more informative error message with np.min or np.max on unordered Categorical

doc/source/whatsnew/v1.1.0.rst

@@ -778,6 +778,7 @@ Other
 - Bug in :meth:`DataFrame.__dir__` caused a segfault when using unicode surrogates in a column name (:issue:`25509`)
 - Bug in :meth:`DataFrame.plot.scatter` caused an error when plotting variable marker sizes (:issue:`32904`)
 - :class:`IntegerArray` now implements the ``sum`` operation (:issue:`33172`)
+- more informative error message with ``np.min`` or ``np.max`` on unordered Categorical (:issue:`33115`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/arrays/categorical.py

@@ -2071,7 +2071,7 @@ def _reduce(self, name, axis=0, **kwargs):
         return func(**kwargs)
 
     @deprecate_kwarg(old_arg_name="numeric_only", new_arg_name="skipna")
-    def min(self, skipna=True):
+    def min(self, skipna=True, **kwargs):
         """
         The minimum value of the object.
 
@@ -2106,7 +2106,7 @@ def min(self, skipna=True):
         return self.categories[pointer]
 
     @deprecate_kwarg(old_arg_name="numeric_only", new_arg_name="skipna")
-    def max(self, skipna=True):
+    def max(self, skipna=True, **kwargs):
         """
         The maximum value of the object.
 

pandas/tests/arrays/categorical/test_analytics.py

@@ -1,3 +1,4 @@
+import re
 import sys
 
 import numpy as np
@@ -93,6 +94,17 @@ def test_deprecate_numeric_only_min_max(self, method):
         with tm.assert_produces_warning(expected_warning=FutureWarning):
             getattr(cat, method)(numeric_only=True)
 
+    @pytest.mark.parametrize("method", ["min", "max"])
+    def test_numpy_min_max_raises(self, method):
+        cat = Categorical(["a", "b", "c", "b"], ordered=False)
+        msg = (
+            f"Categorical is not ordered for operation {method}\n"
+            "you can use .as_ordered() to change the Categorical to an ordered one"
+        )
+        method = getattr(np, method)
+        with pytest.raises(TypeError, match=re.escape(msg)):
+            method(cat)
+
     @pytest.mark.parametrize(
         "values,categories,exp_mode",
         [