TYP: fix a few errors found by pandas-stub

Author: twoertwein

pandas/_testing/asserters.py

@@ -864,7 +864,7 @@ def assert_series_equal(
     check_dtype: bool | Literal["equiv"] = True,
     check_index_type="equiv",
     check_series_type=True,
-    check_less_precise=no_default,
+    check_less_precise: bool | int | NoDefault = no_default,
     check_names=True,
     check_exact=False,
     check_datetimelike_compat=False,

pandas/core/generic.py

@@ -1050,7 +1050,7 @@ def _rename(
             return result.__finalize__(self, method="rename")
 
     @rewrite_axis_style_signature("mapper", [("copy", True), ("inplace", False)])
-    def rename_axis(self, mapper=lib.no_default, **kwargs):
+    def rename_axis(self, mapper: IndexLabel = lib.no_default, **kwargs):
         """
         Set the name of the axis for the index or columns.
 

pandas/core/groupby/groupby.py

@@ -4050,7 +4050,12 @@ def _reindex_output(
             # "ndarray[Any, dtype[floating[_64Bit]]]"; expected "Index"
             levels_list.append(qs)  # type: ignore[arg-type]
             names = names + [None]
-        index, _ = MultiIndex.from_product(levels_list, names=names).sortlevel()
+        # error: Argument "names" to "from_product" of "MultiIndex" has
+        # incompatible type "List[Hashable]"; expected "Union[Sequence[
+        # Optional[str]], Literal[_NoDefault.no_default]]"
+        index, _ = MultiIndex.from_product(
+            levels_list, names=names  # type: ignore[arg-type]
+        ).sortlevel()
 
         if self.as_index:
             # Always holds for SeriesGroupBy unless GH#36507 is implemented

pandas/core/indexes/multi.py

@@ -578,7 +578,10 @@ def from_tuples(
 
     @classmethod
     def from_product(
-        cls, iterables, sortorder=None, names=lib.no_default
+        cls,
+        iterables: Sequence[Iterable[Hashable]],
+        sortorder: int | None = None,
+        names: Sequence[str | None] | lib.NoDefault = lib.no_default,
     ) -> MultiIndex:
         """
         Make a MultiIndex from the cartesian product of multiple iterables.

pandas/plotting/_matplotlib/groupby.py

@@ -112,7 +112,9 @@ def reconstruct_data_with_by(
 
     data_list = []
     for key, group in grouped:
-        columns = MultiIndex.from_product([[key], cols])
+        # error: List item 1 has incompatible type "Union[Hashable,
+        # Sequence[Hashable]]"; expected "Iterable[Hashable]"
+        columns = MultiIndex.from_product([[key], cols])  # type: ignore[list-item]
         sub_group = group[cols]
         sub_group.columns = columns
         data_list.append(sub_group)