisance_depr_passes_through_warnings():
+    # GH 43740
+    # DataFrame.agg with list-likes may emit warnings for both individual
+    # args and for entire columns, but we only want to emit once. We
+    # catch and suppress the warnings for individual args, but need to make
+    # sure if some other warnings were raised, they get passed through to
+    # the user.
+
+    def foo(x):
+        warnings.warn("Hello, World!")
+        return x.sum()
+
+    df = DataFrame({"a": [1, 2, 3]})
+    with tm.assert_produces_warning(UserWarning, match="Hello, World!"):
+        df.agg([foo])