Closes #5394 and #5395: pandas extension update: adding ndarray return to isna and isnull to Categoical Extension Array (#5440)

This PR (Closes #5394 and #5395) adds `ndarray` return to `isna` and
`isnull` to Categoical Extension Array

Co-authored-by: jaketrookman <jaketrookman@users.noreply.github.com>

Author: jaketrookman

arkouda/pandas/extension/_arkouda_categorical_array.py

@@ -13,7 +13,6 @@
 from pandas.api.extensions import ExtensionArray
 from pandas.core.dtypes.dtypes import ExtensionDtype
 
-from arkouda.numpy.dtypes import bool_
 from arkouda.numpy.pdarrayclass import pdarray
 
 from ._arkouda_array import ArkoudaArray
@@ -335,10 +334,41 @@ def astype(
         casted = data.astype(dtype)
         return ArkoudaExtensionArray._from_sequence(casted)
 
-    def isna(self):
-        from arkouda.numpy.pdarraycreation import zeros
+    def isna(self) -> np.ndarray:
+        """
+        # Return a boolean mask indicating missing values.
+
+        # This implements the pandas ExtensionArray.isna contract and returns a
+        # NumPy ndarray[bool] of the same length as this categorical array.
+
+        # Returns
+        # -------
+        # np.ndarray
+        #     Boolean mask where True indicates a missing value.
+
+        # Raises
+        # ------
+        # TypeError
+        #     If the underlying categorical cannot expose its codes or if missing
+        #     detection is unsupported.
+        #
+        """
+        from arkouda.categorical import Categorical
+
+        data = self._data  # should be an arkouda.Categorical
 
-        return zeros(self._data.size, dtype=bool_)
+        if not isinstance(data, Categorical):
+            raise TypeError("ArkoudaCategorical.isna requires an arkouda.Categorical backend")
+
+        # Missing values in ArkoudaCategorical are represented by code == -1
+        try:
+            return (data.codes == -1).to_ndarray()
+        except Exception as e:
+            raise TypeError(f"Unable to determine missing values: {e}") from e
+
+    def isnull(self):
+        """Alias for isna()."""
+        return self.isna()
 
     @property
     def dtype(self):
@@ -534,9 +564,6 @@ def describe(self, *args, **kwargs):
     def from_codes(cls, *args, **kwargs):
         raise NotImplementedError("from_codes is not yet implemented for ArkoudaCategorical.")
 
-    def isnull(self, *args, **kwargs):
-        self._categorical_not_implemented("isnull")
-
     def memory_usage(self, *args, **kwargs):
         self._categorical_not_implemented("memory_usage")
 

tests/pandas/extension/arkouda_categorical_extension.py

@@ -144,6 +144,47 @@ def test_take_categorical_scaling(self, prob_size):
         idx1 = ak.arange(prob_size, dtype=ak.int64) // 2
         assert_equivalent(arr.take(idx1)._data.to_strings(), s.take(idx1.to_ndarray()).to_numpy())
 
+    def test_categorical_isna_and_isnull(self):
+        from arkouda.pandas.extension import ArkoudaCategorical
+
+        cases = [
+            # Case 1: no missing values
+            (
+                ak.Categorical(ak.array(["a", "b", "c"])),
+                np.array([False, False, False]),
+            ),
+            # Case 2: some missing values (must inject after construction)
+            (
+                # construct with valid codes, then rewrite codes to include -1
+                (
+                    lambda: (lambda cat: (setattr(cat, "codes", ak.array([0, -1, 1, -1])) or cat))(
+                        ak.Categorical.from_codes(
+                            codes=ak.array([0, 0, 1, 1]), categories=ak.array(["x", "y"])
+                        )
+                    )
+                )(),
+                np.array([False, True, False, True]),
+            ),
+            # Case 3: empty categorical
+            (
+                ak.Categorical(ak.array([])),
+                np.array([], dtype=bool),
+            ),
+        ]
+
+        for cat, expected in cases:
+            arr = ArkoudaCategorical(cat)
+
+            out_isna = arr.isna()
+            out_isnull = arr.isnull()
+
+            assert isinstance(out_isna, np.ndarray)
+            assert isinstance(out_isnull, np.ndarray)
+            assert out_isna.dtype == bool
+            assert out_isnull.dtype == bool
+            assert np.array_equal(out_isna, expected)
+            assert np.array_equal(out_isnull, expected)
+
 
 class TestArkoudaCategoricalAsType:
     def test_categorical_array_astype_category_stays_extension(