BUG: Categorical.fillna with iterables

doc/source/whatsnew/v0.23.1.txt

@@ -66,6 +66,7 @@ Categorical
 ^^^^^^^^^^^
 
 - Bug in :func:`pandas.util.testing.assert_index_equal` which raised ``AssertionError`` incorrectly, when comparing two :class:`CategoricalIndex` objects with param ``check_categorical=False`` (:issue:`19776`)
+- Bug in :meth:`Categorical.fillna` incorrectly raising a ``TypeError`` when `value` the individual categories are iterable and `value` is an iterable (:issue:`21097`, :issue:`19788`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/arrays/categorical.py

@@ -12,6 +12,7 @@
 from pandas.core.dtypes.generic import (
     ABCSeries, ABCIndexClass, ABCCategoricalIndex)
 from pandas.core.dtypes.missing import isna, notna
+from pandas.core.dtypes.inference import is_hashable
 from pandas.core.dtypes.cast import (
     maybe_infer_to_datetimelike,
     coerce_indexer_dtype)
@@ -1751,7 +1752,7 @@ def fillna(self, value=None, method=None, limit=None):
                 values[indexer] = values_codes[values_codes != -1]
 
             # If value is not a dict or Series it should be a scalar
-            elif is_scalar(value):
+            elif is_hashable(value):
                 if not isna(value) and value not in self.categories:
                     raise ValueError("fill value must be in categories")
 

pandas/tests/categorical/test_missing.py

@@ -1,4 +1,6 @@
 # -*- coding: utf-8 -*-
+import collections
+
 import numpy as np
 import pytest
 
@@ -68,3 +70,16 @@ def test_fillna_raises(self, fillna_kwargs, msg):
 
         with tm.assert_raises_regex(ValueError, msg):
             cat.fillna(**fillna_kwargs)
+
+    @pytest.mark.parametrize("named", [True, False])
+    def test_fillna_iterable_category(self, named):
+        # https://github.com/pandas-dev/pandas/issues/21097
+        if named:
+            Point = collections.namedtuple("Point", "x y")
+        else:
+            Point = lambda *args: args  # tuple
+        cat = Categorical([Point(0, 0), Point(0, 1), None])
+        result = cat.fillna(Point(0, 0))
+        expected = Categorical([Point(0, 0), Point(0, 1), Point(0, 0)])
+
+        tm.assert_categorical_equal(result, expected)