Merge branch 'master' of https://github.com/pandas-dev/pandas

Author: jacobaustin123

doc/source/whatsnew/v1.1.0.rst

@@ -436,6 +436,7 @@ Categorical
 - Bug where :class:`Categorical` comparison operator ``__ne__`` would incorrectly evaluate to ``False`` when either element was missing (:issue:`32276`)
 - :meth:`Categorical.fillna` now accepts :class:`Categorical` ``other`` argument (:issue:`32420`)
 - Bug where :meth:`Categorical.replace` would replace with ``NaN`` whenever the new value and replacement value were equal (:issue:`33288`)
+- Bug where an ordered :class:`Categorical` containing only ``NaN`` values would raise rather than returning ``NaN`` when taking the minimum or maximum  (:issue:`33450`)
 
 Datetimelike
 ^^^^^^^^^^^^

pandas/core/arrays/categorical.py

@@ -2145,7 +2145,7 @@ def min(self, skipna=True):
 
         good = self._codes != -1
         if not good.all():
-            if skipna:
+            if skipna and good.any():
                 pointer = self._codes[good].min()
             else:
                 return np.nan
@@ -2180,7 +2180,7 @@ def max(self, skipna=True):
 
         good = self._codes != -1
         if not good.all():
-            if skipna:
+            if skipna and good.any():
                 pointer = self._codes[good].max()
             else:
                 return np.nan

pandas/core/arrays/integer.py

@@ -571,10 +571,6 @@ def _reduce(self, name: str, skipna: bool = True, **kwargs):
         if np.isnan(result):
             return libmissing.NA
 
-        # if we have a boolean op, don't coerce
-        if name in ["any", "all"]:
-            pass
-
         return result
 
     def _maybe_mask_result(self, result, mask, other, op_name: str):

pandas/tests/arrays/categorical/test_analytics.py

@@ -88,6 +88,14 @@ def test_min_max_with_nan(self, skipna):
             assert _min == 2
             assert _max == 1
 
+    @pytest.mark.parametrize("function", ["min", "max"])
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_min_max_only_nan(self, function, skipna):
+        # https://github.com/pandas-dev/pandas/issues/33450
+        cat = Categorical([np.nan], categories=[1, 2], ordered=True)
+        result = getattr(cat, function)(skipna=skipna)
+        assert result is np.nan
+
     @pytest.mark.parametrize("method", ["min", "max"])
     def test_deprecate_numeric_only_min_max(self, method):
         # GH 25303