Account for categorical dtype

pandas/core/groupby/groupby.py

@@ -84,6 +84,7 @@ class providing the base-class of operations.
     needs_i8_conversion,
     pandas_dtype,
 )
+from pandas.core.dtypes.dtypes import CategoricalDtype
 from pandas.core.dtypes.missing import (
     isna,
     na_value_for_dtype,
@@ -2009,7 +2010,7 @@ def _convert_result_dtype(
 
         converted_result_values = np.empty(out_shape, dtype=out_dtype)
         if func not in cy_op.cast_blocklist:
-            res_dtype = cy_op._get_result_dtype(timezone_free_orig_input_values.dtype)
+            res_dtype = cy_op._get_result_dtype(input_values.dtype)
             converted_result_values = maybe_downcast_to_dtype(
                 converted_result_values, res_dtype
             )
@@ -2052,9 +2053,11 @@ def _preprocess_input_values(self, func, input_values: ArrayLike) -> ArrayLike:
             input_values = input_values.view("int64")
         elif dtype.kind == "b":
             input_values = input_values.view("uint8")
-
-        if input_values.dtype == "float16":
+        elif input_values.dtype == "float16":
             input_values = input_values.astype(np.float32)
+        elif isinstance(dtype, CategoricalDtype):
+            input_values = input_values[0].astype(bool)
+            input_values = input_values[None, :]
 
         if func in ["any", "all"]:
             input_values = input_values.astype(bool, copy=False).view(np.int8)