CLN: assorted cleanups (#38275)

Author: jbrockmendel

pandas/_libs/reduction.pyx

@@ -367,9 +367,9 @@ def apply_frame_axis0(object frame, object f, object names,
 
             try:
                 piece = f(chunk)
-            except Exception:
+            except Exception as err:
                 # We can't be more specific without knowing something about `f`
-                raise InvalidApply('Let this error raise above us')
+                raise InvalidApply("Let this error raise above us") from err
 
             # Need to infer if low level index slider will cause segfaults
             require_slow_apply = i == 0 and piece is chunk

pandas/core/groupby/generic.py

@@ -63,7 +63,7 @@
 import pandas.core.common as com
 from pandas.core.construction import create_series_with_explicit_dtype
 from pandas.core.frame import DataFrame
-from pandas.core.generic import ABCDataFrame, ABCSeries, NDFrame
+from pandas.core.generic import NDFrame
 from pandas.core.groupby import base
 from pandas.core.groupby.groupby import (
     GroupBy,
@@ -531,7 +531,7 @@ def _transform_general(self, func, *args, **kwargs):
             object.__setattr__(group, "name", name)
             res = func(group, *args, **kwargs)
 
-            if isinstance(res, (ABCDataFrame, ABCSeries)):
+            if isinstance(res, (DataFrame, Series)):
                 res = res._values
 
             results.append(klass(res, index=group.index))

pandas/core/groupby/groupby.py

@@ -966,22 +966,6 @@ def _cumcount_array(self, ascending: bool = True):
         rev[sorter] = np.arange(count, dtype=np.intp)
         return out[rev].astype(np.int64, copy=False)
 
-    def _transform_should_cast(self, func_nm: str) -> bool:
-        """
-        Parameters
-        ----------
-        func_nm: str
-            The name of the aggregation function being performed
-
-        Returns
-        -------
-        bool
-            Whether transform should attempt to cast the result of aggregation
-        """
-        filled_series = self.grouper.size().fillna(0)
-        assert filled_series is not None
-        return filled_series.gt(0).any() and func_nm not in base.cython_cast_blocklist
-
     def _cython_transform(
         self, how: str, numeric_only: bool = True, axis: int = 0, **kwargs
     ):

pandas/core/groupby/grouper.py

@@ -18,7 +18,6 @@
     is_scalar,
     is_timedelta64_dtype,
 )
-from pandas.core.dtypes.generic import ABCSeries
 
 import pandas.core.algorithms as algorithms
 from pandas.core.arrays import Categorical, ExtensionArray
@@ -345,9 +344,7 @@ def _set_grouper(self, obj: FrameOrSeries, sort: bool = False):
         if self.key is not None:
             key = self.key
             # The 'on' is already defined
-            if getattr(self.grouper, "name", None) == key and isinstance(
-                obj, ABCSeries
-            ):
+            if getattr(self.grouper, "name", None) == key and isinstance(obj, Series):
                 # pandas\core\groupby\grouper.py:348: error: Item "None" of
                 # "Optional[Any]" has no attribute "take"  [union-attr]
                 ax = self._grouper.take(obj.index)  # type: ignore[union-attr]

pandas/core/indexes/base.py

@@ -70,7 +70,6 @@
     ABCMultiIndex,
     ABCPandasArray,
     ABCPeriodIndex,
-    ABCRangeIndex,
     ABCSeries,
     ABCTimedeltaIndex,
 )
@@ -3494,12 +3493,7 @@ def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
         target = ensure_has_len(target)  # target may be an iterator
 
         if not isinstance(target, Index) and len(target) == 0:
-            values: Union[range, ExtensionArray, np.ndarray]
-            if isinstance(self, ABCRangeIndex):
-                values = range(0)
-            else:
-                values = self._data[:0]  # appropriately-dtyped empty array
-            target = self._simple_new(values, name=self.name)
+            target = self[:0]
         else:
             target = ensure_index(target)
 
@@ -3829,6 +3823,7 @@ def _join_non_unique(self, other, how="left", return_indexers=False):
         else:
             return join_index
 
+    @final
     def _join_level(
         self, other, level, how="left", return_indexers=False, keep_order=True
     ):
@@ -3972,6 +3967,7 @@ def _get_leaf_sorter(labels):
         else:
             return join_index
 
+    @final
     def _join_monotonic(self, other, how="left", return_indexers=False):
         # We only get here with matching dtypes
         assert other.dtype == self.dtype

pandas/tests/series/indexing/test_xs.py

@@ -56,8 +56,8 @@ def test_series_xs_droplevel_false(self):
         mi = MultiIndex.from_tuples(
             [("a", "x"), ("a", "y"), ("b", "x")], names=["level1", "level2"]
         )
-        df = Series([1, 1, 1], index=mi)
-        result = df.xs("a", axis=0, drop_level=False)
+        ser = Series([1, 1, 1], index=mi)
+        result = ser.xs("a", axis=0, drop_level=False)
         expected = Series(
             [1, 1],
             index=MultiIndex.from_tuples(