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BUG: Dataframe.fillna with np.nan for dtype=category(GH 14021) #14051

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BUG: Dataframe.fillna with np.nan for dtype=category(GH 14021) #14051

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.19.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -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`).
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5 changes: 4 additions & 1 deletion pandas/core/categorical.py
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Expand Up @@ -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)
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25 changes: 25 additions & 0 deletions pandas/tests/test_categorical.py
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Expand Up @@ -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])
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add a similar test that uses datetimelike and NaT (in fact ideally loop over DTI, TDI, PI)

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@jreback Fixed

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']
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