BUG: Dataframe.fillna with np.nan for dtype=category(GH 14021)

Author: conquistador1492

doc/source/whatsnew/v0.19.0.txt

@@ -1061,6 +1061,7 @@ Bug Fixes
 - Bug where ``pd.read_gbq()`` could throw ``ImportError: No module named discovery`` as a result of a naming conflict with another python package called apiclient  (:issue:`13454`)
 - Bug in ``Index.union`` returns an incorrect result with a named empty index (:issue:`13432`)
 - Bugs in ``Index.difference`` and ``DataFrame.join`` raise in Python3 when using mixed-integer indexes (:issue:`13432`, :issue:`12814`)
+- Bug in ``DataFrame(..., dtype='category').fillna(value=np.nan)`` raise ``KeyError`` (:issue:`14021`)
 - Bug in ``.to_excel()`` when DataFrame contains a MultiIndex which contains a label with a NaN value (:issue:`13511`)
 - Bug in invalid frequency offset string like "D1", "-2-3H" may not raise ``ValueError (:issue:`13930`)
 - Bug in ``concat`` and ``groupby`` for hierarchical frames with ``RangeIndex`` levels (:issue:`13542`).

pandas/core/categorical.py

@@ -1444,7 +1444,10 @@ def fillna(self, value=None, method=None, limit=None):
             mask = values == -1
             if mask.any():
                 values = values.copy()
-                values[mask] = self.categories.get_loc(value)
+                if isnull(value):
+                    values[mask] = -1
+                else:
+                    values[mask] = self.categories.get_loc(value)
 
         return self._constructor(values, categories=self.categories,
                                  ordered=self.ordered, fastpath=True)

pandas/tests/test_categorical.py

@@ -4100,6 +4100,31 @@ def f():
         res = df.fillna("a")
         tm.assert_frame_equal(res, df_exp)
 
+        # GH 14021
+        cat = Categorical([np.nan, 2, np.nan])
+        val = Categorical([np.nan, np.nan, np.nan])
+        df = DataFrame({"cats": cat, "vals": val})
+        res = df.fillna(df.median())
+        v_exp = [np.nan, np.nan, np.nan]
+        df_exp = pd.DataFrame({"cats": [2, 2, 2], "vals": v_exp},
+                              dtype='category')
+        tm.assert_frame_equal(res, df_exp)
+
+        idx = pd.DatetimeIndex(['2011-01-01 09:00', '2016-01-01 23:45',
+                                '2011-01-01 09:00', pd.NaT, pd.NaT])
+        df = DataFrame({'a': pd.Categorical(idx)})
+        tm.assert_frame_equal(df.fillna(value=pd.NaT), df)
+
+        idx = pd.PeriodIndex(['2011-01', '2011-01', '2011-01',
+                              pd.NaT, pd.NaT], freq='M')
+        df = DataFrame({'a': pd.Categorical(idx)})
+        tm.assert_frame_equal(df.fillna(value=pd.NaT), df)
+
+        idx = pd.TimedeltaIndex(['1 days', '2 days',
+                                 '1 days', pd.NaT, pd.NaT])
+        df = pd.DataFrame({'a': pd.Categorical(idx)})
+        tm.assert_frame_equal(df.fillna(value=pd.NaT), df)
+
     def test_astype_to_other(self):
 
         s = self.cat['value_group']