TST: enable 2D tests for Categorical

pandas/core/arrays/categorical.py

@@ -6,7 +6,6 @@
 from shutil import get_terminal_size
 from typing import (
     TYPE_CHECKING,
-    Any,
     Hashable,
     Sequence,
     TypeVar,
@@ -38,10 +37,6 @@
     Dtype,
     NpDtype,
     Ordered,
-    PositionalIndexer2D,
-    PositionalIndexerTuple,
-    ScalarIndexer,
-    SequenceIndexer,
     Shape,
     npt,
     type_t,
@@ -102,7 +97,10 @@
     take_nd,
     unique1d,
 )
-from pandas.core.arrays._mixins import NDArrayBackedExtensionArray
+from pandas.core.arrays._mixins import (
+    NDArrayBackedExtensionArray,
+    ravel_compat,
+)
 from pandas.core.base import (
     ExtensionArray,
     NoNewAttributesMixin,
@@ -113,7 +111,6 @@
     extract_array,
     sanitize_array,
 )
-from pandas.core.indexers import deprecate_ndim_indexing
 from pandas.core.ops.common import unpack_zerodim_and_defer
 from pandas.core.sorting import nargsort
 from pandas.core.strings.object_array import ObjectStringArrayMixin
@@ -1484,6 +1481,7 @@ def _validate_scalar(self, fill_value):
 
     # -------------------------------------------------------------
 
+    @ravel_compat
     def __array__(self, dtype: NpDtype | None = None) -> np.ndarray:
         """
         The numpy array interface.
@@ -1934,7 +1932,10 @@ def __iter__(self):
         """
         Returns an Iterator over the values of this Categorical.
         """
-        return iter(self._internal_get_values().tolist())
+        if self.ndim == 1:
+            return iter(self._internal_get_values().tolist())
+        else:
+            return (self[n] for n in range(len(self)))
 
     def __contains__(self, key) -> bool:
         """
@@ -2053,27 +2054,6 @@ def __repr__(self) -> str:
 
     # ------------------------------------------------------------------
 
-    @overload
-    def __getitem__(self, key: ScalarIndexer) -> Any:
-        ...
-
-    @overload
-    def __getitem__(
-        self: CategoricalT,
-        key: SequenceIndexer | PositionalIndexerTuple,
-    ) -> CategoricalT:
-        ...
-
-    def __getitem__(self: CategoricalT, key: PositionalIndexer2D) -> CategoricalT | Any:
-        """
-        Return an item.
-        """
-        result = super().__getitem__(key)
-        if getattr(result, "ndim", 0) > 1:
-            result = result._ndarray
-            deprecate_ndim_indexing(result)
-        return result
-
     def _validate_listlike(self, value):
         # NB: here we assume scalar-like tuples have already been excluded
         value = extract_array(value, extract_numpy=True)
@@ -2311,7 +2291,19 @@ def _concat_same_type(
     ) -> CategoricalT:
         from pandas.core.dtypes.concat import union_categoricals
 
-        return union_categoricals(to_concat)
+        result = union_categoricals(to_concat)
+
+        # in case we are concatenating along axis != 0, we need to reshape
+        #  the result from union_categoricals
+        first = to_concat[0]
+        if axis >= first.ndim:
+            raise ValueError
+        if axis == 1:
+            if not all(len(x) == len(first) for x in to_concat):
+                raise ValueError
+            # TODO: Will this get contiguity wrong?
+            result = result.reshape(-1, len(to_concat), order="F")
+        return result
 
     # ------------------------------------------------------------------
 
@@ -2699,6 +2691,11 @@ def _get_codes_for_values(values, categories: Index) -> np.ndarray:
     """
     dtype_equal = is_dtype_equal(values.dtype, categories.dtype)
 
+    if values.ndim > 1:
+        flat = values.ravel()
+        codes = _get_codes_for_values(flat, categories)
+        return codes.reshape(values.shape)
+
     if isinstance(categories.dtype, ExtensionDtype) and is_object_dtype(values):
         # Support inferring the correct extension dtype from an array of
         # scalar objects. e.g.

pandas/tests/extension/test_categorical.py

@@ -303,3 +303,14 @@ def test_not_equal_with_na(self, categories):
 
 class TestParsing(base.BaseParsingTests):
     pass
+
+
+class Test2DCompat(base.Dim2CompatTests):
+    def test_repr_2d(self, data):
+        # Categorical __repr__ doesn't include "Categorical", so we need
+        #  to special-case
+        res = repr(data.reshape(1, -1))
+        assert res.count("\nCategories") == 1
+
+        res = repr(data.reshape(-1, 1))
+        assert res.count("\nCategories") == 1