CLN: Index methods incorrectly assuming object dtype (#45767)

Author: jbrockmendel

pandas/core/indexes/base.py

@@ -391,7 +391,6 @@ def _outer_indexer(
  _comparables: list[str] = ["name"]
  _attributes: list[str] = ["name"]
  _is_numeric_dtype: bool = False
- _can_hold_na: bool = True
  _can_hold_strings: bool = True
 
  # Whether this index is a NumericIndex, but not a Int64Index, Float64Index,
@@ -2206,6 +2205,20 @@ def _get_grouper_for_level(self, mapper, *, level=None):
  # --------------------------------------------------------------------
  # Introspection Methods
 
+ @cache_readonly
+ @final
+ def _can_hold_na(self) -> bool:
+ if isinstance(self.dtype, ExtensionDtype):
+ if isinstance(self.dtype, IntervalDtype):
+ # FIXME(GH#45720): this is inaccurate for integer-backed
+ # IntervalArray, but without it other.categories.take raises
+ # in IntervalArray._cmp_method
+ return True
+ return self.dtype._can_hold_na
+ if self.dtype.kind in ["i", "u", "b"]:
+ return False
+ return True
+
  @final
  @property
  def is_monotonic(self) -> bool:
@@ -2662,10 +2675,21 @@ def inferred_type(self) -> str_t:
  return lib.infer_dtype(self._values, skipna=False)
 
  @cache_readonly
+ @final
  def _is_all_dates(self) -> bool:
  """
  Whether or not the index values only consist of dates.
  """
+
+ if needs_i8_conversion(self.dtype):
+ return True
+ elif self.dtype != _dtype_obj:
+ # TODO(ExtensionIndex): 3rd party EA might override?
+ # Note: this includes IntervalIndex, even when the left/right
+ # contain datetime-like objects.
+ return False
+ elif self._is_multi:
+ return False
  return is_datetime_array(ensure_object(self._values))
 
  @cache_readonly
@@ -6159,6 +6183,10 @@ def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
  """
  Can we compare values of the given dtype to our own?
  """
+ if self.dtype.kind == "b":
+ return dtype.kind == "b"
+ elif is_numeric_dtype(self.dtype):
+ return is_numeric_dtype(dtype)
  return True
 
  @final

pandas/core/indexes/datetimelike.py

@@ -100,10 +100,6 @@ class DatetimeIndexOpsMixin(NDArrayBackedExtensionIndex):
  ),
  )
 
- @property
- def _is_all_dates(self) -> bool:
- return True
-
  # ------------------------------------------------------------------------
 
  def equals(self, other: Any) -> bool:
@@ -151,8 +147,6 @@ def __contains__(self, key: Any) -> bool:
  return False
  return True
 
- _can_hold_na = True
-
  def _convert_tolerance(self, tolerance, target):
  tolerance = np.asarray(to_timedelta(tolerance).to_numpy())
  return super()._convert_tolerance(tolerance, target)

pandas/core/indexes/interval.py

@@ -897,14 +897,6 @@ def _intersection_non_unique(self, other: IntervalIndex) -> IntervalIndex:
 
  # --------------------------------------------------------------------
 
- @property
- def _is_all_dates(self) -> bool:
- """
- This is False even when left/right contain datetime-like objects,
- as the check is done on the Interval itself
- """
- return False
-
  def _get_engine_target(self) -> np.ndarray:
  # Note: we _could_ use libjoin functions by either casting to object
  # dtype or constructing tuples (faster than constructing Intervals)

pandas/core/indexes/multi.py

@@ -1841,10 +1841,6 @@ def to_flat_index(self) -> Index:
  """
  return Index(self._values, tupleize_cols=False)
 
- @property
- def _is_all_dates(self) -> bool:
- return False
-
  def is_lexsorted(self) -> bool:
  warnings.warn(
  "MultiIndex.is_lexsorted is deprecated as a public function, "

pandas/core/indexes/numeric.py

@@ -14,7 +14,6 @@
 )
 from pandas._typing import (
  Dtype,
- DtypeObj,
  npt,
 )
 from pandas.util._decorators import (
@@ -91,14 +90,6 @@ class NumericIndex(Index):
  _can_hold_strings = False
  _is_backward_compat_public_numeric_index: bool = True
 
- # error: Signature of "_can_hold_na" incompatible with supertype "Index"
- @cache_readonly
- def _can_hold_na(self) -> bool: # type: ignore[override]
- if is_float_dtype(self.dtype):
- return True
- else:
- return False
-
  _engine_types: dict[np.dtype, type[libindex.IndexEngine]] = {
  np.dtype(np.int8): libindex.Int8Engine,
  np.dtype(np.int16): libindex.Int16Engine,
@@ -268,10 +259,6 @@ def _convert_tolerance(self, tolerance, target):
  )
  return tolerance
 
- def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
- # If we ever have BoolIndex or ComplexIndex, this may need to be tightened
- return is_numeric_dtype(dtype)
-
  @classmethod
  def _assert_safe_casting(cls, data: np.ndarray, subarr: np.ndarray) -> None:
  """
@@ -284,13 +271,6 @@ def _assert_safe_casting(cls, data: np.ndarray, subarr: np.ndarray) -> None:
  if not np.array_equal(data, subarr):
  raise TypeError("Unsafe NumPy casting, you must explicitly cast")
 
- @property
- def _is_all_dates(self) -> bool:
- """
- Checks that all the labels are datetime objects.
- """
- return False
-
  def _format_native_types(
  self, *, na_rep="", float_format=None, decimal=".", quoting=None, **kwargs
  ):