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BUG: remove_unused_categories dtype coerces to int64 #13261

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BUG: remove_unused_categories dtype coerces to int64 #13261

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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v0.18.2.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -184,3 +184,5 @@ Bug Fixes


- Bug in ``groupby`` where ``apply`` returns different result depending on whether first result is ``None`` or not (:issue:`12824`)

- Bug in ``Categorical.remove_unused_categories()`` changes ``.codes`` dtype to platform int (:issue:`13261`)
2 changes: 1 addition & 1 deletion pandas/core/categorical.py
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Expand Up @@ -883,8 +883,8 @@ def remove_unused_categories(self, inplace=False):
if idx.size != 0 and idx[0] == -1: # na sentinel
idx, inv = idx[1:], inv - 1

cat._codes = inv
cat._categories = cat.categories.take(idx)
cat._codes = _coerce_indexer_dtype(inv, self._categories)

if not inplace:
return cat
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21 changes: 12 additions & 9 deletions pandas/tests/test_categorical.py
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Expand Up @@ -1022,14 +1022,14 @@ def f():
def test_remove_unused_categories(self):
c = Categorical(["a", "b", "c", "d", "a"],
categories=["a", "b", "c", "d", "e"])
exp_categories_all = np.array(["a", "b", "c", "d", "e"])
exp_categories_dropped = np.array(["a", "b", "c", "d"])
exp_categories_all = Index(["a", "b", "c", "d", "e"])
exp_categories_dropped = Index(["a", "b", "c", "d"])

self.assert_numpy_array_equal(c.categories, exp_categories_all)

res = c.remove_unused_categories()
self.assert_numpy_array_equal(res.categories, exp_categories_dropped)
self.assert_numpy_array_equal(c.categories, exp_categories_all)
self.assert_index_equal(res.categories, exp_categories_dropped)
self.assert_index_equal(c.categories, exp_categories_all)

res = c.remove_unused_categories(inplace=True)
self.assert_numpy_array_equal(c.categories, exp_categories_dropped)
Expand All @@ -1039,15 +1039,18 @@ def test_remove_unused_categories(self):
c = Categorical(["a", "b", "c", np.nan],
categories=["a", "b", "c", "d", "e"])
res = c.remove_unused_categories()
self.assert_numpy_array_equal(res.categories,
np.array(["a", "b", "c"]))
self.assert_numpy_array_equal(c.categories, exp_categories_all)
self.assert_index_equal(res.categories,
Index(np.array(["a", "b", "c"])))
exp_codes = np.array([0, 1, 2, -1], dtype=np.int8)
self.assert_numpy_array_equal(res.codes, exp_codes)
self.assert_index_equal(c.categories, exp_categories_all)

val = ['F', np.nan, 'D', 'B', 'D', 'F', np.nan]
cat = pd.Categorical(values=val, categories=list('ABCDEFG'))
out = cat.remove_unused_categories()
self.assert_numpy_array_equal(out.categories, ['B', 'D', 'F'])
self.assert_numpy_array_equal(out.codes, [2, -1, 1, 0, 1, 2, -1])
self.assert_index_equal(out.categories, Index(['B', 'D', 'F']))
exp_codes = np.array([2, -1, 1, 0, 1, 2, -1], dtype=np.int8)
self.assert_numpy_array_equal(out.codes, exp_codes)
self.assertEqual(out.get_values().tolist(), val)

alpha = list('abcdefghijklmnopqrstuvwxyz')
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