Backport PR pandas-dev#54566 on branch 2.1.x (ENH: support Index.any/all with float, timedelta64 dtypes) (pandas-dev#54693)

Backport PR pandas-dev#54566: ENH: support Index.any/all with float, timedelta64 dtypes

Co-authored-by: jbrockmendel <jbrockmendel@gmail.com>

Author: meeseeksmachine

doc/source/whatsnew/v2.1.0.rst

@@ -265,6 +265,7 @@ Other enhancements
 - Many read/to_* functions, such as :meth:`DataFrame.to_pickle` and :func:`read_csv`, support forwarding compression arguments to ``lzma.LZMAFile`` (:issue:`52979`)
 - Reductions :meth:`Series.argmax`, :meth:`Series.argmin`, :meth:`Series.idxmax`, :meth:`Series.idxmin`, :meth:`Index.argmax`, :meth:`Index.argmin`, :meth:`DataFrame.idxmax`, :meth:`DataFrame.idxmin` are now supported for object-dtype (:issue:`4279`, :issue:`18021`, :issue:`40685`, :issue:`43697`)
 - :meth:`DataFrame.to_parquet` and :func:`read_parquet` will now write and read ``attrs`` respectively (:issue:`54346`)
+- :meth:`Index.all` and :meth:`Index.any` with floating dtypes and timedelta64 dtypes no longer raise ``TypeError``, matching the :meth:`Series.all` and :meth:`Series.any` behavior (:issue:`54566`)
 - :meth:`Series.cummax`, :meth:`Series.cummin` and :meth:`Series.cumprod` are now supported for pyarrow dtypes with pyarrow version 13.0 and above (:issue:`52085`)
 - Added support for the DataFrame Consortium Standard (:issue:`54383`)
 - Performance improvement in :meth:`.DataFrameGroupBy.quantile` and :meth:`.SeriesGroupBy.quantile` (:issue:`51722`)

pandas/core/indexes/base.py

@@ -7215,11 +7215,12 @@ def any(self, *args, **kwargs):
         """
         nv.validate_any(args, kwargs)
         self._maybe_disable_logical_methods("any")
-        # error: Argument 1 to "any" has incompatible type "ArrayLike"; expected
-        # "Union[Union[int, float, complex, str, bytes, generic], Sequence[Union[int,
-        # float, complex, str, bytes, generic]], Sequence[Sequence[Any]],
-        # _SupportsArray]"
-        return np.any(self.values)  # type: ignore[arg-type]
+        vals = self._values
+        if not isinstance(vals, np.ndarray):
+            # i.e. EA, call _reduce instead of "any" to get TypeError instead
+            #  of AttributeError
+            return vals._reduce("any")
+        return np.any(vals)
 
     def all(self, *args, **kwargs):
         """
@@ -7262,11 +7263,12 @@ def all(self, *args, **kwargs):
         """
         nv.validate_all(args, kwargs)
         self._maybe_disable_logical_methods("all")
-        # error: Argument 1 to "all" has incompatible type "ArrayLike"; expected
-        # "Union[Union[int, float, complex, str, bytes, generic], Sequence[Union[int,
-        # float, complex, str, bytes, generic]], Sequence[Sequence[Any]],
-        # _SupportsArray]"
-        return np.all(self.values)  # type: ignore[arg-type]
+        vals = self._values
+        if not isinstance(vals, np.ndarray):
+            # i.e. EA, call _reduce instead of "all" to get TypeError instead
+            #  of AttributeError
+            return vals._reduce("all")
+        return np.all(vals)
 
     @final
     def _maybe_disable_logical_methods(self, opname: str_t) -> None:
@@ -7275,9 +7277,9 @@ def _maybe_disable_logical_methods(self, opname: str_t) -> None:
         """
         if (
             isinstance(self, ABCMultiIndex)
-            or needs_i8_conversion(self.dtype)
-            or isinstance(self.dtype, (IntervalDtype, CategoricalDtype))
-            or is_float_dtype(self.dtype)
+            # TODO(3.0): PeriodArray and DatetimeArray any/all will raise,
+            #  so checking needs_i8_conversion will be unnecessary
+            or (needs_i8_conversion(self.dtype) and self.dtype.kind != "m")
         ):
             # This call will raise
             make_invalid_op(opname)(self)

pandas/tests/indexes/numeric/test_numeric.py

@@ -227,6 +227,14 @@ def test_fillna_float64(self):
         exp = Index([1.0, "obj", 3.0], name="x")
         tm.assert_index_equal(idx.fillna("obj"), exp, exact=True)
 
+    def test_logical_compat(self, simple_index):
+        idx = simple_index
+        assert idx.all() == idx.values.all()
+        assert idx.any() == idx.values.any()
+
+        assert idx.all() == idx.to_series().all()
+        assert idx.any() == idx.to_series().any()
+
 
 class TestNumericInt:
     @pytest.fixture(params=[np.int64, np.int32, np.int16, np.int8, np.uint64])

pandas/tests/indexes/test_base.py

@@ -692,7 +692,12 @@ def test_format_missing(self, vals, nulls_fixture):
     @pytest.mark.parametrize("op", ["any", "all"])
     def test_logical_compat(self, op, simple_index):
         index = simple_index
-        assert getattr(index, op)() == getattr(index.values, op)()
+        left = getattr(index, op)()
+        assert left == getattr(index.values, op)()
+        right = getattr(index.to_series(), op)()
+        # left might not match right exactly in e.g. string cases where the
+        # because we use np.any/all instead of .any/all
+        assert bool(left) == bool(right)
 
     @pytest.mark.parametrize(
         "index", ["string", "int64", "int32", "float64", "float32"], indirect=True

pandas/tests/indexes/test_old_base.py

@@ -209,17 +209,25 @@ def test_numeric_compat(self, simple_index):
             1 // idx
 
     def test_logical_compat(self, simple_index):
-        if (
-            isinstance(simple_index, RangeIndex)
-            or is_numeric_dtype(simple_index.dtype)
-            or simple_index.dtype == object
-        ):
+        if simple_index.dtype == object:
             pytest.skip("Tested elsewhere.")
         idx = simple_index
-        with pytest.raises(TypeError, match="cannot perform all"):
-            idx.all()
-        with pytest.raises(TypeError, match="cannot perform any"):
-            idx.any()
+        if idx.dtype.kind in "iufcbm":
+            assert idx.all() == idx._values.all()
+            assert idx.all() == idx.to_series().all()
+            assert idx.any() == idx._values.any()
+            assert idx.any() == idx.to_series().any()
+        else:
+            msg = "cannot perform (any|all)"
+            if isinstance(idx, IntervalIndex):
+                msg = (
+                    r"'IntervalArray' with dtype interval\[.*\] does "
+                    "not support reduction '(any|all)'"
+                )
+            with pytest.raises(TypeError, match=msg):
+                idx.all()
+            with pytest.raises(TypeError, match=msg):
+                idx.any()
 
     def test_repr_roundtrip(self, simple_index):
         if isinstance(simple_index, IntervalIndex):