TST: Address test warnings (#48075)

Author: mroeschke

pandas/core/groupby/generic.py

@@ -973,7 +973,7 @@ def _aggregate_frame(self, func, *args, **kwargs) -> DataFrame:
         result: dict[Hashable, NDFrame | np.ndarray] = {}
         if self.axis == 0:
             # test_pass_args_kwargs_duplicate_columns gets here with non-unique columns
-            for name, data in self:
+            for name, data in self.grouper.get_iterator(obj, self.axis):
                 fres = func(data, *args, **kwargs)
                 result[name] = fres
         else:

pandas/core/groupby/groupby.py

@@ -828,7 +828,7 @@ def __iter__(self) -> Iterator[tuple[Hashable, NDFrameT]]:
                 (
                     "In a future version of pandas, a length 1 "
                     "tuple will be returned when iterating over a "
-                    "a groupby with a grouper equal to a list of "
+                    "groupby with a grouper equal to a list of "
                     "length 1. Don't supply a list with a single grouper "
                     "to avoid this warning."
                 ),

pandas/tests/groupby/aggregate/test_numba.py

@@ -214,6 +214,7 @@ def func_kwargs(values, index):
 
 
 @td.skip_if_no("numba")
+@pytest.mark.filterwarnings("ignore")
 def test_multiindex_one_key(nogil, parallel, nopython):
     def numba_func(values, index):
         return 1

pandas/tests/groupby/test_groupby.py

@@ -2837,7 +2837,7 @@ def test_single_element_list_grouping():
     )
     msg = (
         "In a future version of pandas, a length 1 "
-        "tuple will be returned when iterating over a "
+        "tuple will be returned when iterating over "
         "a groupby with a grouper equal to a list of "
         "length 1. Don't supply a list with a single grouper "
         "to avoid this warning."

pandas/tests/groupby/transform/test_numba.py

@@ -202,6 +202,7 @@ def func_kwargs(values, index):
 
 
 @td.skip_if_no("numba")
+@pytest.mark.filterwarnings("ignore")
 def test_multiindex_one_key(nogil, parallel, nopython):
     def numba_func(values, index):
         return 1

pandas/tests/io/excel/test_readers.py

@@ -89,6 +89,7 @@ def _transfer_marks(engine, read_ext):
         for ext in read_ext_params
         if _is_valid_engine_ext_pair(eng, ext)
     ],
+    ids=str,
 )
 def engine_and_read_ext(request):
     """
@@ -654,6 +655,7 @@ def test_read_excel_blank_with_header(self, read_ext):
         actual = pd.read_excel("blank_with_header" + read_ext, sheet_name="Sheet1")
         tm.assert_frame_equal(actual, expected)
 
+    @pytest.mark.filterwarnings("ignore:Cell A4 is marked:UserWarning:openpyxl")
     def test_date_conversion_overflow(self, request, engine, read_ext):
         # GH 10001 : pandas.ExcelFile ignore parse_dates=False
         if engine == "pyxlsb":

pandas/tests/io/excel/test_writers.py

@@ -875,7 +875,7 @@ def test_to_excel_output_encoding(self, ext):
         )
 
         with tm.ensure_clean("__tmp_to_excel_float_format__." + ext) as filename:
-            df.to_excel(filename, sheet_name="TestSheet", encoding="utf8")
+            df.to_excel(filename, sheet_name="TestSheet")
             result = pd.read_excel(filename, sheet_name="TestSheet", index_col=0)
             tm.assert_frame_equal(result, df)
 
@@ -1287,6 +1287,7 @@ def test_deprecated_attr(self, engine, ext, attr):
                 # Some engines raise if nothing is written
                 DataFrame().to_excel(writer)
 
+    @pytest.mark.filterwarnings("ignore:Calling close():UserWarning:xlsxwriter")
     @pytest.mark.parametrize(
         "attr, args", [("save", ()), ("write_cells", ([], "test"))]
     )

pandas/tests/reshape/merge/test_join.py

@@ -737,7 +737,9 @@ def _check_join(left, right, result, join_col, how="left", lsuffix="_x", rsuffix
     left_grouped = left.groupby(join_col)
     right_grouped = right.groupby(join_col)
 
-    for group_key, group in result.groupby(join_col):
+    for group_key, group in result.groupby(
+        join_col if len(join_col) > 1 else join_col[0]
+    ):
         l_joined = _restrict_to_columns(group, left.columns, lsuffix)
         r_joined = _restrict_to_columns(group, right.columns, rsuffix)